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• v.37(1); 2014 May

The Evidence-Based Practice of Applied Behavior Analysis

Timothy a. slocum.

Utah State University, Logan, UT USA

Ronnie Detrich

Wing Institute, Oakland, CA USA

Susan M. Wilczynski

Ball State University, Muncie, IN USA

Trina D. Spencer

Northern Arizona University, Flagstaff, AZ USA

Oregon State University, Corvallis, OR USA

Katie Wolfe

University of South Carolina, Columbia, SC USA

Evidence-based practice (EBP) is a model of professional decision-making in which practitioners integrate the best available evidence with client values/context and clinical expertise in order to provide services for their clients. This framework provides behavior analysts with a structure for pervasive use of the best available evidence in the complex settings in which they work. This structure recognizes the need for clear and explicit understanding of the strength of evidence supporting intervention options, the important contextual factors including client values that contribute to decision making, and the key role of clinical expertise in the conceptualization, intervention, and evaluation of cases. Opening the discussion of EBP in this journal, Smith ( The Behavior Analyst, 36 , 7–33, 2013 ) raised several key issues related to EBP and applied behavior analysis (ABA). The purpose of this paper is to respond to Smith’s arguments and extend the discussion of the relevant issues. Although we support many of Smith’s ( The Behavior Analyst, 36 , 7–33, 2013 ) points, we contend that Smith’s definition of EBP is significantly narrower than definitions that are used in professions with long histories of EBP and that this narrowness conflicts with the principles that drive applied behavior analytic practice. We offer a definition and framework for EBP that aligns with the foundations of ABA and is consistent with well-established definitions of EBP in medicine, psychology, and other professions. In addition to supporting the systematic use of research evidence in behavior analytic decision making, this definition can promote clear communication about treatment decisions across disciplines and with important outside institutions such as insurance companies and granting agencies.

Almost 45 years ago, Baer et al. ( 1968 ) described a new discipline—applied behavior analysis (ABA). This discipline was distinguished from the experimental analysis of behavior by its focus on social impact (i.e., solving socially important problems in socially important settings). ABA has produced remarkably powerful interventions in fields such as education, developmental disabilities and autism, clinical psychology, behavioral medicine, organizational behavior management, and a host of other fields and populations. Behavior analysts have long recognized that developing interventions capable of improving client behavior solves only one part of the problem. The problem of broad social impact must be solved by having interventions implemented effectively in socially important settings and at scales of social importance (Baer et al. 1987 ; Horner et al. 2005b ; McIntosh et al. 2010 ). This latter set of challenges has proved to be more difficult. In many cases, demonstrations of effectiveness are not sufficient to produce broad adoption and careful implementation of these procedures. Key decision makers may be more influenced by variables other than the increases and decreases in the behaviors of our clients. In addition, even when client behavior is a very powerful factor in decision making, it does not guarantee that empirical data will be the basis for treatment selection; anecdotes, appeals to philosophy, or marketing have been given priority over evidence of outcomes (Carnine 1992 ; Polsgrove 2003 ).

Across settings in which behavior analysts work, there has been a persistent gap between what is known from research and what is actually implemented in practice. Behavior analysts have been concerned with the failed adoption of research-based practices for years (Baer et al. 1987 ). Even in the fields in which behavior analysts have produced powerful interventions, the vast majority of current practice fails to take advantage of them.

Behavior analysts have not been alone in recognizing serious problems with the quality of interventions used employed in practice settings. In the 1960s, many within the medical field recognized a serious research-to-practice gap. Studies suggested that a relatively small percentage (estimates range from 10 to 25 %) of medical treatment decisions were based on high-quality evidence (Goodman 2003 ). This raised the troubling question of what basis was used for the remaining decisions if it was not high-quality evidence. These concerns led to the development of evidence-based practice (EBP) of medicine (Goodman 2003 ; Sackett et al. 1996 ).

The research-to-practice gap appears to be universal across professions. For example, Kazdin ( 2000 ) has reported that less than 10 % of the child and adolescent mental health treatments reported in the professional literature have been systematically evaluated and found to be effective and those that have not been evaluated are more likely to be adopted in practice settings. In recognition of their own research-to-practice gaps, numerous professions have adopted an EBP framework. Nursing and other areas of health care, social work, clinical and educational psychology, speech and language pathology, and many others have adopted this framework and adapted it to the specific needs of their discipline to help guide decision-making. Not only have EBP frameworks been helping to structure professional practice, but they have also been used to guide federal policy. With the passage of No Child Left Behind ( 2002 ) and the reauthorization of the Individuals with Disabilities Education Improvement Act ( 2005 ), the federal department of education has aligned itself with the EBP movement. A recent memorandum from the federal Office of Management and Budget instructed agencies to consider evidence of effectiveness when awarding funds, increase the use of evidence in competitions, and to encourage widespread program evaluation (Zients 2012 ). The memo, which used the term evidence-based practice extensively, stated: “Where evidence is strong, we should act on it. Where evidence is suggestive, we should consider it. Where evidence is weak, we should build the knowledge to support better decisions in the future” (Zients 2012 , p. 1).

EBP is more broadly an effort to improve decision-making in applied settings by explicitly articulating the central role of evidence in these decisions and thereby improving outcomes. It addresses one of the long-standing challenges for ABA; the need to effectively support and disseminate interventions in the larger social systems in which our work is embedded. In particular, EBP addresses the fact that many decision-makers are not sufficiently influenced by the best evidence that is relevant to important decisions. EBP is an explicit statement of one of ABA’s core tenets—a commitment to evidence-based decision-making. Given that the EBP framework is well established in many disciplines closely related to ABA and in the larger institutional contexts in which we operate (e.g., federal policy and funding agencies), aligning ABA with EBP offers an opportunity for behavior analysts to work more effectively within broader social systems.

Discussion of issues related to EBP in ABA has taken place across several years. Researchers have extensively discussed methods for identifying well-supported treatments (e.g., Horner et al. 2005a ; Kratochwill et al. 2010 ), and systematically reviewed the evidence to identify these treatments (e.g., Maggin et al. 2011 ; National Autism Center 2009 ). However, until recently, discussion of an explicit definition of EBP in ABA has been limited to conference papers (e.g., Detrich 2009 ). Smith ( 2013 ) opened a discussion of the definition and critical features of EBP of ABA in the pages of The Behavior Analyst . In his thought-provoking article, Smith raised many important points that deserve serious discussion as the field moves toward a clear vision of EBP of ABA. Most importantly, Smith ( 2013 ) argued that behavior analysts must carefully consider how EBP is to be defined and understood by researchers and practitioners of behavior analysis.

Definitions Matter

We find much to agree with in Smith’s paper, and we will describe these points of agreement below. However, we have a core disagreement with Smith concerning the vision of what EBP is and how it might enhance and expand the effective practice of ABA. As behavior analysts know, definitions matter. A well-conceived definition can promote conceptual understanding and set the context for effective action. Conversely, a poor definition or confusion about definitions hinders clear understanding, communication, and action.

In providing a basis for his definition of EBP, Smith refers to definitions in professions that have well-developed conceptions of EBP. He quotes the American Psychological Association (APA) ( 2005 ) definition (which we quote here more extensively than he did):

Evidence-based practice in psychology (EBPP) is the integration of the best available research with clinical expertise in the context of patient characteristics, culture, and preferences. This definition of EBPP closely parallels the definition of evidence-based practice adopted by the Institute of Medicine ( 2001 , p. 147) as adapted from Sackett et al. ( 2000 ): “Evidence-based practice is the integration of best research evidence with clinical expertise and patient values.” The purpose of EBPP is to promote effective psychological practice and enhance public health by applying empirically supported principles of psychological assessment, case formulation, therapeutic relationship, and intervention.

The key to understanding this definition is to note how APA and the Institute of Medicine use the word practice . Clearly, practice does not refer to an intervention; instead, it references one’s professional behavior. This is the sense in which one might speak of the professional practice of behavior analysis. American Psychological Association Presidential Task Force of Evidence-Based Practice ( 2006 ) further elaborates this point:

It is important to clarify the relation between EBPP and empirically supported treatments (ESTs)…. ESTs are specific psychological treatments that have been shown to be efficacious in controlled clinical trials, whereas EBPP encompasses a broader range of clinical activities (e.g., psychological assessment, case formulation, therapy relationships). As such, EBPP articulates a decision-making process for integrating multiple streams of research evidence—including but not limited to RCTs—into the intervention process. (p. 273)

In contrast, Smith defined EBP not as a decision-making process but as a set of interventions that have been shown to be efficacious through rigorous research. He stated:

An evidence-based practice is a service that helps solve a consumer’s problem. Thus it is likely to be an integrated package of procedures, operationalized in a manual, and validated in studies of socially meaningful outcomes, usually with group designs. (p. 27).

Smith’s EBP is what APA has clearly labeled an empirically supported treatment . This is a common misconception found in conversation and in published articles (e.g., Cook and Cook 2013 ) but at odds with formal definitions provided by many professional organizations; definitions which result from extensive consideration and debate by representative leaders of each professional field (e.g., APA 2005 ; American Occupational Therapy Association 2008 ; American Speech-Language Hearing Association 2005 ; Institute of Medicine 2001 ).

Before entering into the discussion of a useful definition of EBP of ABA, we should clarify the functions that we believe a useful definition of EBP should perform. First, a useful definition should align with the philosophical tenets of ABA, support the most effective current practice of ABA, and contribute to further improvement of ABA practice. A definition that is in conflict with the foundations of ABA or detracts from effective practice clearly would be counterproductive. Second, a useful definition of EBP of ABA should enhance social support for ABA practice by describing its empirical basis and decision-making processes in a way that is understandable to professions that already have well-established definitions of EBP. A definition that corresponds with the fundamental components of EBP in other fields would promote ABA practice by improving communication with external audiences. This improved communication is critical in the interdisciplinary contexts in which behavior analysts often practice and for legitimacy among those familiar with EBP who often control local contingencies (e.g., policy makers and funding agencies).

Based on these functions, we propose the following definition: Evidence-based practice of applied behavior analysis is a decision-making process that integrates (a) the best available evidence with (b) clinical expertise and (c) client values and context. This definition positions EBP as a pervasive feature of all professional decision-making by a behavior analyst with respect to client services; it is not limited to a narrowly restricted set of situations or decisions. The definition asserts that the best available evidence should be a primary influence on all decision-making related to services for clients (e.g., intervention selection, progress monitoring, etc.). It also recognizes that evidence cannot be the sole basis for a decision; effective decision-making in a discipline as complex as ABA requires clinical expertise in identifying, defining, and analyzing problems, determining what evidence is relevant, and deciding how it should be applied. In the absence of this decision-making framework, practitioners of ABA would be conceptualized as behavioral technicians rather than analysts. Further, the definition of EBP of ABA includes client values and context. Decision-making is necessarily based on a set of values that determine the goals that are to be pursued and the means that are appropriate to achieve them. Context is included in recognition of the fact that the effectiveness of an intervention is highly dependent upon the context in which it is implemented. The definition asserts that effective decision-making must be informed by important contextual factors. We elaborate on each component of the definition below, but first we contrast our definition with that offered by Smith ( 2013 ).

Although Smith ( 2013 ) made brief reference to the other critical components of EBP, he framed EBP as a list of multicomponent interventions that can claim a sufficient level of research support. We agree with his argument that such lists are valuable resources for practitioners and therefore developing them should be a goal of researchers. However, such lists are not, by themselves , a powerful means of improving the effectiveness of behavior analytic practice. The vast majority of decisions faced in the practice of behavior analysis cannot be made by implementing the kind of manualized, multicomponent treatment packages described by Smith.

There are a number of reasons a list of interventions is not an adequate basis for EBP of ABA. First, there are few interventions that qualify as “practices” under Smith’s definition. For example, when discussing the importance of manuals for operationalizing treatments, Smith stated that the requirement that a “practice” be based on a manual, “sharply reduces the number of ABA approaches that can be regarded as evidence based. Of the 11 interventions for ASD identified in the NAC ( 2009 ) report, only the three that have been standardized in manuals might be considered to be practices, and even these may be incomplete” (p. 18). Thus, although the example referenced the autism treatment literature, it seems apparent that even a loose interpretation of this particular criterion would leave all practitioners with a highly restricted number of intervention options.

Second, even if more “practices” were developed and validated, many consumers cannot be well served with existing multicomponent packages. In order to meet their clients’ needs, behavior analysts must be able to selectively implement focused interventions alone or in combination. This flexibility is necessary to meet the diverse needs of their clients and to minimize the response demands on direct care providers or staff, who are less likely to implement a complicated intervention with fidelity (Riley-Tillman and Chafouleas 2003 ).

Third, the strategy of assembling a list of treatments and describing these as “practices” severely limits the ways in which research findings are used by practitioners. With the list approach to defining EBP, research only impacts practice by placing an intervention on a list when a specific criteria has been met. Thus, any research on an intervention that is not sufficiently broad or manualized to qualify as a “practice” has no influence on EBP. Similarly, a research study that shows clear results but is not part of a sufficient body of support for an intervention would also have no influence. A study that provides suggestive results but is not methodologically strong enough to be definitive would have no influence, even if it were the only study that is relevant to a given problem.

The primary problem with a list approach is that it does not provide a strong framework that directs practitioners to include the best available evidence in all of their professional decision-making. Too often, practitioners who consult such lists find that no interventions relevant to their specific case have been validated as “evidence-based” and therefore EBP is irrelevant. In contrast, definitions of EBP as a decision-making process can provide a robust framework for including research evidence along with clinical expertise and client values and context in the practice of behavior analysis. In the next sections, we explore the components of this definition in more detail.

Best Available Evidence

The term “best available evidence” occupies a critical and central place in the definition and concept of EBP; this aligns with the fundamental reliance on scientific research that is one of the core tenets of ABA. The Behavior Analyst Certification Board ( 2010 ) Guidelines for Responsible Conduct for Behavior Analysts repeatedly affirm ways in which behavior analysts should base their professional conduct on the best available evidence. For example:

Behavior analysts rely on scientifically and professionally derived knowledge when making scientific or professional judgments in human service provision, or when engaging in scholarly or professional endeavors.

• The behavior analyst always has the responsibility to recommend scientifically supported most effective treatment procedures. Effective treatment procedures have been validated as having both long-term and short-term benefits to clients and society.
• Clients have a right to effective treatment (i.e., based on the research literature and adapted to the individual client).

A Continuum of Evidence Quality

The term best implies that evidence can be of varying quality, and that better quality evidence is preferred over lower quality evidence. Quality of evidence for informing a specific practical question involves two dimensions: (a) relevance of the evidence and (b) certainty of the evidence.

The dimension of relevance recognizes that some evidence is more germane to a particular decision than is other evidence. This idea is similar to the concept of external validity. External validity refers to the degree to which research results apply to a range of applied situations whereas relevance refers to the degree to which research results apply to a specific applied situation. In general, evidence is more relevant when it matches the particular situation in terms of (a) important characteristics of the clients, (b) specific treatments or interventions under consideration, (c) outcomes or target behaviors including their functions, and (d) contextual variables such as the physical and social environment, staff skills, and the capacity of the organization. Unless all conditions match perfectly, behavior analysts are necessarily required to use their expertise to determine the applicability of the scientific evidence to each unique clinical situation. Evidence based on functionally similar situations is preferred over evidence based on situations that share fewer important characteristics with the specific practice situation. However, functional similarity between a study or set of studies and a particular applied problem is not always obvious.

The dimension of certainty of evidence recognizes that some evidence provides stronger support for claims that a particular intervention produced a specific result. Any instance of evidence can be evaluated for its methodological rigor or internal validity (i.e., the degree to which it provides strong support for the claim of effectiveness and rules out alternative explanations). Anecdotes are clearly weaker than more systematic observations, and well-controlled experiments provide the strongest evidence. Methodological rigor extends to the quality of the dependent measure, treatment fidelity, and other variables of interest (e.g., maintenance of skill acquisition), all of which influence the certainty of evidence. But the internal validity of any particular study is not the only variable influencing the certainty of evidence; the quantity of evidence supporting a claim is also critical to its certainty. Both systematic and direct replication are vital for strengthening claims of effectiveness (Johnston and Pennypacker 1993 ; Sidman 1960 ). Certainty of evidence is based on both the rigor of each bit of evidence and the degree to which the findings have been consistently replicated. Although these issues are simple in principle, operationalizing and measuring rigor of research is extremely complex. Numerous quality appraisal systems for both group and single-subject research have been proposed and used in systematic reviews (see below for more detail).

Under ideal circumstances, consistently high-quality evidence that closely matches the specifics of the practice situation is available; unfortunately, this is not always the case, and evidence-based practitioners of ABA must proceed despite an imperfect evidence base. The mandate to use the best available evidence specifies that the practitioner make decisions based on the best evidence that is available. Although this statement may seem rather obvious, the point is worth underscoring because the implications are highly relevant to behavior analysts. In an area with considerable high-quality relevant research, the standards for evidence should be quite high. But in an area with more limited research, the practitioner should take advantage of the best evidence that is available. This may require tentative reliance on research that is somewhat weaker or is only indirectly relevant to the specific situation at hand. For example, ideally, evidence-based practitioners of ABA would rely on well-controlled experimental results that have been replicated with the precise population with whom they are working. However, if this kind of evidence is not available, they might have to make decisions based on a single study that involves a similar but not identical population.

This idea of using the best of the available evidence is very different from one of using only extremely high-quality evidence (i.e., empirically supported treatments). If we limit EBP to considering only the highest quality evidence, we leave the practitioner with no guidance in the numerous situations in which high-quality and directly relevant evidence (i.e., precise matching of setting, function, behavior, motivating operations and precise procedures) simply does not exist. This approach would lead to a form of EBP that is irrelevant to the majority of decisions that a behavior analyst must make on a daily basis. Instead, our proposed definition of EBP asserts that the practitioner should be informed by the best evidence that is available.

Expanding Research on Utility of Treatments

Smith ( 2013 ) argued that the research methods used by behavior analysts to evaluate these treatments should be expanded to more comprehensively describe the utility of interventions. He suggested that too much ABA research is conducted in settings that do not approximate typical service settings, optimizing experimental control at the expense of external validity. Along this same line of reasoning, he noted that it is important to test the generality of effects across clients and identify variables that predict differential effectiveness. He suggested systematically reporting results from all research participants (e.g., the intent-to-treat model), and purposive selection of participants would provide a more complete account of the situations in which treatments are successful and those in which they are unsuccessful. Smith argued that researchers should include more distal and socially important outcomes because with a narrow target “behavior may change, but remain a problem for the individual or may be only a small component of a much larger cluster of problems such as addiction or delinquency.” He pointed out that in order to best support effective practice, research must demonstrate that an intervention produces or contributes to producing the socially important outcomes that would cause a consumer to say that the problem is solved.

Further, Smith argues that many of the questions most relevant to EBP—questions about the likely outcomes of a treatment when applied in a particular type of situation—are well suited to group research designs. He argued that RCTs are likely to be necessary within a program of research because:

most problems pose important actuarial questions (e.g., determining whether an intervention package is more effective than community treatment as usual; deciding whether to invest in one intervention package or another, both, or neither; and determining whether the long-term benefits justify the resources devoted to the intervention)…. A particularly important actuarial issue centers on the identification of the conditions under which the intervention is most likely to be effective. (p. 23)

We agree that selection of research methods should be driven by the kinds of questions being asked and that group research designs are the methods of choice for some types of questions that are central to EBP. Therefore, we support Smith’s call for increased use of group research designs within ABA. If practice decisions are to be informed by the best available evidence, we must take advantage of both group and single-subject designs. However, we disagree with Smith’s statement that EBP should be limited to treatments that are validated “usually with group designs” (Smith, p. 27). Practitioners should be supported by reviews of research that draw from all of the available evidence and provide the best recommendations possible given the state of knowledge on the particular question. In most areas of behavior analytic practice, single-subject research makes up a large portion of the best available evidence. The Institute for Education Science (IES) has recognized the contribution single case designs can make toward identifying effective practices and has recently established standards for evaluating the quality of single case design studies (Institute of Educational Sciences, n.d. ; Kratochwill et al. 2013 ).

Classes of Evidence

Identifying the best available evidence to inform specific practice decisions is extremely complex, and no single currently available source of evidence can adequately inform all aspects of practice. Therefore, we outline a number of strategies for identifying and summarizing evidence in ways that can support the EBP of ABA. We do not intend to cover all sources of evidence comprehensively, but merely outline some of the options available to behavior analysts.

Empirically Supported Treatment Reviews

Empirically supported treatments (EST) are identified through a particular form of systematic literature review. Systematic reviews bring a rigorous methodology to the process of reviewing research. The development and use of these methods are, in part, a response to the recognition that the process of reviewing the literature is subject to threats to validity. The systematic review process is characterized by explicitly stated and replicable methods for (a) searching for studies, (b) screening studies for relevance to the review question, (c) appraising the methodological quality of studies, (d) describing outcomes from each study, and (e) determining the degree to which the treatment (or treatments) is supported by the research. When the evidence in support of a treatment is plentiful and of high quality, the treatment generally earns the status of an EST. Many systematic reviews, however, find that no intervention for a particular problem has sufficient evidence to qualify as an EST.

Well-known organizations in medicine (e.g., Cochrane Collaboration), education (e.g., What Works Clearinghouse), and mental health (e.g., National Registry of Evidence-based Programs and Practices) conduct EST reviews. Until recently, systematic reviews have focused nearly exclusively on group research; however, systematic reviews of single-subject research are quickly becoming more common and more sophisticated (e.g., Carr 2009 ; NAC 2009 ; Maggin et al. 2012 ).

Systematic reviews for EST status is one important way to summarize the best available evidence because it can give a relatively objective evaluation of the strength of the research literature supporting a particular intervention. But systematic reviews are not infallible; as with all other research and evaluation methods, they require skillful application and are subject to threats to validity. The results of reviews can change dramatically based on seemingly minor changes in operational definitions and procedures for locating articles, screening for relevance, describing treatments, appraising methodological quality, describing outcomes, summarizing outcomes for the body of research as a whole, and rating the degree to which an intervention is sufficiently supported (Slocum et al. 2012a ; Wilczynski 2012 ). Systematic reviews and claims based upon them must be examined critically with full recognition of their limitations just as one examines primary research reports.

Behavior analysts encounter many situations in which no ESTs have been established for the particular combination of client characteristics, target behaviors, functions, contexts, and other parameters for decision-making. This dearth may exist because no systematic review has addressed the particular problem or because a systematic review has been conducted but failed to find any well-supported treatments for the particular problem. For example, in a recent review of all of the recommendations in the empirically supported practice guides published by the IES, 45 % of the recommendations had minimal support (Slocum et al. 2012b ). As Smith noted ( 2013 ), only 3 of the 11 interventions that the NAC identified as meeting quality standards might be considered practices in the sense that they are manualized. In these common situations, a behavior analyst cannot respond by simply selecting an intervention from a list of ESTs. A comprehensive EBP of ABA requires additional strategies for reviewing research evidence and drawing practice recommendations from existing evidence—strategies that can glean the best available evidence from an imperfect research base and formulate practice recommendations that are most likely to lead to favorable outcomes under conditions of uncertainty.

Other Methods for Reviewing Research Literature

The three strategies outlined below may complement systematic reviews in guiding behavior analysts toward effective decision-making.

Narrative Reviews of the Literature

There has been a long tradition across disciplines of relying on narrative reviews to summarize what is known with respect to treatments for a class of problems (e.g., aggression) or what is known about a particular treatment (e.g., token economy). The author of the review, presumably an expert, selects the theme and synthesizes the research literature that he or she considers most relevant. Narrative reviews allow the author to consider a wide range of research including studies that are indirectly relevant (e.g., those studying a given problem with a different population or demonstrating general principles) and studies that may not qualify for systematic reviews because of methodological limitations but which illustrate important points nonetheless. Narrative reviews can consider a broader array of evidence and have greater interpretive flexibility than most systematic reviews.

As with all sources of evidence, there are difficulties with narrative reviews. The selection of the literature is left up to the author’s discretion; there are no methodological guidelines and little transparency about how the author decided which literature to include and which to exclude. There is always the risk of confirmation bias that the author emphasized literature that is consistent with her preconceived opinions. Even with a peer-review process, it is always possible that the author neglected or misinterpreted research relevant to the discussion. These concerns not withstanding, narrative reviews may provide the best available evidence when no systematic reviews exist or when substantial generalizations from the systematic review to the practice context are needed. Many textbooks (e.g., Cooper et al. 2007 ) and handbooks (e.g., Fisher et al. 2011 ; Madden et al. 2013 ) provide excellent examples of narrative reviews that can provide important guidance for evidence-based practitioners of ABA.

Best Practice Guides

Best practice guides are another source of evidence that can inform decisions in the absence of available and relevant systematic reviews. Best practice guides provide recommendations that reflect the collective wisdom of an expert panel. It is presumed that the recommendations reflect what is known from the research literature, but the validity of recommendations is largely derived from the panel’s expertise rather than from the rigor of their methodology. Recommendations from best practice panels are usually much broader than the recommendations from systematic reviews. The recommendations from these guides can provide important information about how to implement a treatment, how to adapt the treatment for specific circumstances, and what is necessary for broad scale or system-wide implementation.

The limitations to best practice guides are similar to those for narrative reviews; specifically, potential bias and lack of transparency are significant concerns. Panel members are typically not selected using a specific set of operationalized criteria. Bias is possible if the panel is drawn too narrowly. If the panel is drawn too broadly; however, the panel may have difficulty reaching a consensus (Wilczynski 2012 ).

Empirically Supported Practice Guides

Empirically supported practice guides, a more recently developed strategy, integrate the strengths of systematic reviews and best practice panels. In this type of review, an expert panel is charged with developing recommendations on a topic. As part of the process, a systematic review of the literature is conducted. Following the systematic review, the panel generates a set of recommendations and objectively determines the strength of evidence for the recommendation and assigns an evidence rating. When there is little empirical evidence directly related to a specific issue, the panel’s recommendations may have weak research support but nonetheless may be based on the best evidence that is available. The obvious advantage of empirically supported practice guides is that there is greater transparency about the review process and certainty of recommendations. Practice recommendations are usually broader than those derived from systematic reviews and address issues related to implementation and acceptable variations to enhance the treatment’s contextual fit (Shanahan et al. 2010 ; Slocum et al. 2012b ). Although empirically supported practice guides offer the objectivity of a systematic review and the flexibility of best practice guidelines, they also face potential sources of error from both methods. Systematic and explicit criteria are used to review the research and rate the level of evidence for each recommendation; however, it is the panel that formulates recommendations. Thus, results of these reviews are influenced by the selection of panel members. When research evidence is incomplete or equivocal, panelists must exercise judgment in interpreting the evidence and drawing conclusions (Shanahan et al. 2010 ).

Other Units of Analysis

Smith ( 2013 ) weighed in on the critical issue of the unit of analysis when describing and evaluating treatments (Slocum and Wilczynski 2008 ). The unit of analysis refers to whether EBP should focus on (a) principles, such as reinforcement; (b) tactics, such as backward chaining; (c) multicomponent packages, such as Functional Communication Training; or (d) even more comprehensive systems, such as Early Intensive Behavioral Intervention. After reviewing the ongoing debate between those favoring a smaller unit of analysis that focuses on specific procedures and those favoring a larger unit of analysis that evaluates the effects of multicomponent packages, Smith made a case that the multicomponent treatment package is the key unit in EBP. Smith noted that practitioners rarely solve a client’s problem with a single procedure; instead, solutions typically involve combinations of procedures. He argued that the unit should be “a service aimed at solving people’s problems” and procedures that are merely components of such services are not sufficiently complete to be the proper unit of analysis for EBP. He further stated that these treatment packages should include strategies for implementation in typical service settings and an intervention manual.

We concur that the multicomponent treatment package is a particularly significant and strategic unit of treatment because it specifies a suite of procedures and exactly how they are to be used together to solve a problem. Validated treatment packages are far more than the sum of their parts. A well-developed treatment package can be revised and optimized over many iterations in a way that would be difficult or impossible for a practitioner to accomplish independently. In addition, research outcomes from implementation of treatment packages reflect the interaction of the components, and these interactions may not be evident in the research literature on the individual components. Further, research on the outcomes from multicomponent packages can evaluate broader and more socially important outcomes than is generally possible when evaluating more narrowly defined treatments. For example, in the case of teaching a child with autism to communicate, research on a focused procedure such as time delay may indicate that its use leads to more independent communicative responses; however, research on a comprehensive Early Intensive Behavioral Intervention can evaluate the impact of the program on children’s global development or intellectual functioning.

Having recognized our agreement with Smith ( 2013 ) on the special importance of multicomponent treatment packages for EBP, we hasten to add that this type of intervention is not enough to support a broad and robust EBP of ABA. EBP must also provide guidance to the practitioner in the frequently encountered situations in which well-established treatment packages are not available. In these situations, problems may be best addressed by building an intervention from a set of elemental components. These components, referred to as practice elements (Chorpita et al. 2005 , 2007 ) or kernels (Embry 2004 ; Embry and Biglan 2008 ), may be validated either directly or indirectly. The practitioner assembles a particular combination of components to solve a specific problem. Because this newly constructed package has not been evaluated as a whole, there is additional uncertainty about the effectiveness of the package, and the quality of evidence may be considered lower than a well-supported treatment package (Slocum et al. 2012b ; Smith 2013 ; however, see Chorpita ( 2003 ) for a differing view). Nonetheless, treatment components that are supported by strong evidence provide the practitioner with tools to solve practical problems when EST packages are not relevant.

In some cases, behavior analysts are presented with problems that cannot be addressed even by assembling established components. In these cases, the ABA practitioner must apply principles of behavior to construct an intervention and must depend on these principles to guide sensible modifications of interventions in response to client needs and to support sensible implementation of interventions. Principles of behavior are broadly generalized statements describing behavioral relations. Their empirical base is extremely large and diverse including both human and nonhuman participants across numerous contexts, behaviors, and consequences. Although principles of behavior are based on an extremely broad research literature, they are also stated at a broad level. As a result, the behavior analyst must use a great deal of judgment in applying principles to particular problems and a particular attempt to apply a principle to solve a problem may not be successful. Thus, although behavioral principles are supported by evidence, newly constructed interventions based on these principles have not yet been evaluated. These interventions must be considered less certain or validated than treatment packages or elements that have been demonstrated to be effective for specific problems, populations, and context (Slocum et al. 2012b ).

Evidence-based practitioners of ABA recognize that the process of selecting and implementing treatments always includes some level of uncertainty (Detrich et al. 2013 ). One of the fundamental tenets of ABA shared with many other professions is that the best evidence regarding the effectiveness of an intervention does not come from systematic literature reviews, best practice guides, or principles of behavior, but from close continual contact with the relevant outcomes (Bushell and Baer 1994 ). The BACB guidelines ( 2010 ) state that, “behavior analysts recognize limits to the certainty with which judgments or predictions can be made about individuals” (item 3.0 [c]). As a result, “the behavior analyst collects data…needed to assess progress within the program” (item 4.07) and “modifies the program on the basis of data” (item 4.08). Thus, an important feature of the EBP of ABA is that professional decision-making does not end with the selection of an initial intervention. The process continues with ongoing progress monitoring and adjustments to the treatment plan as needed to achieve the targeted outcomes. Progress monitoring and data-based decision-making are the ultimate hedge against the inherent uncertainties of imperfect knowledge derived from research. As the quality of the best available evidence decreases, the importance of frequent direct measurement of client progress increases.

Practice decisions are always accompanied by some degree of uncertainty; however, better decisions are likely when multiple of sources of evidence are integrated. For example, a multicomponent treatment package may be an EST for clients who differ slightly from those the practitioner currently serves. Confidence in the use of this treatment may be increased if there is evidence showing the central components are effective with clients belonging to the population of interest. The principles of behavior might further inform sensible variations appropriate for the specific context of practice. When considered together, numerous sources of evidence increase the confidence the behavior analyst can have in the intervention. And when the plan is implemented, progress monitoring may reveal the need for additional adjustments. Each of these different classes of evidence provides answers to different questions for the practitioner, resulting in a more fine-grained analysis of the clinical problem and solutions to it (Detrich et al. 2013 ).

Client Values and Context

In order to be compatible with the underlying tenets of ABA, parallel with other professions, and to promote effective practice, a definition of EBP of ABA must include client values and context among the primary contributors to professional decision-making. Baer et al. ( 1968 ) suggested that the word applied refers to an immediate and important change in behavior that has practical value and that this value is determined “by the interest which society shows in the problems” (p. 92)—that is, by social values. Wolf ( 1978 ) went on to specify that behavior analytic practice can only be termed successful if it addresses goals that are meaningful to our clients, uses procedures that are judged appropriate by our clients, and produces effects that are valued by our clients. These foundational tenets of ABA correspond with the centrality of client values in classic definitions of EBP (e.g., Institute of Medicine 2001 ). Like medical professionals and those in the many other fields that have adopted similar conceptualizations of EBP, behavior analysts have long recognized that client values are critical contributors to responsible decision-making.

Behavior analysts have defined the client as the individual who is the focus of the behavior change, other individuals who are critical to the behavior change process (Baer et al. 1968 ; Heward et al. 2005 ), as well as outside individuals or groups who may have a stake in the target behavior or improved outcomes (Baer et al. 1987 ; Wolf 1978 ). Wolf ( 1978 ) argued that only our clients can judge the social validity of our work and suggested that behavior analysts address three levels of social validity: (a) the social significance of the goals, (b) the social desirability of the procedures, and (c) the social importance of the outcomes. With respect to selection of interventions, Wolf noted, “not only is it important to determine the acceptability of treatment procedures to participants for ethical reasons, it may also be that the acceptability of the program is related to effectiveness, as well as to the likelihood that the program will be adopted and supported by others” (p. 210). He further maintained that clients are the ultimate arbiters of whether or not the effects of a program are sufficiently helpful to be termed successful.

The concept of social validity directs our attention to some of the important aspects of the context of intervention. Intervention always occurs in some context and features of that context can directly influence the fidelity with which the intervention is implemented and its effectiveness. Albin et al. ( 1996 ) expanded further on the contextual variables that might be critical for designing and implementing effective interventions. They described the concept of contextual fit or the congruence of a behavioral support plan and the context and indicate that this fit will determine its implementation, effectiveness, and maintenance.

Contextual fit includes the issues of social validity, but also explicitly encompasses issues associated with the individuals who implement treatments and manage other aspects of the environments within which treatments are implemented. Behavioral intervention plans prescribe the behavior of implementers. These implementers may include professionals, such as therapists and teachers, as well as nonprofessionals, such as family and community members. It is important to consider characteristics of these implementers when developing plans because the success of a plan may hinge on how it corresponds with the values, skills, goals, and stressors of the implementers. Effective plans must be within the skill repertoire of the implementers, or training to fidelity must occur to introduce the plan components into that repertoire. Values, goals, and stressors refer to motivating operations that determine the reinforcing or punishing value of implementing the plan. Plans that provide little reinforcement and substantial punishment in the process of implementation or outcomes are unlikely to be implemented with fidelity or maintained over time. The effectiveness of behavioral interventions is also influenced by their compatibility with other aspects of their context. Plans that are compatible with ongoing routines are more likely to be implemented than those that conflict (Riley-Tillman and Chafouleas 2003 ). Interventions require various kinds of resources to be implemented and sustained. For example, financial resources may be necessary to purchase curricula, equipment, or other goods. Interventions may require human resources such as direct service staff, training, supervision, administration, and consultation. Fixsen et al. ( 2005 ) have completed an extensive review of contextual variables that can potentially influence the quality of intervention implementation. Behavior analytic practice is unlikely to be effective if it does not consider the context in which interventions will be implemented.

Extensive behavior analytic research has documented the importance of social validity and other contextual factors in producing behavioral changes with practical value. This research tradition is as old as our field (e.g., Jones and Azrin 1969 ) and continues through the present day. For example, Strain et al. ( 2012 ) provided multiple examples of the impact of social validity considerations on relevant outcomes. They reported that integrating client values, preferences, and characteristics in the selection and implementation of an intervention can successfully inform decisions regarding (a) how to design service delivery systems, (b) how to support implementers with complex strategies, (c) when to fade support, (e) how to identify important and unanticipated effects, and (f) how to focus on future research efforts.

Benazzi et al. ( 2006 ) examined the effect of stakeholder participation in intervention planning on the acceptability and usability of behavior intervention plans (BIP) based on descriptive functional behavior assessments (FBA). Plans developed by behavior experts were rated as high in technical adequacy, but low in acceptability. Conversely, plans developed by key stakeholders were highly acceptable, but lacked technical adequacy. However, when the process included both behavior experts and key stakeholders, BIPs were considered both acceptable and technically adequate. Thus, the BIPs developed by behavior analysts may be marginalized and implementation may be less likely to occur in the absence of key stakeholder input. Thus, a practical commitment to effective interventions that are implemented and maintained with integrity over time requires that behavior analysts consider motivational variables such as the alignment of interventions with the values, reinforcers, and punishers of relevant stakeholders.

Clinical Expertise

All of the key components for expert behavior analytic practice (i.e., identification of important behavioral problems, recognition of underlying behavioral processes, weighing of evidence supporting various treatment options, selecting and implementing treatments in complex social contexts, engaging in ongoing data-based decision making, and being responsive to client values and context) require clinical expertise. Clinical expertise refers to the competence attained by practitioners through education, training, and experience that results in effective practice (American Psychological Association Presidential Task Force of Evidence-Based Practice 2006 ). Clinical expertise is the means by which the best available evidence is applied to individual cases in all their complexity. Based on the work of Goodheart ( 2006 ), we suggest that clinical expertise in EBP of ABA includes (a) knowledge of the research literature and its applicability to particular clients, (b) incorporation of the conceptual system of ABA, (c) breadth and depth of clinical and interpersonal skills, (d) integration of client values and context, (e) recognition of the need for outside consultation, (f) data-based decision making, and (g) ongoing professional development. In the sections that follow, we describe each component of clinical expertise in ABA.

Knowledge and Application of the Research Literature

ABA practitioners must be skilled in applying the best available evidence to unique cases in specific contexts. The role of the best available evidence in EBP of ABA was discussed above. Practitioners need to be knowledgeable about the scientific literature and able to appropriately apply the literature to behaviors, clients, and contexts that are rarely a perfect match to the behaviors, clients, and contexts in any particular study. This confluence of knowledge and skillful application requires that the behavior analyst respond to the functionally important features of cases. A great deal of training is necessary to build the expertise required to discriminate critical functional features from those that are incidental. These discriminations must be made with respect to the presenting problem (i.e., the behavioral patterns that have been identified as problematic, their antecedent stimuli, motivating operations, and consequences); client variables such as histories, skills, and preferences; and contextual variables that may impact the effectiveness of various treatment options as applied to the particular case. These skills are reflected in BACB Guidelines 1.01 and 2.10 cited above.

Incorporation of the Conceptual System

The critical features of a case must be identified and mapped onto the conceptual system of ABA. It is not enough to recognize that a particular feature of the environment is important; it must also be understood in terms of its likely behavioral function. This initial conceptualization is necessary in order to generate reasonable hypotheses that may be tested in more thorough analyses. Developing the skill of describing cases in terms of likely behavioral functions typically requires a great deal of formal and informal training as well as ongoing learning from experience. These repertoires are usually acquired through extensive training, supervised practice, and the ongoing feedback of client outcomes. This is recognized in BACB Guidelines; for example, 4.0 states that “the behavior analyst designs programs that are based on behavior analytic principles” (BACB 2010 ).

Breadth and Depth of Clinical and Interpersonal Skills

Evidence-based practitioners of behavior analysis must be able to implement various assessment and intervention procedures with fidelity, and often to train and supervise others to implement such procedures with fidelity. Further, clinical expertise in ABA requires that the practitioner have effective interpersonal skills. For example, he must be able to explain the behavioral philosophy and approach, in nonbehavioral terms, to various audiences who may have different theoretical orientations. BCBA Guidelines 1.05 specifies that behavior analysts “use language that is fully understandable to the recipient of those services” (BACB 2010 ).

Integration of Client Values and Context

In all aspects of their work, practitioners of evidence-based ABA must integrate the values and preferences of the client and other stakeholders as well as the features of the specific context that may impact the effectiveness of an intervention. These factors can be considered additional variables that the behavior analyst must attend to when planning and providing behavior-analytic services. For example, when assessment data suggest behavior serves a particular function, a range of intervention alternatives may be considered (see Geiger, Carr, and LeBlanc for an example of a model for selecting treatments for escape-maintained problem behavior). A caregiver’s statements might suggest that one type of intervention may not be viable due to limited resources while another treatment may be acceptable based on financial considerations, available resources, or other practical factors; the behavior analyst must have the training and expertise to evaluate and incorporate these factors into initial treatment selection and to re-evaluate these concerns as a part of progress monitoring for both treatment integrity and client improvement. BACB Guideline 4.0 states that the behavior analyst “involves the client … in the planning of … programs, [and] obtains the consent of the client” and 4.1 states that “if environmental conditions hamper implementation of the behavior analytic program, the behavior analyst seeks to eliminate the environmental constraints, or identifies in writing the obstacles to doing so” (BACB 2010 ).

Recognition of Need for Outside Consultation

Behavior analysts engaging in responsible evidence-based practice discriminate between behaviors and contexts that are within the scope of their training and those that are not, and respond differently based on this discrimination. For example, a behavior analyst who has been trained to provide assessment and intervention for severe problem behavior may not have the specific training to provide organizational behavior management services to a corporation; in this case, a behavior analyst with clinical expertise would make this discrimination and seek additional consultation or make appropriate referrals. This aspect of expertise is described in BACB ( 2010 ) Guidelines 1.02 and 2.02.

Data-Based Decision Making

Data-based decision making plays a central role in the practice of ABA and is an indispensable feature of clinical expertise. The process of data-based decision making includes identifying useful measurement pinpoints, constructing measurement systems, and graphing results, as well as identifying meaningful patterns in data, interpreting these patterns, and making appropriate responses to them (e.g., maintaining, modifying, replacing, or ending a program). The functional features of the case, the best available research evidence, and the new evidence obtained through progress monitoring must inform these judgments and are central to this model of EBP of ABA. BACB ( 2010 ) Guidelines 4.07 and 4.08 specify that behavior analysts collect data to assess progress and modify programs on the basis of data.

Ongoing Professional Development

Clinical expertise is not static; rather, it requires ongoing professional development. Clinical expertise in ABA requires ongoing contact with the research literature to ensure that practice reflects current knowledge about the most effective and efficient assessment and intervention procedures. The critical literature includes primary empirical research as well as reviews and syntheses such as those described in the section on “ Best Available Evidence ”. In addition, professional consensus on important topics for professional practice evolves over time. For example, in ABA, there has been increased emphasis recently on ethics and supervision competence. All of these dynamics point to the need for ongoing professional development. This is reflected in the requirement that certified behavior analysts “undertake ongoing efforts to maintain competence in the skills they use by reading the appropriate literature, attending conferences and conventions, participating in workshops, and/or obtaining Behavior Analyst Certification Board certification” (Guideline 1.03, BACB 2010 ).

Conclusions

We propose that EBP of ABA be understood as a professional decision-making framework that draws on the best available evidence, client values and context, and clinical expertise. We argue that this conception of EBP of ABA is more compatible with the basic tenets of ABA and more closely aligned with definitions of EBP in other fields than that provided by Smith ( 2013 ). It is noteworthy that this notion of EBP is not necessarily in conflict with many of the observations and arguments put forth by Smith ( 2013 ). His concerns were primarily about how to define and validate EST, which is an important way to inform practitioners about the best available evidence to integrate into their overall EBP.

Given the close alignment between the proposed framework of EBP of ABA and broadly accepted descriptions of behavior analytic practice, one might wonder whether EBP offers anything new. We believe that the EBP of ABA framework, offered here, has several important implications for our field. First, this framework draws together numerous elements of ABA practice into a single coherent system, which can help behavior analysts provide an explicit rationale for their decision-making to clients and other stakeholders. The EBP of ABA provides a decision-making framework that supports a cogent and transparent description of (a) the evidence considered, including direct and frequent measurement of the client’s behavior; (b) why this evidence was identified as the “best available” for the particular case; (c) how client values and contextual factors influenced the process; and (d) the ways in which clinical expertise was used to conceptualize the case and integrate the various considerations. This transparency and explicitness allows the behavior analyst to offer empirically based treatment recommendations while addressing the concerns raised by stakeholders. It also highlights the critical analysis required to be an effective behavior analyst. For example, if an EST is available and appropriate, the behavior analyst can describe the relevance and certainty of the evidence for this intervention. If no relevant EST is available, the behavior analyst can describe how the best available evidence supports the intervention and emphasize the importance of progress monitoring.

Second, the EBP framework prompts the behavior analyst to refer to the important client values that underlie the goals of intervention, the specific methods of intervention, and describe how the intervention is supported by features of the context. This requires the behavior analyst to explicitly recognize that the effectiveness of an intervention is always context dependent. By serving as a prompt, the EBP framework should increase behavior analysts’ adherence to this central tenet of ABA.

Third, by explicitly recognizing the role of clinical expertise, the framework gives the behavior analyst a way to talk about the complex skills required to make appropriate decisions about client needs. In addition, the fact that the proposed definition of EBP of ABA is so closely aligned with definitions in other professions such as medicine and psychology that it provides a common framework and language for communicating about a particular case that can enhance collaboration between behavior analysts and other professionals.

Fourth, this framework for EBP of ABA suggests further development of behavior analysis as well. Examination of the meaning of best available evidence encourages behavior analysts to continue to refine methods for systematically reviewing research literature and identifying ESTs. Further, behavior analysts could better support EBP if we developed methods for validating other units of intervention such as practice elements, kernels, and even the principles of behavior; when these are invoked to support interventions, they must be supported by a clearly specified research base.

Finally, the explicit recognition of the role of clinical expertise in the EBP of ABA has important implications for training behavior analysts. This framework suggests that decision-making is at the heart of EBP of ABA and could be an organizing theme for ABA training programs. Training programs could systematically teach students to articulate the chain of logic that is the basis for their treatment recommendations. The chain of logic would include statements about which research was considered and why, how the client’s values influenced decision-making, and how contextual factors influenced the selection and adaptation (if necessary) of the treatment. This type of training could be embedded in all instructional activities. Formally requiring students to articulate a rationale for the decisions and receiving feedback about their decisions would sharpen their clinical expertise.

In addition to influencing our behavior analytic practice, the EBP of ABA framework impacts our relationship with other members of the broader human service field as well as individuals and agencies that control contingencies relevant to practitioners and scientists. Methodologically rigorous reviews that identify ESTs and other treatments supported by the best available evidence are extremely important for working with organizations that control funding for behavior analytic research and practice. Federal funding for research and service provision is moving strongly towards EBP and ESTs. This trend is clear in education through the No Child Left Behind Act of 2001 , the Individuals with Disabilities Education Act of 2004 , the funding policies of IES, and the What Works Clearinghouse. The recent memorandum by the Director of the Office of Management and Budget (Zients 2012 ) makes it clear that the importance of EBP is not limited to a single discipline or to one political party. In addition, insurance companies are increasingly making reimbursement decisions based, in part, on whether or not credible scientific evidence supports the use of the treatment (Small 2004 ). The insurance companies have consistently adopted criteria for scientific evidence that are closely related to EST (Bogduk and Fraifeld 2010 ). As a result, reimbursement for ABA services may depend on the scientific credibility of EST reviews, a critical component of EBP. Methodologically rigorous reviews that identify ESTs within a broader framework of EBP appear to be critical for ABA to maintain and expand its access to federal funding and insurance reimbursement for services. Establishment of this literature base will require behavior analysts to develop appropriate methods for reviewing and summarizing research based on single-subject designs. IES has established such standards for reviewing studies, but to date, there are no accepted methods for calculating a measure of effect size as an objective basis for combining result across studies (Kratochwill et al. 2013 ). If behavior analysts develop such a measure, it would reflect a significant methodological advance as a field and it would increase the credibility of behavior analytic research with agencies that fund research and services.

EBP of ABA emphasizes the research-supported selection of treatments and data-driven decisions about treatment progress that have always been at the core of ABA. ABA’s long-standing recognition of the importance of social validity is reflected in the definition of EBP. This framework for EBP of ABA offers many positive professional consequences for scientists and practitioners while promoting the best of the behavior analytic tradition and making contact with developments in other disciplines and the larger context in which behavior analysts work.

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7 Module 7: Thinking, Reasoning, and Problem-Solving

This module is about how a solid working knowledge of psychological principles can help you to think more effectively, so you can succeed in school and life. You might be inclined to believe that—because you have been thinking for as long as you can remember, because you are able to figure out the solution to many problems, because you feel capable of using logic to argue a point, because you can evaluate whether the things you read and hear make sense—you do not need any special training in thinking. But this, of course, is one of the key barriers to helping people think better. If you do not believe that there is anything wrong, why try to fix it?

The human brain is indeed a remarkable thinking machine, capable of amazing, complex, creative, logical thoughts. Why, then, are we telling you that you need to learn how to think? Mainly because one major lesson from cognitive psychology is that these capabilities of the human brain are relatively infrequently realized. Many psychologists believe that people are essentially “cognitive misers.” It is not that we are lazy, but that we have a tendency to expend the least amount of mental effort necessary. Although you may not realize it, it actually takes a great deal of energy to think. Careful, deliberative reasoning and critical thinking are very difficult. Because we seem to be successful without going to the trouble of using these skills well, it feels unnecessary to develop them. As you shall see, however, there are many pitfalls in the cognitive processes described in this module. When people do not devote extra effort to learning and improving reasoning, problem solving, and critical thinking skills, they make many errors.

As is true for memory, if you develop the cognitive skills presented in this module, you will be more successful in school. It is important that you realize, however, that these skills will help you far beyond school, even more so than a good memory will. Although it is somewhat useful to have a good memory, ten years from now no potential employer will care how many questions you got right on multiple choice exams during college. All of them will, however, recognize whether you are a logical, analytical, critical thinker. With these thinking skills, you will be an effective, persuasive communicator and an excellent problem solver.

The module begins by describing different kinds of thought and knowledge, especially conceptual knowledge and critical thinking. An understanding of these differences will be valuable as you progress through school and encounter different assignments that require you to tap into different kinds of knowledge. The second section covers deductive and inductive reasoning, which are processes we use to construct and evaluate strong arguments. They are essential skills to have whenever you are trying to persuade someone (including yourself) of some point, or to respond to someone’s efforts to persuade you. The module ends with a section about problem solving. A solid understanding of the key processes involved in problem solving will help you to handle many daily challenges.

7.1. Different kinds of thought

7.2. Reasoning and Judgment

7.3. Problem Solving

READING WITH PURPOSE

Remember and understand.

By reading and studying Module 7, you should be able to remember and describe:

• Concepts and inferences (7.1)
• Procedural knowledge (7.1)
• Metacognition (7.1)
• Characteristics of critical thinking:  skepticism; identify biases, distortions, omissions, and assumptions; reasoning and problem solving skills  (7.1)
• Reasoning:  deductive reasoning, deductively valid argument, inductive reasoning, inductively strong argument, availability heuristic, representativeness heuristic  (7.2)
• Fixation:  functional fixedness, mental set  (7.3)
• Algorithms, heuristics, and the role of confirmation bias (7.3)
• Effective problem solving sequence (7.3)

By reading and thinking about how the concepts in Module 6 apply to real life, you should be able to:

• Identify which type of knowledge a piece of information is (7.1)
• Recognize examples of deductive and inductive reasoning (7.2)
• Recognize judgments that have probably been influenced by the availability heuristic (7.2)
• Recognize examples of problem solving heuristics and algorithms (7.3)

Analyze, Evaluate, and Create

By reading and thinking about Module 6, participating in classroom activities, and completing out-of-class assignments, you should be able to:

• Use the principles of critical thinking to evaluate information (7.1)
• Explain whether examples of reasoning arguments are deductively valid or inductively strong (7.2)
• Outline how you could try to solve a problem from your life using the effective problem solving sequence (7.3)

7.1. Different kinds of thought and knowledge

• Take a few minutes to write down everything that you know about dogs.
• Do you believe that:
• Psychic ability exists?
• Hypnosis is an altered state of consciousness?
• Magnet therapy is effective for relieving pain?
• Aerobic exercise is an effective treatment for depression?
• UFO’s from outer space have visited earth?

On what do you base your belief or disbelief for the questions above?

Of course, we all know what is meant by the words  think  and  knowledge . You probably also realize that they are not unitary concepts; there are different kinds of thought and knowledge. In this section, let us look at some of these differences. If you are familiar with these different kinds of thought and pay attention to them in your classes, it will help you to focus on the right goals, learn more effectively, and succeed in school. Different assignments and requirements in school call on you to use different kinds of knowledge or thought, so it will be very helpful for you to learn to recognize them (Anderson, et al. 2001).

Factual and conceptual knowledge

Module 5 introduced the idea of declarative memory, which is composed of facts and episodes. If you have ever played a trivia game or watched Jeopardy on TV, you realize that the human brain is able to hold an extraordinary number of facts. Likewise, you realize that each of us has an enormous store of episodes, essentially facts about events that happened in our own lives. It may be difficult to keep that in mind when we are struggling to retrieve one of those facts while taking an exam, however. Part of the problem is that, in contradiction to the advice from Module 5, many students continue to try to memorize course material as a series of unrelated facts (picture a history student simply trying to memorize history as a set of unrelated dates without any coherent story tying them together). Facts in the real world are not random and unorganized, however. It is the way that they are organized that constitutes a second key kind of knowledge, conceptual.

Concepts are nothing more than our mental representations of categories of things in the world. For example, think about dogs. When you do this, you might remember specific facts about dogs, such as they have fur and they bark. You may also recall dogs that you have encountered and picture them in your mind. All of this information (and more) makes up your concept of dog. You can have concepts of simple categories (e.g., triangle), complex categories (e.g., small dogs that sleep all day, eat out of the garbage, and bark at leaves), kinds of people (e.g., psychology professors), events (e.g., birthday parties), and abstract ideas (e.g., justice). Gregory Murphy (2002) refers to concepts as the “glue that holds our mental life together” (p. 1). Very simply, summarizing the world by using concepts is one of the most important cognitive tasks that we do. Our conceptual knowledge  is  our knowledge about the world. Individual concepts are related to each other to form a rich interconnected network of knowledge. For example, think about how the following concepts might be related to each other: dog, pet, play, Frisbee, chew toy, shoe. Or, of more obvious use to you now, how these concepts are related: working memory, long-term memory, declarative memory, procedural memory, and rehearsal? Because our minds have a natural tendency to organize information conceptually, when students try to remember course material as isolated facts, they are working against their strengths.

One last important point about concepts is that they allow you to instantly know a great deal of information about something. For example, if someone hands you a small red object and says, “here is an apple,” they do not have to tell you, “it is something you can eat.” You already know that you can eat it because it is true by virtue of the fact that the object is an apple; this is called drawing an  inference , assuming that something is true on the basis of your previous knowledge (for example, of category membership or of how the world works) or logical reasoning.

Procedural knowledge

Physical skills, such as tying your shoes, doing a cartwheel, and driving a car (or doing all three at the same time, but don’t try this at home) are certainly a kind of knowledge. They are procedural knowledge, the same idea as procedural memory that you saw in Module 5. Mental skills, such as reading, debating, and planning a psychology experiment, are procedural knowledge, as well. In short, procedural knowledge is the knowledge how to do something (Cohen & Eichenbaum, 1993).

Metacognitive knowledge

Floyd used to think that he had a great memory. Now, he has a better memory. Why? Because he finally realized that his memory was not as great as he once thought it was. Because Floyd eventually learned that he often forgets where he put things, he finally developed the habit of putting things in the same place. (Unfortunately, he did not learn this lesson before losing at least 5 watches and a wedding ring.) Because he finally realized that he often forgets to do things, he finally started using the To Do list app on his phone. And so on. Floyd’s insights about the real limitations of his memory have allowed him to remember things that he used to forget.

All of us have knowledge about the way our own minds work. You may know that you have a good memory for people’s names and a poor memory for math formulas. Someone else might realize that they have difficulty remembering to do things, like stopping at the store on the way home. Others still know that they tend to overlook details. This knowledge about our own thinking is actually quite important; it is called metacognitive knowledge, or  metacognition . Like other kinds of thinking skills, it is subject to error. For example, in unpublished research, one of the authors surveyed about 120 General Psychology students on the first day of the term. Among other questions, the students were asked them to predict their grade in the class and report their current Grade Point Average. Two-thirds of the students predicted that their grade in the course would be higher than their GPA. (The reality is that at our college, students tend to earn lower grades in psychology than their overall GPA.) Another example: Students routinely report that they thought they had done well on an exam, only to discover, to their dismay, that they were wrong (more on that important problem in a moment). Both errors reveal a breakdown in metacognition.

The Dunning-Kruger Effect

In general, most college students probably do not study enough. For example, using data from the National Survey of Student Engagement, Fosnacht, McCormack, and Lerma (2018) reported that first-year students at 4-year colleges in the U.S. averaged less than 14 hours per week preparing for classes. The typical suggestion is that you should spend two hours outside of class for every hour in class, or 24 – 30 hours per week for a full-time student. Clearly, students in general are nowhere near that recommended mark. Many observers, including some faculty, believe that this shortfall is a result of students being too busy or lazy. Now, it may be true that many students are too busy, with work and family obligations, for example. Others, are not particularly motivated in school, and therefore might correctly be labeled lazy. A third possible explanation, however, is that some students might not think they need to spend this much time. And this is a matter of metacognition. Consider the scenario that we mentioned above, students thinking they had done well on an exam only to discover that they did not. Justin Kruger and David Dunning examined scenarios very much like this in 1999. Kruger and Dunning gave research participants tests measuring humor, logic, and grammar. Then, they asked the participants to assess their own abilities and test performance in these areas. They found that participants in general tended to overestimate their abilities, already a problem with metacognition. Importantly, the participants who scored the lowest overestimated their abilities the most. Specifically, students who scored in the bottom quarter (averaging in the 12th percentile) thought they had scored in the 62nd percentile. This has become known as the  Dunning-Kruger effect . Many individual faculty members have replicated these results with their own student on their course exams, including the authors of this book. Think about it. Some students who just took an exam and performed poorly believe that they did well before seeing their score. It seems very likely that these are the very same students who stopped studying the night before because they thought they were “done.” Quite simply, it is not just that they did not know the material. They did not know that they did not know the material. That is poor metacognition.

In order to develop good metacognitive skills, you should continually monitor your thinking and seek frequent feedback on the accuracy of your thinking (Medina, Castleberry, & Persky 2017). For example, in classes get in the habit of predicting your exam grades. As soon as possible after taking an exam, try to find out which questions you missed and try to figure out why. If you do this soon enough, you may be able to recall the way it felt when you originally answered the question. Did you feel confident that you had answered the question correctly? Then you have just discovered an opportunity to improve your metacognition. Be on the lookout for that feeling and respond with caution.

concept :  a mental representation of a category of things in the world

Dunning-Kruger effect : individuals who are less competent tend to overestimate their abilities more than individuals who are more competent do

inference : an assumption about the truth of something that is not stated. Inferences come from our prior knowledge and experience, and from logical reasoning

metacognition :  knowledge about one’s own cognitive processes; thinking about your thinking

Critical thinking

One particular kind of knowledge or thinking skill that is related to metacognition is  critical thinking (Chew, 2020). You may have noticed that critical thinking is an objective in many college courses, and thus it could be a legitimate topic to cover in nearly any college course. It is particularly appropriate in psychology, however. As the science of (behavior and) mental processes, psychology is obviously well suited to be the discipline through which you should be introduced to this important way of thinking.

More importantly, there is a particular need to use critical thinking in psychology. We are all, in a way, experts in human behavior and mental processes, having engaged in them literally since birth. Thus, perhaps more than in any other class, students typically approach psychology with very clear ideas and opinions about its subject matter. That is, students already “know” a lot about psychology. The problem is, “it ain’t so much the things we don’t know that get us into trouble. It’s the things we know that just ain’t so” (Ward, quoted in Gilovich 1991). Indeed, many of students’ preconceptions about psychology are just plain wrong. Randolph Smith (2002) wrote a book about critical thinking in psychology called  Challenging Your Preconceptions,  highlighting this fact. On the other hand, many of students’ preconceptions about psychology are just plain right! But wait, how do you know which of your preconceptions are right and which are wrong? And when you come across a research finding or theory in this class that contradicts your preconceptions, what will you do? Will you stick to your original idea, discounting the information from the class? Will you immediately change your mind? Critical thinking can help us sort through this confusing mess.

But what is critical thinking? The goal of critical thinking is simple to state (but extraordinarily difficult to achieve): it is to be right, to draw the correct conclusions, to believe in things that are true and to disbelieve things that are false. We will provide two definitions of critical thinking (or, if you like, one large definition with two distinct parts). First, a more conceptual one: Critical thinking is thinking like a scientist in your everyday life (Schmaltz, Jansen, & Wenckowski, 2017).  Our second definition is more operational; it is simply a list of skills that are essential to be a critical thinker. Critical thinking entails solid reasoning and problem solving skills; skepticism; and an ability to identify biases, distortions, omissions, and assumptions. Excellent deductive and inductive reasoning, and problem solving skills contribute to critical thinking. So, you can consider the subject matter of sections 7.2 and 7.3 to be part of critical thinking. Because we will be devoting considerable time to these concepts in the rest of the module, let us begin with a discussion about the other aspects of critical thinking.

Let’s address that first part of the definition. Scientists form hypotheses, or predictions about some possible future observations. Then, they collect data, or information (think of this as making those future observations). They do their best to make unbiased observations using reliable techniques that have been verified by others. Then, and only then, they draw a conclusion about what those observations mean. Oh, and do not forget the most important part. “Conclusion” is probably not the most appropriate word because this conclusion is only tentative. A scientist is always prepared that someone else might come along and produce new observations that would require a new conclusion be drawn. Wow! If you like to be right, you could do a lot worse than using a process like this.

A Critical Thinker’s Toolkit 

Now for the second part of the definition. Good critical thinkers (and scientists) rely on a variety of tools to evaluate information. Perhaps the most recognizable tool for critical thinking is  skepticism (and this term provides the clearest link to the thinking like a scientist definition, as you are about to see). Some people intend it as an insult when they call someone a skeptic. But if someone calls you a skeptic, if they are using the term correctly, you should consider it a great compliment. Simply put, skepticism is a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided. People from Missouri should recognize this principle, as Missouri is known as the Show-Me State. As a skeptic, you are not inclined to believe something just because someone said so, because someone else believes it, or because it sounds reasonable. You must be persuaded by high quality evidence.

Of course, if that evidence is produced, you have a responsibility as a skeptic to change your belief. Failure to change a belief in the face of good evidence is not skepticism; skepticism has open mindedness at its core. M. Neil Browne and Stuart Keeley (2018) use the term weak sense critical thinking to describe critical thinking behaviors that are used only to strengthen a prior belief. Strong sense critical thinking, on the other hand, has as its goal reaching the best conclusion. Sometimes that means strengthening your prior belief, but sometimes it means changing your belief to accommodate the better evidence.

Many times, a failure to think critically or weak sense critical thinking is related to a  bias , an inclination, tendency, leaning, or prejudice. Everybody has biases, but many people are unaware of them. Awareness of your own biases gives you the opportunity to control or counteract them. Unfortunately, however, many people are happy to let their biases creep into their attempts to persuade others; indeed, it is a key part of their persuasive strategy. To see how these biases influence messages, just look at the different descriptions and explanations of the same events given by people of different ages or income brackets, or conservative versus liberal commentators, or by commentators from different parts of the world. Of course, to be successful, these people who are consciously using their biases must disguise them. Even undisguised biases can be difficult to identify, so disguised ones can be nearly impossible.

Here are some common sources of biases:

• Personal values and beliefs.  Some people believe that human beings are basically driven to seek power and that they are typically in competition with one another over scarce resources. These beliefs are similar to the world-view that political scientists call “realism.” Other people believe that human beings prefer to cooperate and that, given the chance, they will do so. These beliefs are similar to the world-view known as “idealism.” For many people, these deeply held beliefs can influence, or bias, their interpretations of such wide ranging situations as the behavior of nations and their leaders or the behavior of the driver in the car ahead of you. For example, if your worldview is that people are typically in competition and someone cuts you off on the highway, you may assume that the driver did it purposely to get ahead of you. Other types of beliefs about the way the world is or the way the world should be, for example, political beliefs, can similarly become a significant source of bias.
• Racism, sexism, ageism and other forms of prejudice and bigotry.  These are, sadly, a common source of bias in many people. They are essentially a special kind of “belief about the way the world is.” These beliefs—for example, that women do not make effective leaders—lead people to ignore contradictory evidence (examples of effective women leaders, or research that disputes the belief) and to interpret ambiguous evidence in a way consistent with the belief.
• Self-interest.  When particular people benefit from things turning out a certain way, they can sometimes be very susceptible to letting that interest bias them. For example, a company that will earn a profit if they sell their product may have a bias in the way that they give information about their product. A union that will benefit if its members get a generous contract might have a bias in the way it presents information about salaries at competing organizations. (Note that our inclusion of examples describing both companies and unions is an explicit attempt to control for our own personal biases). Home buyers are often dismayed to discover that they purchased their dream house from someone whose self-interest led them to lie about flooding problems in the basement or back yard. This principle, the biasing power of self-interest, is likely what led to the famous phrase  Caveat Emptor  (let the buyer beware) .  

Knowing that these types of biases exist will help you evaluate evidence more critically. Do not forget, though, that people are not always keen to let you discover the sources of biases in their arguments. For example, companies or political organizations can sometimes disguise their support of a research study by contracting with a university professor, who comes complete with a seemingly unbiased institutional affiliation, to conduct the study.

People’s biases, conscious or unconscious, can lead them to make omissions, distortions, and assumptions that undermine our ability to correctly evaluate evidence. It is essential that you look for these elements. Always ask, what is missing, what is not as it appears, and what is being assumed here? For example, consider this (fictional) chart from an ad reporting customer satisfaction at 4 local health clubs.

Clearly, from the results of the chart, one would be tempted to give Club C a try, as customer satisfaction is much higher than for the other 3 clubs.

There are so many distortions and omissions in this chart, however, that it is actually quite meaningless. First, how was satisfaction measured? Do the bars represent responses to a survey? If so, how were the questions asked? Most importantly, where is the missing scale for the chart? Although the differences look quite large, are they really?

Well, here is the same chart, with a different scale, this time labeled:

Club C is not so impressive any more, is it? In fact, all of the health clubs have customer satisfaction ratings (whatever that means) between 85% and 88%. In the first chart, the entire scale of the graph included only the percentages between 83 and 89. This “judicious” choice of scale—some would call it a distortion—and omission of that scale from the chart make the tiny differences among the clubs seem important, however.

Also, in order to be a critical thinker, you need to learn to pay attention to the assumptions that underlie a message. Let us briefly illustrate the role of assumptions by touching on some people’s beliefs about the criminal justice system in the US. Some believe that a major problem with our judicial system is that many criminals go free because of legal technicalities. Others believe that a major problem is that many innocent people are convicted of crimes. The simple fact is, both types of errors occur. A person’s conclusion about which flaw in our judicial system is the greater tragedy is based on an assumption about which of these is the more serious error (letting the guilty go free or convicting the innocent). This type of assumption is called a value assumption (Browne and Keeley, 2018). It reflects the differences in values that people develop, differences that may lead us to disregard valid evidence that does not fit in with our particular values.

Oh, by the way, some students probably noticed this, but the seven tips for evaluating information that we shared in Module 1 are related to this. Actually, they are part of this section. The tips are, to a very large degree, set of ideas you can use to help you identify biases, distortions, omissions, and assumptions. If you do not remember this section, we strongly recommend you take a few minutes to review it.

skepticism :  a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided

bias : an inclination, tendency, leaning, or prejudice

• Which of your beliefs (or disbeliefs) from the Activate exercise for this section were derived from a process of critical thinking? If some of your beliefs were not based on critical thinking, are you willing to reassess these beliefs? If the answer is no, why do you think that is? If the answer is yes, what concrete steps will you take?

7.2 Reasoning and Judgment

• What percentage of kidnappings are committed by strangers?
• Which area of the house is riskiest: kitchen, bathroom, or stairs?
• What is the most common cancer in the US?
• What percentage of workplace homicides are committed by co-workers?

An essential set of procedural thinking skills is  reasoning , the ability to generate and evaluate solid conclusions from a set of statements or evidence. You should note that these conclusions (when they are generated instead of being evaluated) are one key type of inference that we described in Section 7.1. There are two main types of reasoning, deductive and inductive.

Deductive reasoning

Suppose your teacher tells you that if you get an A on the final exam in a course, you will get an A for the whole course. Then, you get an A on the final exam. What will your final course grade be? Most people can see instantly that you can conclude with certainty that you will get an A for the course. This is a type of reasoning called  deductive reasoning , which is defined as reasoning in which a conclusion is guaranteed to be true as long as the statements leading to it are true. The three statements can be listed as an  argument , with two beginning statements and a conclusion:

Statement 1: If you get an A on the final exam, you will get an A for the course

Statement 2: You get an A on the final exam

Conclusion: You will get an A for the course

This particular arrangement, in which true beginning statements lead to a guaranteed true conclusion, is known as a  deductively valid argument . Although deductive reasoning is often the subject of abstract, brain-teasing, puzzle-like word problems, it is actually an extremely important type of everyday reasoning. It is just hard to recognize sometimes. For example, imagine that you are looking for your car keys and you realize that they are either in the kitchen drawer or in your book bag. After looking in the kitchen drawer, you instantly know that they must be in your book bag. That conclusion results from a simple deductive reasoning argument. In addition, solid deductive reasoning skills are necessary for you to succeed in the sciences, philosophy, math, computer programming, and any endeavor involving the use of logic to persuade others to your point of view or to evaluate others’ arguments.

Cognitive psychologists, and before them philosophers, have been quite interested in deductive reasoning, not so much for its practical applications, but for the insights it can offer them about the ways that human beings think. One of the early ideas to emerge from the examination of deductive reasoning is that people learn (or develop) mental versions of rules that allow them to solve these types of reasoning problems (Braine, 1978; Braine, Reiser, & Rumain, 1984). The best way to see this point of view is to realize that there are different possible rules, and some of them are very simple. For example, consider this rule of logic:

therefore q

Logical rules are often presented abstractly, as letters, in order to imply that they can be used in very many specific situations. Here is a concrete version of the of the same rule:

I’ll either have pizza or a hamburger for dinner tonight (p or q)

I won’t have pizza (not p)

Therefore, I’ll have a hamburger (therefore q)

This kind of reasoning seems so natural, so easy, that it is quite plausible that we would use a version of this rule in our daily lives. At least, it seems more plausible than some of the alternative possibilities—for example, that we need to have experience with the specific situation (pizza or hamburger, in this case) in order to solve this type of problem easily. So perhaps there is a form of natural logic (Rips, 1990) that contains very simple versions of logical rules. When we are faced with a reasoning problem that maps onto one of these rules, we use the rule.

But be very careful; things are not always as easy as they seem. Even these simple rules are not so simple. For example, consider the following rule. Many people fail to realize that this rule is just as valid as the pizza or hamburger rule above.

if p, then q

therefore, not p

Concrete version:

If I eat dinner, then I will have dessert

I did not have dessert

Therefore, I did not eat dinner

The simple fact is, it can be very difficult for people to apply rules of deductive logic correctly; as a result, they make many errors when trying to do so. Is this a deductively valid argument or not?

Students who like school study a lot

Students who study a lot get good grades

Jane does not like school

Therefore, Jane does not get good grades

Many people are surprised to discover that this is not a logically valid argument; the conclusion is not guaranteed to be true from the beginning statements. Although the first statement says that students who like school study a lot, it does NOT say that students who do not like school do not study a lot. In other words, it may very well be possible to study a lot without liking school. Even people who sometimes get problems like this right might not be using the rules of deductive reasoning. Instead, they might just be making judgments for examples they know, in this case, remembering instances of people who get good grades despite not liking school.

Making deductive reasoning even more difficult is the fact that there are two important properties that an argument may have. One, it can be valid or invalid (meaning that the conclusion does or does not follow logically from the statements leading up to it). Two, an argument (or more correctly, its conclusion) can be true or false. Here is an example of an argument that is logically valid, but has a false conclusion (at least we think it is false).

Either you are eleven feet tall or the Grand Canyon was created by a spaceship crashing into the earth.

You are not eleven feet tall

Therefore the Grand Canyon was created by a spaceship crashing into the earth

This argument has the exact same form as the pizza or hamburger argument above, making it is deductively valid. The conclusion is so false, however, that it is absurd (of course, the reason the conclusion is false is that the first statement is false). When people are judging arguments, they tend to not observe the difference between deductive validity and the empirical truth of statements or conclusions. If the elements of an argument happen to be true, people are likely to judge the argument logically valid; if the elements are false, they will very likely judge it invalid (Markovits & Bouffard-Bouchard, 1992; Moshman & Franks, 1986). Thus, it seems a stretch to say that people are using these logical rules to judge the validity of arguments. Many psychologists believe that most people actually have very limited deductive reasoning skills (Johnson-Laird, 1999). They argue that when faced with a problem for which deductive logic is required, people resort to some simpler technique, such as matching terms that appear in the statements and the conclusion (Evans, 1982). This might not seem like a problem, but what if reasoners believe that the elements are true and they happen to be wrong; they will would believe that they are using a form of reasoning that guarantees they are correct and yet be wrong.

deductive reasoning :  a type of reasoning in which the conclusion is guaranteed to be true any time the statements leading up to it are true

argument :  a set of statements in which the beginning statements lead to a conclusion

deductively valid argument :  an argument for which true beginning statements guarantee that the conclusion is true

Inductive reasoning and judgment

Every day, you make many judgments about the likelihood of one thing or another. Whether you realize it or not, you are practicing  inductive reasoning   on a daily basis. In inductive reasoning arguments, a conclusion is likely whenever the statements preceding it are true. The first thing to notice about inductive reasoning is that, by definition, you can never be sure about your conclusion; you can only estimate how likely the conclusion is. Inductive reasoning may lead you to focus on Memory Encoding and Recoding when you study for the exam, but it is possible the instructor will ask more questions about Memory Retrieval instead. Unlike deductive reasoning, the conclusions you reach through inductive reasoning are only probable, not certain. That is why scientists consider inductive reasoning weaker than deductive reasoning. But imagine how hard it would be for us to function if we could not act unless we were certain about the outcome.

Inductive reasoning can be represented as logical arguments consisting of statements and a conclusion, just as deductive reasoning can be. In an inductive argument, you are given some statements and a conclusion (or you are given some statements and must draw a conclusion). An argument is  inductively strong   if the conclusion would be very probable whenever the statements are true. So, for example, here is an inductively strong argument:

• Statement #1: The forecaster on Channel 2 said it is going to rain today.
• Statement #2: The forecaster on Channel 5 said it is going to rain today.
• Statement #3: It is very cloudy and humid.
• Statement #4: You just heard thunder.
• Conclusion (or judgment): It is going to rain today.

Think of the statements as evidence, on the basis of which you will draw a conclusion. So, based on the evidence presented in the four statements, it is very likely that it will rain today. Will it definitely rain today? Certainly not. We can all think of times that the weather forecaster was wrong.

A true story: Some years ago psychology student was watching a baseball playoff game between the St. Louis Cardinals and the Los Angeles Dodgers. A graphic on the screen had just informed the audience that the Cardinal at bat, (Hall of Fame shortstop) Ozzie Smith, a switch hitter batting left-handed for this plate appearance, had never, in nearly 3000 career at-bats, hit a home run left-handed. The student, who had just learned about inductive reasoning in his psychology class, turned to his companion (a Cardinals fan) and smugly said, “It is an inductively strong argument that Ozzie Smith will not hit a home run.” He turned back to face the television just in time to watch the ball sail over the right field fence for a home run. Although the student felt foolish at the time, he was not wrong. It was an inductively strong argument; 3000 at-bats is an awful lot of evidence suggesting that the Wizard of Ozz (as he was known) would not be hitting one out of the park (think of each at-bat without a home run as a statement in an inductive argument). Sadly (for the die-hard Cubs fan and Cardinals-hating student), despite the strength of the argument, the conclusion was wrong.

Given the possibility that we might draw an incorrect conclusion even with an inductively strong argument, we really want to be sure that we do, in fact, make inductively strong arguments. If we judge something probable, it had better be probable. If we judge something nearly impossible, it had better not happen. Think of inductive reasoning, then, as making reasonably accurate judgments of the probability of some conclusion given a set of evidence.

We base many decisions in our lives on inductive reasoning. For example:

Statement #1: Psychology is not my best subject

Statement #2: My psychology instructor has a reputation for giving difficult exams

Statement #3: My first psychology exam was much harder than I expected

Judgment: The next exam will probably be very difficult.

Decision: I will study tonight instead of watching Netflix.

Some other examples of judgments that people commonly make in a school context include judgments of the likelihood that:

• A particular class will be interesting/useful/difficult
• You will be able to finish writing a paper by next week if you go out tonight
• Your laptop’s battery will last through the next trip to the library
• You will not miss anything important if you skip class tomorrow
• Your instructor will not notice if you skip class tomorrow
• You will be able to find a book that you will need for a paper
• There will be an essay question about Memory Encoding on the next exam

Tversky and Kahneman (1983) recognized that there are two general ways that we might make these judgments; they termed them extensional (i.e., following the laws of probability) and intuitive (i.e., using shortcuts or heuristics, see below). We will use a similar distinction between Type 1 and Type 2 thinking, as described by Keith Stanovich and his colleagues (Evans and Stanovich, 2013; Stanovich and West, 2000). Type 1 thinking is fast, automatic, effortful, and emotional. In fact, it is hardly fair to call it reasoning at all, as judgments just seem to pop into one’s head. Type 2 thinking , on the other hand, is slow, effortful, and logical. So obviously, it is more likely to lead to a correct judgment, or an optimal decision. The problem is, we tend to over-rely on Type 1. Now, we are not saying that Type 2 is the right way to go for every decision or judgment we make. It seems a bit much, for example, to engage in a step-by-step logical reasoning procedure to decide whether we will have chicken or fish for dinner tonight.

Many bad decisions in some very important contexts, however, can be traced back to poor judgments of the likelihood of certain risks or outcomes that result from the use of Type 1 when a more logical reasoning process would have been more appropriate. For example:

Statement #1: It is late at night.

Statement #2: Albert has been drinking beer for the past five hours at a party.

Statement #3: Albert is not exactly sure where he is or how far away home is.

Judgment: Albert will have no difficulty walking home.

Decision: He walks home alone.

As you can see in this example, the three statements backing up the judgment do not really support it. In other words, this argument is not inductively strong because it is based on judgments that ignore the laws of probability. What are the chances that someone facing these conditions will be able to walk home alone easily? And one need not be drunk to make poor decisions based on judgments that just pop into our heads.

The truth is that many of our probability judgments do not come very close to what the laws of probability say they should be. Think about it. In order for us to reason in accordance with these laws, we would need to know the laws of probability, which would allow us to calculate the relationship between particular pieces of evidence and the probability of some outcome (i.e., how much likelihood should change given a piece of evidence), and we would have to do these heavy math calculations in our heads. After all, that is what Type 2 requires. Needless to say, even if we were motivated, we often do not even know how to apply Type 2 reasoning in many cases.

So what do we do when we don’t have the knowledge, skills, or time required to make the correct mathematical judgment? Do we hold off and wait until we can get better evidence? Do we read up on probability and fire up our calculator app so we can compute the correct probability? Of course not. We rely on Type 1 thinking. We “wing it.” That is, we come up with a likelihood estimate using some means at our disposal. Psychologists use the term heuristic to describe the type of “winging it” we are talking about. A  heuristic   is a shortcut strategy that we use to make some judgment or solve some problem (see Section 7.3). Heuristics are easy and quick, think of them as the basic procedures that are characteristic of Type 1.  They can absolutely lead to reasonably good judgments and decisions in some situations (like choosing between chicken and fish for dinner). They are, however, far from foolproof. There are, in fact, quite a lot of situations in which heuristics can lead us to make incorrect judgments, and in many cases the decisions based on those judgments can have serious consequences.

Let us return to the activity that begins this section. You were asked to judge the likelihood (or frequency) of certain events and risks. You were free to come up with your own evidence (or statements) to make these judgments. This is where a heuristic crops up. As a judgment shortcut, we tend to generate specific examples of those very events to help us decide their likelihood or frequency. For example, if we are asked to judge how common, frequent, or likely a particular type of cancer is, many of our statements would be examples of specific cancer cases:

Statement #1: Andy Kaufman (comedian) had lung cancer.

Statement #2: Colin Powell (US Secretary of State) had prostate cancer.

Statement #3: Bob Marley (musician) had skin and brain cancer

Statement #4: Sandra Day O’Connor (Supreme Court Justice) had breast cancer.

Statement #5: Fred Rogers (children’s entertainer) had stomach cancer.

Statement #6: Robin Roberts (news anchor) had breast cancer.

Statement #7: Bette Davis (actress) had breast cancer.

Judgment: Breast cancer is the most common type.

Your own experience or memory may also tell you that breast cancer is the most common type. But it is not (although it is common). Actually, skin cancer is the most common type in the US. We make the same types of misjudgments all the time because we do not generate the examples or evidence according to their actual frequencies or probabilities. Instead, we have a tendency (or bias) to search for the examples in memory; if they are easy to retrieve, we assume that they are common. To rephrase this in the language of the heuristic, events seem more likely to the extent that they are available to memory. This bias has been termed the  availability heuristic   (Kahneman and Tversky, 1974).

The fact that we use the availability heuristic does not automatically mean that our judgment is wrong. The reason we use heuristics in the first place is that they work fairly well in many cases (and, of course that they are easy to use). So, the easiest examples to think of sometimes are the most common ones. Is it more likely that a member of the U.S. Senate is a man or a woman? Most people have a much easier time generating examples of male senators. And as it turns out, the U.S. Senate has many more men than women (74 to 26 in 2020). In this case, then, the availability heuristic would lead you to make the correct judgment; it is far more likely that a senator would be a man.

In many other cases, however, the availability heuristic will lead us astray. This is because events can be memorable for many reasons other than their frequency. Section 5.2, Encoding Meaning, suggested that one good way to encode the meaning of some information is to form a mental image of it. Thus, information that has been pictured mentally will be more available to memory. Indeed, an event that is vivid and easily pictured will trick many people into supposing that type of event is more common than it actually is. Repetition of information will also make it more memorable. So, if the same event is described to you in a magazine, on the evening news, on a podcast that you listen to, and in your Facebook feed; it will be very available to memory. Again, the availability heuristic will cause you to misperceive the frequency of these types of events.

Most interestingly, information that is unusual is more memorable. Suppose we give you the following list of words to remember: box, flower, letter, platypus, oven, boat, newspaper, purse, drum, car. Very likely, the easiest word to remember would be platypus, the unusual one. The same thing occurs with memories of events. An event may be available to memory because it is unusual, yet the availability heuristic leads us to judge that the event is common. Did you catch that? In these cases, the availability heuristic makes us think the exact opposite of the true frequency. We end up thinking something is common because it is unusual (and therefore memorable). Yikes.

The misapplication of the availability heuristic sometimes has unfortunate results. For example, if you went to K-12 school in the US over the past 10 years, it is extremely likely that you have participated in lockdown and active shooter drills. Of course, everyone is trying to prevent the tragedy of another school shooting. And believe us, we are not trying to minimize how terrible the tragedy is. But the truth of the matter is, school shootings are extremely rare. Because the federal government does not keep a database of school shootings, the Washington Post has maintained their own running tally. Between 1999 and January 2020 (the date of the most recent school shooting with a death in the US at of the time this paragraph was written), the Post reported a total of 254 people died in school shootings in the US. Not 254 per year, 254 total. That is an average of 12 per year. Of course, that is 254 people who should not have died (particularly because many were children), but in a country with approximately 60,000,000 students and teachers, this is a very small risk.

But many students and teachers are terrified that they will be victims of school shootings because of the availability heuristic. It is so easy to think of examples (they are very available to memory) that people believe the event is very common. It is not. And there is a downside to this. We happen to believe that there is an enormous gun violence problem in the United States. According the the Centers for Disease Control and Prevention, there were 39,773 firearm deaths in the US in 2017. Fifteen of those deaths were in school shootings, according to the Post. 60% of those deaths were suicides. When people pay attention to the school shooting risk (low), they often fail to notice the much larger risk.

And examples like this are by no means unique. The authors of this book have been teaching psychology since the 1990’s. We have been able to make the exact same arguments about the misapplication of the availability heuristics and keep them current by simply swapping out for the “fear of the day.” In the 1990’s it was children being kidnapped by strangers (it was known as “stranger danger”) despite the facts that kidnappings accounted for only 2% of the violent crimes committed against children, and only 24% of kidnappings are committed by strangers (US Department of Justice, 2007). This fear overlapped with the fear of terrorism that gripped the country after the 2001 terrorist attacks on the World Trade Center and US Pentagon and still plagues the population of the US somewhat in 2020. After a well-publicized, sensational act of violence, people are extremely likely to increase their estimates of the chances that they, too, will be victims of terror. Think about the reality, however. In October of 2001, a terrorist mailed anthrax spores to members of the US government and a number of media companies. A total of five people died as a result of this attack. The nation was nearly paralyzed by the fear of dying from the attack; in reality the probability of an individual person dying was 0.00000002.

The availability heuristic can lead you to make incorrect judgments in a school setting as well. For example, suppose you are trying to decide if you should take a class from a particular math professor. You might try to make a judgment of how good a teacher she is by recalling instances of friends and acquaintances making comments about her teaching skill. You may have some examples that suggest that she is a poor teacher very available to memory, so on the basis of the availability heuristic you judge her a poor teacher and decide to take the class from someone else. What if, however, the instances you recalled were all from the same person, and this person happens to be a very colorful storyteller? The subsequent ease of remembering the instances might not indicate that the professor is a poor teacher after all.

Although the availability heuristic is obviously important, it is not the only judgment heuristic we use. Amos Tversky and Daniel Kahneman examined the role of heuristics in inductive reasoning in a long series of studies. Kahneman received a Nobel Prize in Economics for this research in 2002, and Tversky would have certainly received one as well if he had not died of melanoma at age 59 in 1996 (Nobel Prizes are not awarded posthumously). Kahneman and Tversky demonstrated repeatedly that people do not reason in ways that are consistent with the laws of probability. They identified several heuristic strategies that people use instead to make judgments about likelihood. The importance of this work for economics (and the reason that Kahneman was awarded the Nobel Prize) is that earlier economic theories had assumed that people do make judgments rationally, that is, in agreement with the laws of probability.

Another common heuristic that people use for making judgments is the  representativeness heuristic (Kahneman & Tversky 1973). Suppose we describe a person to you. He is quiet and shy, has an unassuming personality, and likes to work with numbers. Is this person more likely to be an accountant or an attorney? If you said accountant, you were probably using the representativeness heuristic. Our imaginary person is judged likely to be an accountant because he resembles, or is representative of the concept of, an accountant. When research participants are asked to make judgments such as these, the only thing that seems to matter is the representativeness of the description. For example, if told that the person described is in a room that contains 70 attorneys and 30 accountants, participants will still assume that he is an accountant.

inductive reasoning :  a type of reasoning in which we make judgments about likelihood from sets of evidence

inductively strong argument :  an inductive argument in which the beginning statements lead to a conclusion that is probably true

heuristic :  a shortcut strategy that we use to make judgments and solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

availability heuristic :  judging the frequency or likelihood of some event type according to how easily examples of the event can be called to mind (i.e., how available they are to memory)

representativeness heuristic:   judging the likelihood that something is a member of a category on the basis of how much it resembles a typical category member (i.e., how representative it is of the category)

Type 1 thinking : fast, automatic, and emotional thinking.

Type 2 thinking : slow, effortful, and logical thinking.

• What percentage of workplace homicides are co-worker violence?

Many people get these questions wrong. The answers are 10%; stairs; skin; 6%. How close were your answers? Explain how the availability heuristic might have led you to make the incorrect judgments.

• Can you think of some other judgments that you have made (or beliefs that you have) that might have been influenced by the availability heuristic?

7.3 Problem Solving

• Please take a few minutes to list a number of problems that you are facing right now.
• Now write about a problem that you recently solved.
• What is your definition of a problem?

Mary has a problem. Her daughter, ordinarily quite eager to please, appears to delight in being the last person to do anything. Whether getting ready for school, going to piano lessons or karate class, or even going out with her friends, she seems unwilling or unable to get ready on time. Other people have different kinds of problems. For example, many students work at jobs, have numerous family commitments, and are facing a course schedule full of difficult exams, assignments, papers, and speeches. How can they find enough time to devote to their studies and still fulfill their other obligations? Speaking of students and their problems: Show that a ball thrown vertically upward with initial velocity v0 takes twice as much time to return as to reach the highest point (from Spiegel, 1981).

These are three very different situations, but we have called them all problems. What makes them all the same, despite the differences? A psychologist might define a  problem   as a situation with an initial state, a goal state, and a set of possible intermediate states. Somewhat more meaningfully, we might consider a problem a situation in which you are in here one state (e.g., daughter is always late), you want to be there in another state (e.g., daughter is not always late), and with no obvious way to get from here to there. Defined this way, each of the three situations we outlined can now be seen as an example of the same general concept, a problem. At this point, you might begin to wonder what is not a problem, given such a general definition. It seems that nearly every non-routine task we engage in could qualify as a problem. As long as you realize that problems are not necessarily bad (it can be quite fun and satisfying to rise to the challenge and solve a problem), this may be a useful way to think about it.

Can we identify a set of problem-solving skills that would apply to these very different kinds of situations? That task, in a nutshell, is a major goal of this section. Let us try to begin to make sense of the wide variety of ways that problems can be solved with an important observation: the process of solving problems can be divided into two key parts. First, people have to notice, comprehend, and represent the problem properly in their minds (called  problem representation ). Second, they have to apply some kind of solution strategy to the problem. Psychologists have studied both of these key parts of the process in detail.

When you first think about the problem-solving process, you might guess that most of our difficulties would occur because we are failing in the second step, the application of strategies. Although this can be a significant difficulty much of the time, the more important source of difficulty is probably problem representation. In short, we often fail to solve a problem because we are looking at it, or thinking about it, the wrong way.

problem :  a situation in which we are in an initial state, have a desired goal state, and there is a number of possible intermediate states (i.e., there is no obvious way to get from the initial to the goal state)

problem representation :  noticing, comprehending and forming a mental conception of a problem

Defining and Mentally Representing Problems in Order to Solve Them

So, the main obstacle to solving a problem is that we do not clearly understand exactly what the problem is. Recall the problem with Mary’s daughter always being late. One way to represent, or to think about, this problem is that she is being defiant. She refuses to get ready in time. This type of representation or definition suggests a particular type of solution. Another way to think about the problem, however, is to consider the possibility that she is simply being sidetracked by interesting diversions. This different conception of what the problem is (i.e., different representation) suggests a very different solution strategy. For example, if Mary defines the problem as defiance, she may be tempted to solve the problem using some kind of coercive tactics, that is, to assert her authority as her mother and force her to listen. On the other hand, if Mary defines the problem as distraction, she may try to solve it by simply removing the distracting objects.

As you might guess, when a problem is represented one way, the solution may seem very difficult, or even impossible. Seen another way, the solution might be very easy. For example, consider the following problem (from Nasar, 1998):

Two bicyclists start 20 miles apart and head toward each other, each going at a steady rate of 10 miles per hour. At the same time, a fly that travels at a steady 15 miles per hour starts from the front wheel of the southbound bicycle and flies to the front wheel of the northbound one, then turns around and flies to the front wheel of the southbound one again, and continues in this manner until he is crushed between the two front wheels. Question: what total distance did the fly cover?

Please take a few minutes to try to solve this problem.

Most people represent this problem as a question about a fly because, well, that is how the question is asked. The solution, using this representation, is to figure out how far the fly travels on the first leg of its journey, then add this total to how far it travels on the second leg of its journey (when it turns around and returns to the first bicycle), then continue to add the smaller distance from each leg of the journey until you converge on the correct answer. You would have to be quite skilled at math to solve this problem, and you would probably need some time and pencil and paper to do it.

If you consider a different representation, however, you can solve this problem in your head. Instead of thinking about it as a question about a fly, think about it as a question about the bicycles. They are 20 miles apart, and each is traveling 10 miles per hour. How long will it take for the bicycles to reach each other? Right, one hour. The fly is traveling 15 miles per hour; therefore, it will travel a total of 15 miles back and forth in the hour before the bicycles meet. Represented one way (as a problem about a fly), the problem is quite difficult. Represented another way (as a problem about two bicycles), it is easy. Changing your representation of a problem is sometimes the best—sometimes the only—way to solve it.

Unfortunately, however, changing a problem’s representation is not the easiest thing in the world to do. Often, problem solvers get stuck looking at a problem one way. This is called  fixation . Most people who represent the preceding problem as a problem about a fly probably do not pause to reconsider, and consequently change, their representation. A parent who thinks her daughter is being defiant is unlikely to consider the possibility that her behavior is far less purposeful.

Problem-solving fixation was examined by a group of German psychologists called Gestalt psychologists during the 1930’s and 1940’s. Karl Dunker, for example, discovered an important type of failure to take a different perspective called  functional fixedness . Imagine being a participant in one of his experiments. You are asked to figure out how to mount two candles on a door and are given an assortment of odds and ends, including a small empty cardboard box and some thumbtacks. Perhaps you have already figured out a solution: tack the box to the door so it forms a platform, then put the candles on top of the box. Most people are able to arrive at this solution. Imagine a slight variation of the procedure, however. What if, instead of being empty, the box had matches in it? Most people given this version of the problem do not arrive at the solution given above. Why? Because it seems to people that when the box contains matches, it already has a function; it is a matchbox. People are unlikely to consider a new function for an object that already has a function. This is functional fixedness.

Mental set is a type of fixation in which the problem solver gets stuck using the same solution strategy that has been successful in the past, even though the solution may no longer be useful. It is commonly seen when students do math problems for homework. Often, several problems in a row require the reapplication of the same solution strategy. Then, without warning, the next problem in the set requires a new strategy. Many students attempt to apply the formerly successful strategy on the new problem and therefore cannot come up with a correct answer.

The thing to remember is that you cannot solve a problem unless you correctly identify what it is to begin with (initial state) and what you want the end result to be (goal state). That may mean looking at the problem from a different angle and representing it in a new way. The correct representation does not guarantee a successful solution, but it certainly puts you on the right track.

A bit more optimistically, the Gestalt psychologists discovered what may be considered the opposite of fixation, namely  insight . Sometimes the solution to a problem just seems to pop into your head. Wolfgang Kohler examined insight by posing many different problems to chimpanzees, principally problems pertaining to their acquisition of out-of-reach food. In one version, a banana was placed outside of a chimpanzee’s cage and a short stick inside the cage. The stick was too short to retrieve the banana, but was long enough to retrieve a longer stick also located outside of the cage. This second stick was long enough to retrieve the banana. After trying, and failing, to reach the banana with the shorter stick, the chimpanzee would try a couple of random-seeming attempts, react with some apparent frustration or anger, then suddenly rush to the longer stick, the correct solution fully realized at this point. This sudden appearance of the solution, observed many times with many different problems, was termed insight by Kohler.

Lest you think it pertains to chimpanzees only, Karl Dunker demonstrated that children also solve problems through insight in the 1930s. More importantly, you have probably experienced insight yourself. Think back to a time when you were trying to solve a difficult problem. After struggling for a while, you gave up. Hours later, the solution just popped into your head, perhaps when you were taking a walk, eating dinner, or lying in bed.

fixation :  when a problem solver gets stuck looking at a problem a particular way and cannot change his or her representation of it (or his or her intended solution strategy)

functional fixedness :  a specific type of fixation in which a problem solver cannot think of a new use for an object that already has a function

mental set :  a specific type of fixation in which a problem solver gets stuck using the same solution strategy that has been successful in the past

insight :  a sudden realization of a solution to a problem

Solving Problems by Trial and Error

Correctly identifying the problem and your goal for a solution is a good start, but recall the psychologist’s definition of a problem: it includes a set of possible intermediate states. Viewed this way, a problem can be solved satisfactorily only if one can find a path through some of these intermediate states to the goal. Imagine a fairly routine problem, finding a new route to school when your ordinary route is blocked (by road construction, for example). At each intersection, you may turn left, turn right, or go straight. A satisfactory solution to the problem (of getting to school) is a sequence of selections at each intersection that allows you to wind up at school.

If you had all the time in the world to get to school, you might try choosing intermediate states randomly. At one corner you turn left, the next you go straight, then you go left again, then right, then right, then straight. Unfortunately, trial and error will not necessarily get you where you want to go, and even if it does, it is not the fastest way to get there. For example, when a friend of ours was in college, he got lost on the way to a concert and attempted to find the venue by choosing streets to turn onto randomly (this was long before the use of GPS). Amazingly enough, the strategy worked, although he did end up missing two out of the three bands who played that night.

Trial and error is not all bad, however. B.F. Skinner, a prominent behaviorist psychologist, suggested that people often behave randomly in order to see what effect the behavior has on the environment and what subsequent effect this environmental change has on them. This seems particularly true for the very young person. Picture a child filling a household’s fish tank with toilet paper, for example. To a child trying to develop a repertoire of creative problem-solving strategies, an odd and random behavior might be just the ticket. Eventually, the exasperated parent hopes, the child will discover that many of these random behaviors do not successfully solve problems; in fact, in many cases they create problems. Thus, one would expect a decrease in this random behavior as a child matures. You should realize, however, that the opposite extreme is equally counterproductive. If the children become too rigid, never trying something unexpected and new, their problem solving skills can become too limited.

Effective problem solving seems to call for a happy medium that strikes a balance between using well-founded old strategies and trying new ground and territory. The individual who recognizes a situation in which an old problem-solving strategy would work best, and who can also recognize a situation in which a new untested strategy is necessary is halfway to success.

Solving Problems with Algorithms and Heuristics

For many problems there is a possible strategy available that will guarantee a correct solution. For example, think about math problems. Math lessons often consist of step-by-step procedures that can be used to solve the problems. If you apply the strategy without error, you are guaranteed to arrive at the correct solution to the problem. This approach is called using an  algorithm , a term that denotes the step-by-step procedure that guarantees a correct solution. Because algorithms are sometimes available and come with a guarantee, you might think that most people use them frequently. Unfortunately, however, they do not. As the experience of many students who have struggled through math classes can attest, algorithms can be extremely difficult to use, even when the problem solver knows which algorithm is supposed to work in solving the problem. In problems outside of math class, we often do not even know if an algorithm is available. It is probably fair to say, then, that algorithms are rarely used when people try to solve problems.

Because algorithms are so difficult to use, people often pass up the opportunity to guarantee a correct solution in favor of a strategy that is much easier to use and yields a reasonable chance of coming up with a correct solution. These strategies are called  problem solving heuristics . Similar to what you saw in section 6.2 with reasoning heuristics, a problem solving heuristic is a shortcut strategy that people use when trying to solve problems. It usually works pretty well, but does not guarantee a correct solution to the problem. For example, one problem solving heuristic might be “always move toward the goal” (so when trying to get to school when your regular route is blocked, you would always turn in the direction you think the school is). A heuristic that people might use when doing math homework is “use the same solution strategy that you just used for the previous problem.”

By the way, we hope these last two paragraphs feel familiar to you. They seem to parallel a distinction that you recently learned. Indeed, algorithms and problem-solving heuristics are another example of the distinction between Type 1 thinking and Type 2 thinking.

Although it is probably not worth describing a large number of specific heuristics, two observations about heuristics are worth mentioning. First, heuristics can be very general or they can be very specific, pertaining to a particular type of problem only. For example, “always move toward the goal” is a general strategy that you can apply to countless problem situations. On the other hand, “when you are lost without a functioning gps, pick the most expensive car you can see and follow it” is specific to the problem of being lost. Second, all heuristics are not equally useful. One heuristic that many students know is “when in doubt, choose c for a question on a multiple-choice exam.” This is a dreadful strategy because many instructors intentionally randomize the order of answer choices. Another test-taking heuristic, somewhat more useful, is “look for the answer to one question somewhere else on the exam.”

You really should pay attention to the application of heuristics to test taking. Imagine that while reviewing your answers for a multiple-choice exam before turning it in, you come across a question for which you originally thought the answer was c. Upon reflection, you now think that the answer might be b. Should you change the answer to b, or should you stick with your first impression? Most people will apply the heuristic strategy to “stick with your first impression.” What they do not realize, of course, is that this is a very poor strategy (Lilienfeld et al, 2009). Most of the errors on exams come on questions that were answered wrong originally and were not changed (so they remain wrong). There are many fewer errors where we change a correct answer to an incorrect answer. And, of course, sometimes we change an incorrect answer to a correct answer. In fact, research has shown that it is more common to change a wrong answer to a right answer than vice versa (Bruno, 2001).

The belief in this poor test-taking strategy (stick with your first impression) is based on the  confirmation bias   (Nickerson, 1998; Wason, 1960). You first saw the confirmation bias in Module 1, but because it is so important, we will repeat the information here. People have a bias, or tendency, to notice information that confirms what they already believe. Somebody at one time told you to stick with your first impression, so when you look at the results of an exam you have taken, you will tend to notice the cases that are consistent with that belief. That is, you will notice the cases in which you originally had an answer correct and changed it to the wrong answer. You tend not to notice the other two important (and more common) cases, changing an answer from wrong to right, and leaving a wrong answer unchanged.

Because heuristics by definition do not guarantee a correct solution to a problem, mistakes are bound to occur when we employ them. A poor choice of a specific heuristic will lead to an even higher likelihood of making an error.

algorithm :  a step-by-step procedure that guarantees a correct solution to a problem

problem solving heuristic :  a shortcut strategy that we use to solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

confirmation bias :  people’s tendency to notice information that confirms what they already believe

An Effective Problem-Solving Sequence

You may be left with a big question: If algorithms are hard to use and heuristics often don’t work, how am I supposed to solve problems? Robert Sternberg (1996), as part of his theory of what makes people successfully intelligent (Module 8) described a problem-solving sequence that has been shown to work rather well:

• Identify the existence of a problem.  In school, problem identification is often easy; problems that you encounter in math classes, for example, are conveniently labeled as problems for you. Outside of school, however, realizing that you have a problem is a key difficulty that you must get past in order to begin solving it. You must be very sensitive to the symptoms that indicate a problem.
• Define the problem.  Suppose you realize that you have been having many headaches recently. Very likely, you would identify this as a problem. If you define the problem as “headaches,” the solution would probably be to take aspirin or ibuprofen or some other anti-inflammatory medication. If the headaches keep returning, however, you have not really solved the problem—likely because you have mistaken a symptom for the problem itself. Instead, you must find the root cause of the headaches. Stress might be the real problem. For you to successfully solve many problems it may be necessary for you to overcome your fixations and represent the problems differently. One specific strategy that you might find useful is to try to define the problem from someone else’s perspective. How would your parents, spouse, significant other, doctor, etc. define the problem? Somewhere in these different perspectives may lurk the key definition that will allow you to find an easier and permanent solution.
• Formulate strategy.  Now it is time to begin planning exactly how the problem will be solved. Is there an algorithm or heuristic available for you to use? Remember, heuristics by their very nature guarantee that occasionally you will not be able to solve the problem. One point to keep in mind is that you should look for long-range solutions, which are more likely to address the root cause of a problem than short-range solutions.
• Represent and organize information.  Similar to the way that the problem itself can be defined, or represented in multiple ways, information within the problem is open to different interpretations. Suppose you are studying for a big exam. You have chapters from a textbook and from a supplemental reader, along with lecture notes that all need to be studied. How should you (represent and) organize these materials? Should you separate them by type of material (text versus reader versus lecture notes), or should you separate them by topic? To solve problems effectively, you must learn to find the most useful representation and organization of information.
• Allocate resources.  This is perhaps the simplest principle of the problem solving sequence, but it is extremely difficult for many people. First, you must decide whether time, money, skills, effort, goodwill, or some other resource would help to solve the problem Then, you must make the hard choice of deciding which resources to use, realizing that you cannot devote maximum resources to every problem. Very often, the solution to problem is simply to change how resources are allocated (for example, spending more time studying in order to improve grades).
• Monitor and evaluate solutions.  Pay attention to the solution strategy while you are applying it. If it is not working, you may be able to select another strategy. Another fact you should realize about problem solving is that it never does end. Solving one problem frequently brings up new ones. Good monitoring and evaluation of your problem solutions can help you to anticipate and get a jump on solving the inevitable new problems that will arise.

Please note that this as  an  effective problem-solving sequence, not  the  effective problem solving sequence. Just as you can become fixated and end up representing the problem incorrectly or trying an inefficient solution, you can become stuck applying the problem-solving sequence in an inflexible way. Clearly there are problem situations that can be solved without using these skills in this order.

Additionally, many real-world problems may require that you go back and redefine a problem several times as the situation changes (Sternberg et al. 2000). For example, consider the problem with Mary’s daughter one last time. At first, Mary did represent the problem as one of defiance. When her early strategy of pleading and threatening punishment was unsuccessful, Mary began to observe her daughter more carefully. She noticed that, indeed, her daughter’s attention would be drawn by an irresistible distraction or book. Fresh with a re-representation of the problem, she began a new solution strategy. She began to remind her daughter every few minutes to stay on task and remind her that if she is ready before it is time to leave, she may return to the book or other distracting object at that time. Fortunately, this strategy was successful, so Mary did not have to go back and redefine the problem again.

Pick one or two of the problems that you listed when you first started studying this section and try to work out the steps of Sternberg’s problem solving sequence for each one.

a mental representation of a category of things in the world

an assumption about the truth of something that is not stated. Inferences come from our prior knowledge and experience, and from logical reasoning

knowledge about one’s own cognitive processes; thinking about your thinking

individuals who are less competent tend to overestimate their abilities more than individuals who are more competent do

Thinking like a scientist in your everyday life for the purpose of drawing correct conclusions. It entails skepticism; an ability to identify biases, distortions, omissions, and assumptions; and excellent deductive and inductive reasoning, and problem solving skills.

a way of thinking in which you refrain from drawing a conclusion or changing your mind until good evidence has been provided

an inclination, tendency, leaning, or prejudice

a type of reasoning in which the conclusion is guaranteed to be true any time the statements leading up to it are true

a set of statements in which the beginning statements lead to a conclusion

an argument for which true beginning statements guarantee that the conclusion is true

a type of reasoning in which we make judgments about likelihood from sets of evidence

an inductive argument in which the beginning statements lead to a conclusion that is probably true

fast, automatic, and emotional thinking

slow, effortful, and logical thinking

a shortcut strategy that we use to make judgments and solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

udging the frequency or likelihood of some event type according to how easily examples of the event can be called to mind (i.e., how available they are to memory)

judging the likelihood that something is a member of a category on the basis of how much it resembles a typical category member (i.e., how representative it is of the category)

a situation in which we are in an initial state, have a desired goal state, and there is a number of possible intermediate states (i.e., there is no obvious way to get from the initial to the goal state)

noticing, comprehending and forming a mental conception of a problem

when a problem solver gets stuck looking at a problem a particular way and cannot change his or her representation of it (or his or her intended solution strategy)

a specific type of fixation in which a problem solver cannot think of a new use for an object that already has a function

a specific type of fixation in which a problem solver gets stuck using the same solution strategy that has been successful in the past

a sudden realization of a solution to a problem

a step-by-step procedure that guarantees a correct solution to a problem

The tendency to notice and pay attention to information that confirms your prior beliefs and to ignore information that disconfirms them.

a shortcut strategy that we use to solve problems. Although they are easy to use, they do not guarantee correct judgments and solutions

Introduction to Psychology Copyright © 2020 by Ken Gray; Elizabeth Arnott-Hill; and Or'Shaundra Benson is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Analytical Thinking vs Problem Solving: A Comprehensive Comparison

Analytical thinking and problem solving are crucial skills in various aspects of life, including personal and professional situations. While they may seem interchangeable, there are distinct differences between the two. Analytical thinking focuses on breaking down complex information into smaller, manageable components to understand a situation and evaluate alternatives effectively. On the other hand, problem solving involves devising practical solutions to overcome challenges or resolve issues that arise in daily life or the workplace.

Key Takeaways

Understanding analytical thinking.

Nature of Analytical Thinking

Key components of analytical thinking include reasoning, fact-checking, and questioning assumptions. This skill set allows individuals to approach problems with an open mind, meticulously gather and analyze data, and make well-informed decisions. Ultimately, analytical thinking leads to more informed and strategic decision-making, increasing the likelihood of success in professional and personal endeavors.

How Analytical Thinking Works

It is important to note that analytical thinking is not solely reserved for mathematicians or scientists but is a valuable skill applicable to a wide range of disciplines and professions. From business analysts, who require analytical thinking and problem-solving skills to identify and implement changes, to daily decision-making in personal lives, analytical reasoning plays a vital role in successfully navigating through various complexities.

Significance of Problem Solving

Features of problem solving, process of problem solving, comparing analytical thinking and problem solving, similarities.

Moreover, practicing both analytical thinking and problem-solving techniques can lead to improved decision-making abilities. This development, in turn, translates into greater efficiency and effectiveness in personal and professional contexts.

Differences

In conclusion, analytical thinking and problem-solving, while both essential skills, have distinct applications and methods, and their effective use can be instrumental in achieving success in various aspects of life.

Ways to Improve Both Techniques

Developing analytical thinking.

Collaborating with others can also help individuals enhance their analytical thinking skills. By working together, people can build on each other’s strengths and overcome challenges. Additionally, they can exchange ideas and learn from different viewpoints, which may lead to innovative solutions.

Enhancing Problem Solving Skills

Utilizing a methodical approach to problem-solving can also yield positive results. Techniques like breaking down complex issues into manageable steps or generating multiple possible solutions can enable a more comprehensive analysis, increasing the likelihood of success in overcoming challenges.

Importance in Workplace and Career Success

Relevance in the workplace.

Effective communication is an important aspect of analytical thinking and problem solving. In a professional setting, employees must often convey their findings and ideas to stakeholders, ensuring that solutions are implemented appropriately and any concerns are addressed. This communication can lead to improved collaboration, clearer goals, and faster resolution of issues 3 .

Implication for Career Success

Role in decision making and risk management, influence on decision making.

Analytical thinking plays a crucial role in decision making, as it involves breaking things down into their component parts and using deductive reasoning to draw conclusions from given evidence and assumptions source . This allows individuals and organizations to carefully consider the pros and cons of each option, determine the feasibility of implementing potential solutions, and weigh the costs and benefits associated with each decision.

Contribution to Risk Management

Similarly, problem-solving assists in risk management by addressing potential challenges that may arise during the implementation of solutions, such as examining potential obstacles, resource constraints, and other factors that may impact the success of an initiative source . By combining the strengths of both analytical thinking and problem-solving, decision-makers can enhance their risk management strategies and ensure a higher probability of success in their respective decisions.

Utilization in Business Analysis

Application in business analysis.

When approaching a problem, business analysts consider several key factors, such as people, processes, and technology. They employ systems thinking to understand the enterprise holistically and how all these elements interact. This mindset helps them to not only identify the root cause of a problem, but also to develop solutions that address the underlying issues effectively [2] .

Understanding Financial Data

Real life examples.

Analytical thinking and problem solving are essential skills in both personal and professional life. They allow individuals to tackle complex issues, identify the root causes, and develop effective solutions. Let’s examine some real-life examples that emphasize the differences between these two thought processes.

Another example can be found in the realm of personal finance. Analytical thinking would be employed to evaluate one’s financial situation and understand patterns in spending habits. This analysis could reveal areas where money may be saved or better utilized. For instance, it may uncover excessive spending on dining out or ineffective monthly budgeting practices.

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Analytic vs Holistic Thinking: Perspectives for Enhanced Problem Solving

Exploring the world of human cognition, we encounter two intriguing thinking approaches: analytic and holistic thinking.

Each possesses distinct strengths and applications, and understanding when to wield them can profoundly impact different facets of our lives.

In this article, we’ll delve into the essence of both analytic and holistic thinking, delve into their unique qualities, and unearth how they can collaborate to enhance problem-solving and decision-making with greater effectiveness.

What is Analytic Thinking?

Analytic thinking can be compared to the role of a detective in our own thoughts.

It’s like unraveling intricate problems by breaking them down into smaller components, somewhat similar to solving a puzzle or peeling the layers of an onion.

By closely examining these individual pieces, we gain a deeper understanding of how they interconnect, ultimately assisting us in problem-solving and comprehending various real-life situations.

Analytic thinking serves as a valuable tool for dissecting and reassembling information to gain insights into the bigger picture.

• Read also : Why Following Rules Isn’t Always Rational: Logic of Appropriateness
• Read also : What is Convergent Thinking

Characteristics of analytic thinking

Key characteristics of analytic thinking include:

Detail-Oriented

Analytic thinking is akin to the meticulous work of a detective carefully scrutinizing each clue at a crime scene.

It’s about immersing oneself in the specific details and facts, no matter how minuscule, to acquire a profound grasp of a problem.

Analytic thinkers excel not only in collecting information but also in connecting the dots, identifying patterns, and unveiling concealed solutions within the data, much like the process of piecing together a jigsaw puzzle.

Linear and sequential 

Analytic thinkers approach problem-solving in a structured and sequential manner, much like architects building a skyscraper floor by floor or following a recipe to cook a meal.

They break down complex problems into manageable steps, ensuring that no crucial detail is overlooked.

This approach is akin to following a treasure map’s clues or a journey where each step contributes to the final outcome. 

Critical evaluation

Analytic thinking encompasses critical analysis, hypothesis testing, and a systematic approach to problem-solving.

It involves meticulously evaluating information, similar to a detective who carefully examines evidence to solve a case.

Analytic thinkers use a scientific method, forming hypotheses and testing them, much like scientists in a lab conducting experiments.

When to use analytic thinking?

Analytic thinking is most suitable for situations requiring precision, accuracy, and a systematic approach.

It excels in fields like mathematics, science, and engineering, and when troubleshooting technical problems.

It ensures precise solutions in mathematical equations, grounded reasoning in scientific research, meticulous design in engineering, and systematic issue resolution in technical matters.

However, it can also be applied in various life situations, helping with logical decision-making and strategic planning.

Analytic thinking is like a specialized tool that ensures reliable and accurate outcomes when precision is paramount.

What is Holistic Thinking?

Holistic thinking is about appreciating the interconnectedness of elements within a system, rather than isolating them.

It’s like stepping back to see the entire forest, understanding that every component contributes to the ecosystem’s balance.

Holistic thinking acknowledges the complexity of relationships and embraces it, much like appreciating the intricacies of a masterpiece painting.

It’s about finding harmony within complexity, where each part plays a unique role in creating a balanced and vibrant whole, whether it’s in nature, the human body, city planning, or any interconnected system.

Characteristics of holistic thinking

Key characteristics of holistic thinking include:

Big-picture perspective 

Holistic thinking entails embracing a broader perspective, acknowledging that the entirety can surpass the mere summation of its components.

It’s akin to marveling at a panoramic landscape rather than fixating on specific details.

It’s the realization that the delectable flavor of a cake emerges from the harmonious blend of its ingredients and the understanding that the vitality of a city emanates from the harmonious synergy of its diverse elements.

Creative and intuitive

Holistic thinking relies on intuition , empathy, and creative insights to solve problems and make connections .

It’s akin to being an artist, composer, and explorer, where creative inspiration guides problem-solving.

This approach values emotional understanding and human nature, making it essential in fields like business, healthcare, and relationships. 

Embracing complexity

Holistic thinking thrives in complex situations where multiple variables are at play.

It’s like a skilled director orchestrating a play with a large cast, understanding how each character contributes to the narrative.

Holistic thinking envisions the complete picture in complex puzzles, recognizing that every piece plays a role in the whole. 

When to use holistic thinking?

Holistic thinking is valuable in scenarios requiring creativity, empathy, and an understanding of human behavior.

It finds application in psychology, where it delves into the intricate aspects of the human mind and emotions, going beyond symptoms to understand a person’s life story.

In the world of art, holistic thinking allows for the creation of masterpieces by blending colors, emotions, and concepts.

In design, it ensures products and experiences are not only functional but also aesthetically pleasing and well-integrated into broader contexts.

For addressing complex societal and environmental issues, holistic thinking helps grasp the interconnectedness of problems and make informed decisions.

It’s a versatile approach that appreciates the complexity of life and guides decision-making in various fields.

The Benefits of Both Analytic and Holistic Thinking

While analytic and holistic thinking may seem like opposing forces, they are not mutually exclusive. In fact, when combined, they can yield remarkable results:

Enhanced problem-solving 

Integrating both holistic and analytic thinking approaches enhances problem-solving.

Holistic thinking, with its focus on the bigger picture, creativity, and empathy, is valuable in understanding human behavior, art, design, and complex societal issues.

Analytic thinking excels in precision and systematic problem-solving in fields like mathematics and science.

Combining both approaches offers a more comprehensive problem-solving toolkit for various scenarios.

Innovation 

Innovation often results from the collaboration of analytic and holistic thinking.

Analytic thinking provides a structured foundation with precise data and logical deductions, akin to building the base of a skyscraper.

Holistic thinking, like a creative maestro, weaves these facts and figures into a visionary narrative, envisioning how ideas can transform into innovation. 

Adaptability 

The ability to switch between analytic and holistic thinking modes enhances adaptability in various situations.

Like a versatile musician playing different instruments, individuals can choose the thinking mode that best suits the task at hand.

This adaptability is valuable in diverse fields, from business to education, and enriches problem-solving and understanding of the world. 

Better decision-making 

Holistic thinking enhances decision-making by considering both short-term and long-term consequences.

It goes beyond analyzing immediate pros and cons, guiding individuals to make well-rounded decisions that align with their life’s broader narrative.

Holistic thinking ensures that choices resonate with values, aspirations, and the legacy one wants to create, whether in career decisions, personal relationships, or business leadership.

• Read also : What is Linear Thinking? The Basics of This Problem-Solving
• Read also : What is Dialectical Thinking

In the journey of human thought, both analytic and holistic thinking play pivotal roles, like two sides of the same coin.

Recognizing the strengths of each and knowing when to employ them empowers us to approach challenges and opportunities with greater wisdom and insight.

In a world that thrives on complexity, balancing these thinking styles can lead to more profound understanding and innovative solutions.

Absolutely! While individuals may have a natural inclination toward one style, it’s entirely possible to develop proficiency in both through practice and awareness.

Rarely. Most situations benefit from a blend of both thinking styles. However, specific tasks or professions may lean more heavily toward one or the other.

Enhancing holistic thinking involves practicing empathy, embracing complexity, and seeking diverse perspectives. Engaging in creative activities and expanding your knowledge in various fields can also help.

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Critical thinking and problem-solving, jump to: , what is critical thinking, characteristics of critical thinking, why teach critical thinking.

• Teaching Strategies to Help Promote Critical Thinking Skills

References and Resources

When examining the vast literature on critical thinking, various definitions of critical thinking emerge. Here are some samples:

• "Critical thinking is the intellectually disciplined process of actively and skillfully conceptualizing, applying, analyzing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication, as a guide to belief and action" (Scriven, 1996).
• "Most formal definitions characterize critical thinking as the intentional application of rational, higher order thinking skills, such as analysis, synthesis, problem recognition and problem solving, inference, and evaluation" (Angelo, 1995, p. 6).
• "Critical thinking is thinking that assesses itself" (Center for Critical Thinking, 1996b).
• "Critical thinking is the ability to think about one's thinking in such a way as 1. To recognize its strengths and weaknesses and, as a result, 2. To recast the thinking in improved form" (Center for Critical Thinking, 1996c).

Perhaps the simplest definition is offered by Beyer (1995) : "Critical thinking... means making reasoned judgments" (p. 8). Basically, Beyer sees critical thinking as using criteria to judge the quality of something, from cooking to a conclusion of a research paper. In essence, critical thinking is a disciplined manner of thought that a person uses to assess the validity of something (statements, news stories, arguments, research, etc.).

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Wade (1995) identifies eight characteristics of critical thinking. Critical thinking involves asking questions, defining a problem, examining evidence, analyzing assumptions and biases, avoiding emotional reasoning, avoiding oversimplification, considering other interpretations, and tolerating ambiguity. Dealing with ambiguity is also seen by Strohm & Baukus (1995) as an essential part of critical thinking, "Ambiguity and doubt serve a critical-thinking function and are a necessary and even a productive part of the process" (p. 56).

Another characteristic of critical thinking identified by many sources is metacognition. Metacognition is thinking about one's own thinking. More specifically, "metacognition is being aware of one's thinking as one performs specific tasks and then using this awareness to control what one is doing" (Jones & Ratcliff, 1993, p. 10 ).

In the book, Critical Thinking, Beyer elaborately explains what he sees as essential aspects of critical thinking. These are:

• Dispositions: Critical thinkers are skeptical, open-minded, value fair-mindedness, respect evidence and reasoning, respect clarity and precision, look at different points of view, and will change positions when reason leads them to do so.
• Criteria: To think critically, must apply criteria. Need to have conditions that must be met for something to be judged as believable. Although the argument can be made that each subject area has different criteria, some standards apply to all subjects. "... an assertion must... be based on relevant, accurate facts; based on credible sources; precise; unbiased; free from logical fallacies; logically consistent; and strongly reasoned" (p. 12).
• Argument: Is a statement or proposition with supporting evidence. Critical thinking involves identifying, evaluating, and constructing arguments.
• Reasoning: The ability to infer a conclusion from one or multiple premises. To do so requires examining logical relationships among statements or data.
• Point of View: The way one views the world, which shapes one's construction of meaning. In a search for understanding, critical thinkers view phenomena from many different points of view.
• Procedures for Applying Criteria: Other types of thinking use a general procedure. Critical thinking makes use of many procedures. These procedures include asking questions, making judgments, and identifying assumptions.

Oliver & Utermohlen (1995) see students as too often being passive receptors of information. Through technology, the amount of information available today is massive. This information explosion is likely to continue in the future. Students need a guide to weed through the information and not just passively accept it. Students need to "develop and effectively apply critical thinking skills to their academic studies, to the complex problems that they will face, and to the critical choices they will be forced to make as a result of the information explosion and other rapid technological changes" (Oliver & Utermohlen, p. 1 ).

As mentioned in the section, Characteristics of Critical Thinking , critical thinking involves questioning. It is important to teach students how to ask good questions, to think critically, in order to continue the advancement of the very fields we are teaching. "Every field stays alive only to the extent that fresh questions are generated and taken seriously" (Center for Critical Thinking, 1996a ).

Beyer sees the teaching of critical thinking as important to the very state of our nation. He argues that to live successfully in a democracy, people must be able to think critically in order to make sound decisions about personal and civic affairs. If students learn to think critically, then they can use good thinking as the guide by which they live their lives.

Teaching Strategies to Help Promote Critical Thinking

The 1995, Volume 22, issue 1, of the journal, Teaching of Psychology , is devoted to the teaching critical thinking. Most of the strategies included in this section come from the various articles that compose this issue.

• CATS (Classroom Assessment Techniques): Angelo stresses the use of ongoing classroom assessment as a way to monitor and facilitate students' critical thinking. An example of a CAT is to ask students to write a "Minute Paper" responding to questions such as "What was the most important thing you learned in today's class? What question related to this session remains uppermost in your mind?" The teacher selects some of the papers and prepares responses for the next class meeting.
• Cooperative Learning Strategies: Cooper (1995) argues that putting students in group learning situations is the best way to foster critical thinking. "In properly structured cooperative learning environments, students perform more of the active, critical thinking with continuous support and feedback from other students and the teacher" (p. 8).
• Case Study /Discussion Method: McDade (1995) describes this method as the teacher presenting a case (or story) to the class without a conclusion. Using prepared questions, the teacher then leads students through a discussion, allowing students to construct a conclusion for the case.
• Using Questions: King (1995) identifies ways of using questions in the classroom:
• Reciprocal Peer Questioning: Following lecture, the teacher displays a list of question stems (such as, "What are the strengths and weaknesses of...). Students must write questions about the lecture material. In small groups, the students ask each other the questions. Then, the whole class discusses some of the questions from each small group.
• Reader's Questions: Require students to write questions on assigned reading and turn them in at the beginning of class. Select a few of the questions as the impetus for class discussion.
• Conference Style Learning: The teacher does not "teach" the class in the sense of lecturing. The teacher is a facilitator of a conference. Students must thoroughly read all required material before class. Assigned readings should be in the zone of proximal development. That is, readings should be able to be understood by students, but also challenging. The class consists of the students asking questions of each other and discussing these questions. The teacher does not remain passive, but rather, helps "direct and mold discussions by posing strategic questions and helping students build on each others' ideas" (Underwood & Wald, 1995, p. 18 ).
• Use Writing Assignments: Wade sees the use of writing as fundamental to developing critical thinking skills. "With written assignments, an instructor can encourage the development of dialectic reasoning by requiring students to argue both [or more] sides of an issue" (p. 24).
• Written dialogues: Give students written dialogues to analyze. In small groups, students must identify the different viewpoints of each participant in the dialogue. Must look for biases, presence or exclusion of important evidence, alternative interpretations, misstatement of facts, and errors in reasoning. Each group must decide which view is the most reasonable. After coming to a conclusion, each group acts out their dialogue and explains their analysis of it.
• Spontaneous Group Dialogue: One group of students are assigned roles to play in a discussion (such as leader, information giver, opinion seeker, and disagreer). Four observer groups are formed with the functions of determining what roles are being played by whom, identifying biases and errors in thinking, evaluating reasoning skills, and examining ethical implications of the content.
• Ambiguity: Strohm & Baukus advocate producing much ambiguity in the classroom. Don't give students clear cut material. Give them conflicting information that they must think their way through.
• Angelo, T. A. (1995). Beginning the dialogue: Thoughts on promoting critical thinking: Classroom assessment for critical thinking. Teaching of Psychology, 22(1), 6-7.
• Beyer, B. K. (1995). Critical thinking. Bloomington, IN: Phi Delta Kappa Educational Foundation.
• Center for Critical Thinking (1996a). The role of questions in thinking, teaching, and learning. [On-line]. Available HTTP: http://www.criticalthinking.org/University/univlibrary/library.nclk
• Center for Critical Thinking (1996b). Structures for student self-assessment. [On-line]. Available HTTP: http://www.criticalthinking.org/University/univclass/trc.nclk
• Center for Critical Thinking (1996c). Three definitions of critical thinking [On-line]. Available HTTP: http://www.criticalthinking.org/University/univlibrary/library.nclk
• Cooper, J. L. (1995). Cooperative learning and critical thinking. Teaching of Psychology, 22(1), 7-8.
• Jones, E. A. & Ratcliff, G. (1993). Critical thinking skills for college students. National Center on Postsecondary Teaching, Learning, and Assessment, University Park, PA. (Eric Document Reproduction Services No. ED 358 772)
• King, A. (1995). Designing the instructional process to enhance critical thinking across the curriculum: Inquiring minds really do want to know: Using questioning to teach critical thinking. Teaching of Psychology, 22 (1) , 13-17.
• McDade, S. A. (1995). Case study pedagogy to advance critical thinking. Teaching Psychology, 22(1), 9-10.
• Oliver, H. & Utermohlen, R. (1995). An innovative teaching strategy: Using critical thinking to give students a guide to the future.(Eric Document Reproduction Services No. 389 702)
• Robertson, J. F. & Rane-Szostak, D. (1996). Using dialogues to develop critical thinking skills: A practical approach. Journal of Adolescent & Adult Literacy, 39(7), 552-556.
• Scriven, M. & Paul, R. (1996). Defining critical thinking: A draft statement for the National Council for Excellence in Critical Thinking. [On-line]. Available HTTP: http://www.criticalthinking.org/University/univlibrary/library.nclk
• Strohm, S. M., & Baukus, R. A. (1995). Strategies for fostering critical thinking skills. Journalism and Mass Communication Educator, 50 (1), 55-62.
• Underwood, M. K., & Wald, R. L. (1995). Conference-style learning: A method for fostering critical thinking with heart. Teaching Psychology, 22(1), 17-21.
• Wade, C. (1995). Using writing to develop and assess critical thinking. Teaching of Psychology, 22(1), 24-28.

Other Reading

• Bean, J. C. (1996). Engaging ideas: The professor's guide to integrating writing, critical thinking, & active learning in the classroom. Jossey-Bass.
• Bernstein, D. A. (1995). A negotiation model for teaching critical thinking. Teaching of Psychology, 22(1), 22-24.
• Carlson, E. R. (1995). Evaluating the credibility of sources. A missing link in the teaching of critical thinking. Teaching of Psychology, 22(1), 39-41.
• Facione, P. A., Sanchez, C. A., Facione, N. C., & Gainen, J. (1995). The disposition toward critical thinking. The Journal of General Education, 44(1), 1-25.
• Halpern, D. F., & Nummedal, S. G. (1995). Closing thoughts about helping students improve how they think. Teaching of Psychology, 22(1), 82-83.
• Isbell, D. (1995). Teaching writing and research as inseparable: A faculty-librarian teaching team. Reference Services Review, 23(4), 51-62.
• Jones, J. M. & Safrit, R. D. (1994). Developing critical thinking skills in adult learners through innovative distance learning. Paper presented at the International Conference on the practice of adult education and social development. Jinan, China. (Eric Document Reproduction Services No. ED 373 159)
• Sanchez, M. A. (1995). Using critical-thinking principles as a guide to college-level instruction. Teaching of Psychology, 22(1), 72-74.
• Spicer, K. L. & Hanks, W. E. (1995). Multiple measures of critical thinking skills and predisposition in assessment of critical thinking. Paper presented at the annual meeting of the Speech Communication Association, San Antonio, TX. (Eric Document Reproduction Services No. ED 391 185)
• Terenzini, P. T., Springer, L., Pascarella, E. T., & Nora, A. (1995). Influences affecting the development of students' critical thinking skills. Research in Higher Education, 36(1), 23-39.

On the Internet

• Carr, K. S. (1990). How can we teach critical thinking. Eric Digest. [On-line]. Available HTTP: http://ericps.ed.uiuc.edu/eece/pubs/digests/1990/carr90.html
• The Center for Critical Thinking (1996). Home Page. Available HTTP: http://www.criticalthinking.org/University/
• Ennis, Bob (No date). Critical thinking. [On-line], April 4, 1997. Available HTTP: http://www.cof.orst.edu/cof/teach/for442/ct.htm
• Montclair State University (1995). Curriculum resource center. Critical thinking resources: An annotated bibliography. [On-line]. Available HTTP: http://www.montclair.edu/Pages/CRC/Bibliographies/CriticalThinking.html
• No author, No date. Critical Thinking is ... [On-line], April 4, 1997. Available HTTP: http://library.usask.ca/ustudy/critical/
• Sheridan, Marcia (No date). Internet education topics hotlink page. [On-line], April 4, 1997. Available HTTP: http://sun1.iusb.edu/~msherida/topics/critical.html

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50 Problem-Solving and Critical Thinking Examples

Critical thinking and problem solving are essential skills for success in the 21st century. Critical thinking is the ability to analyze information, evaluate evidence, and draw logical conclusions. Problem solving is the ability to apply critical thinking to find effective solutions to various challenges. Both skills require creativity, curiosity, and persistence. Developing critical thinking and problem solving skills can help students improve their academic performance, enhance their career prospects, and become more informed and engaged citizens.

Sanju Pradeepa

In today’s complex and fast-paced world, the ability to think critically and solve problems effectively has become a vital skill for success in all areas of life. Whether it’s navigating professional challenges, making sound decisions, or finding innovative solutions, critical thinking and problem-solving are key to overcoming obstacles and achieving desired outcomes. In this blog post, we will explore problem-solving and critical thinking examples.

Table of Contents

Developing the skills needed for critical thinking and problem solving.

It is not enough to simply recognize an issue; we must use the right tools and techniques to address it. To do this, we must learn how to define and identify the problem or task at hand, gather relevant information from reliable sources, analyze and compare data to draw conclusions, make logical connections between different ideas, generate a solution or action plan, and make a recommendation.

The first step in developing these skills is understanding what the problem or task is that needs to be addressed. This requires careful consideration of all available information in order to form an accurate picture of what needs to be done. Once the issue has been identified, gathering reliable sources of data can help further your understanding of it. Sources could include interviews with customers or stakeholders, surveys, industry reports, and analysis of customer feedback.

After collecting relevant information from reliable sources, it’s important to analyze and compare the data in order to draw meaningful conclusions about the situation at hand. This helps us better understand our options for addressing an issue by providing context for decision-making. Once you have analyzed the data you collected, making logical connections between different ideas can help you form a more complete picture of the situation and inform your potential solutions.

Once you have analyzed your options for addressing an issue based on all available data points, it’s time to generate a solution or action plan that takes into account considerations such as cost-effectiveness and feasibility. It’s also important to consider the risk factors associated with any proposed solutions in order to ensure that they are responsible before moving forward with implementation. Finally, once all the analysis has been completed, it is time to make a recommendation based on your findings, which should take into account any objectives set out by stakeholders at the beginning of this process as well as any other pertinent factors discovered throughout the analysis stage.

By following these steps carefully when faced with complex issues, one can effectively use critical thinking and problem-solving skills in order to achieve desired outcomes more efficiently than would otherwise be possible without them, while also taking responsibility for decisions made along the way.

What Does Critical Thinking Involve: 5 Essential Skill

Problem-solving and critical thinking examples.

Problem-solving and critical thinking are key skills that are highly valued in any professional setting. These skills enable individuals to analyze complex situations, make informed decisions, and find innovative solutions. Here, we present 25 examples of problem-solving and critical thinking. problem-solving scenarios to help you cultivate and enhance these skills.

Ethical dilemma: A company faces a situation where a client asks for a product that does not meet quality standards. The team must decide how to address the client’s request without compromising the company’s credibility or values.

Brainstorming session: A team needs to come up with new ideas for a marketing campaign targeting a specific demographic. Through an organized brainstorming session, they explore various approaches and analyze their potential impact.

Troubleshooting technical issues : An IT professional receives a ticket indicating a network outage. They analyze the issue, assess potential causes (hardware, software, or connectivity), and solve the problem efficiently.

Negotiation : During contract negotiations, representatives from two companies must find common ground to strike a mutually beneficial agreement, considering the needs and limitations of both parties.

Project management: A project manager identifies potential risks and develops contingency plans to address unforeseen obstacles, ensuring the project stays on track.

Decision-making under pressure: In a high-stakes situation, a medical professional must make a critical decision regarding a patient’s treatment, weighing all available information and considering potential risks.

Conflict resolution: A team encounters conflicts due to differing opinions or approaches. The team leader facilitates a discussion to reach a consensus while considering everyone’s perspectives.

Data analysis: A data scientist is presented with a large dataset and is tasked with extracting valuable insights. They apply analytical techniques to identify trends, correlations, and patterns that can inform decision-making.

Customer service: A customer service representative encounters a challenging customer complaint and must employ active listening and problem-solving skills to address the issue and provide a satisfactory resolution.

Market research : A business seeks to expand into a new market. They conduct thorough market research, analyzing consumer behavior, competitor strategies, and economic factors to make informed market-entry decisions.

Creative problem-solvin g: An engineer faces a design challenge and must think outside the box to come up with a unique and innovative solution that meets project requirements.

Change management: During a company-wide transition, managers must effectively communicate the change, address employees’ concerns, and facilitate a smooth transition process.

Crisis management: When a company faces a public relations crisis, effective critical thinking is necessary to analyze the situation, develop a response strategy, and minimize potential damage to the company’s reputation.

Cost optimization : A financial analyst identifies areas where expenses can be reduced while maintaining operational efficiency, presenting recommendations for cost savings.

Time management : An employee has multiple deadlines to meet. They assess the priority of each task, develop a plan, and allocate time accordingly to achieve optimal productivity.

Quality control: A production manager detects an increase in product defects and investigates the root causes, implementing corrective actions to enhance product quality.

Strategic planning: An executive team engages in strategic planning to define long-term goals, assess market trends, and identify growth opportunities.

Cross-functional collaboration: Multiple teams with different areas of expertise must collaborate to develop a comprehensive solution, combining their knowledge and skills.

Training and development : A manager identifies skill gaps in their team and designs training programs to enhance critical thinking, problem-solving, and decision-making abilities.

Risk assessment : A risk management professional evaluates potential risks associated with a new business venture, weighing their potential impact and developing strategies to mitigate them.

Continuous improvement: An operations manager analyzes existing processes, identifies inefficiencies, and introduces improvements to enhance productivity and customer satisfaction.

Customer needs analysis: A product development team conducts extensive research to understand customer needs and preferences, ensuring that the resulting product meets those requirements.

Crisis decision-making: A team dealing with a crisis must think quickly, assess the situation, and make timely decisions with limited information.

Marketing campaign analysis : A marketing team evaluates the success of a recent campaign, analyzing key performance indicators to understand its impact on sales and customer engagement.

Constructive feedback: A supervisor provides feedback to an employee, highlighting areas for improvement and offering constructive suggestions for growth.

Conflict resolution in a team project: Team members engaged in a project have conflicting ideas on the approach. They must engage in open dialogue, actively listen to each other’s perspectives, and reach a compromise that aligns with the project’s goals.

Crisis response in a natural disaster: Emergency responders must think critically and swiftly in responding to a natural disaster, coordinating rescue efforts, allocating resources effectively, and prioritizing the needs of affected individuals.

Product innovation : A product development team conducts market research, studies consumer trends, and uses critical thinking to create innovative products that address unmet customer needs.

Supply chain optimization: A logistics manager analyzes the supply chain to identify areas for efficiency improvement, such as reducing transportation costs, improving inventory management, or streamlining order fulfillment processes.

Business strategy formulation: A business executive assesses market dynamics, the competitive landscape, and internal capabilities to develop a robust business strategy that ensures sustainable growth and competitiveness.

Crisis communication: In the face of a public relations crisis, an organization’s spokesperson must think critically to develop and deliver a transparent, authentic, and effective communication strategy to rebuild trust and manage reputation.

Social problem-solving: A group of volunteers addresses a specific social issue, such as poverty or homelessness, by critically examining its root causes, collaborating with stakeholders, and implementing sustainable solutions for the affected population.

Problem-Solving Mindset: How to Achieve It (15 Ways)

Risk assessment in investment decision-making: An investment analyst evaluates various investment opportunities, conducting risk assessments based on market trends, financial indicators, and potential regulatory changes to make informed investment recommendations.

Environmental sustainability: An environmental scientist analyzes the impact of industrial processes on the environment, develops strategies to mitigate risks, and promotes sustainable practices within organizations and communities.

Adaptation to technological advancements : In a rapidly evolving technological landscape, professionals need critical thinking skills to adapt to new tools, software, and systems, ensuring they can effectively leverage these advancements to enhance productivity and efficiency.

Productivity improvement: An operations manager leverages critical thinking to identify productivity bottlenecks within a workflow and implement process improvements to optimize resource utilization, minimize waste, and increase overall efficiency.

Cost-benefit analysis: An organization considering a major investment or expansion opportunity conducts a thorough cost-benefit analysis, weighing potential costs against expected benefits to make an informed decision.

Human resources management : HR professionals utilize critical thinking to assess job applicants, identify skill gaps within the organization, and design training and development programs to enhance the workforce’s capabilities.

Root cause analysis: In response to a recurring problem or inefficiency, professionals apply critical thinking to identify the root cause of the issue, develop remedial actions, and prevent future occurrences.

Leadership development: Aspiring leaders undergo critical thinking exercises to enhance their decision-making abilities, develop strategic thinking skills, and foster a culture of innovation within their teams.

Brand positioning : Marketers conduct comprehensive market research and consumer behavior analysis to strategically position a brand, differentiating it from competitors and appealing to target audiences effectively.

Resource allocation: Non-profit organizations distribute limited resources efficiently, critically evaluating project proposals, considering social impact, and allocating resources to initiatives that align with their mission.

Innovating in a mature market: A company operating in a mature market seeks to innovate to maintain a competitive edge. They cultivate critical thinking skills to identify gaps, anticipate changing customer needs, and develop new strategies, products, or services accordingly.

Analyzing financial statements : Financial analysts critically assess financial statements, analyze key performance indicators, and derive insights to support financial decision-making, such as investment evaluations or budget planning.

Crisis intervention : Mental health professionals employ critical thinking and problem-solving to assess crises faced by individuals or communities, develop intervention plans, and provide support during challenging times.

Data privacy and cybersecurity : IT professionals critically evaluate existing cybersecurity measures, identify vulnerabilities, and develop strategies to protect sensitive data from threats, ensuring compliance with privacy regulations.

Process improvement : Professionals in manufacturing or service industries critically evaluate existing processes, identify inefficiencies, and implement improvements to optimize efficiency, quality, and customer satisfaction.

Multi-channel marketing strategy : Marketers employ critical thinking to design and execute effective marketing campaigns across various channels such as social media, web, print, and television, ensuring a cohesive brand experience for customers.

Peer review: Researchers critically analyze and review the work of their peers, providing constructive feedback and ensuring the accuracy, validity, and reliability of scientific studies.

Project coordination : A project manager must coordinate multiple teams and resources to ensure seamless collaboration, identify potential bottlenecks, and find solutions to keep the project on schedule.  

These examples highlight the various contexts in which problem-solving and critical-thinking skills are necessary for success. By understanding and practicing these skills, individuals can enhance their ability to navigate challenges and make sound decisions in both personal and professional endeavors.

Conclusion:

Critical thinking and problem-solving are indispensable skills that empower individuals to overcome challenges, make sound decisions, and find innovative solutions. By honing these skills, one can navigate through the complexities of modern life and achieve success in both personal and professional endeavors. Embrace the power of critical thinking and problem-solving, and unlock the door to endless possibilities and growth.

• Problem solving From Wikipedia, the free encyclopedia
• Critical thinking From Wikipedia, the free encyclopedia
• The Importance of Critical Thinking and Problem Solving Skills for Students (5 Minutes)

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Effective Learning Behavior in Problem-Based Learning: a Scoping Review

• Published: 21 April 2021
• Volume 31 , pages 1199–1211, ( 2021 )

Cite this article

• Azril Shahreez Abdul Ghani   ORCID: orcid.org/0000-0001-9130-2175 1 , 2 ,
• Ahmad Fuad Abdul Rahim   ORCID: orcid.org/0000-0001-7499-8895 2 ,
• Muhamad Saiful Bahri Yusoff   ORCID: orcid.org/0000-0002-4969-9217 2 &
• Siti Nurma Hanim Hadie   ORCID: orcid.org/0000-0001-9046-9379 3  

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Problem-based learning (PBL) emphasizes learning behavior that leads to critical thinking, problem-solving, communication, and collaborative skills in preparing students for a professional medical career. However, learning behavior that develops these skills has not been systematically described. This review aimed to unearth the elements of effective learning behavior in a PBL context, using the protocol by Arksey and O’Malley. The protocol identified the research question, selected relevant studies, charted and collected data, and collated, summarized, and reported results. We discovered three categories of elements—intrinsic empowerment, entrustment, and functional skills—proven effective in the achievement of learning outcomes in PBL.

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Introduction

Problem-based learning (PBL) is an educational approach that utilizes the principles of collaborative learning in small groups, first introduced by McMaster Medical University [ 1 ]. The shift of the higher education curriculum from traditional, lecture-based approaches to an integrated, student-centered approach was triggered by concern over the content-driven nature of medical knowledge with minimal clinical application [ 2 ]. The PBL pedagogy uses a systematic approach, starting with an authentic, real-life problem scenario as a context in which learning is not separated from practice as students collaborate and learn [ 3 ]. The tutor acts as a facilitator who guides the students’ learning, while students are required to solve the problems by discussing them with group members [ 4 ]. The essential aspect of the PBL process is the ability of the students to recognize their current knowledge, determine the gaps in their knowledge and experience, and acquire new knowledge to bridge the gaps [ 5 ]. PBL is a holistic approach that gives students an active role in their learning.

Since its inception, PBL has been used in many undergraduate and postgraduate degree programs, such as medicine [ 6 , 7 ], nursing [ 8 ], social work education [ 9 ], law [ 10 ], architecture [ 11 ], economics [ 12 ], business [ 13 ], science [ 14 ], and engineering [ 15 ]. It has also been applied in elementary and secondary education [ 16 , 17 , 18 ]. Despite its many applications, its implementation is based on a single universal workflow framework that contains three elements: problem as the initiator for learning, tutor as a facilitator in the group versions, and group work as a stimulus for collaborative interaction [ 19 ]. However, there are various versions of PBL workflow, such as the seven-step technique based on the Maastricht “seven jumps” process. The tutor’s role is to ensure the achievement of learning objectives and to assess students’ performance [ 20 , 21 ].

The PBL process revolves around four types of learning principles: constructive, self-directed, collaborative, and contextual [ 19 ]. Through the constructive learning process, the students are encouraged to think about what is already known and integrate their prior knowledge with their new understanding. This process helps the student understand the content, form a new opinion, and acquire new knowledge [ 22 ]. The PBL process encourages students to become self-directed learners who plan, monitor, and evaluate their own learning, enabling them to become lifelong learners [ 23 ]. The contextualized collaborative learning process also promotes interaction among students, who share similar responsibilities to achieve common goals relevant to the learning context [ 24 ]. By exchanging ideas and providing feedback during the learning session, the students can attain a greater understanding of the subject matter [ 25 ].

Dolmans et al. [ 19 ] pointed out two issues related to the implementation of PBL: dominant facilitators and dysfunctional PBL groups. These problems inhibit students’ self-directed learning and reduce their satisfaction level with the PBL session. A case study by Eryilmaz [ 26 ] that evaluated engineering students’ and tutors’ experience of PBL discovered that PBL increased the students’ self-confidence and improved essential skills such as problem-solving, communications, critical thinking, and collaboration. Although most of the participants in the study found PBL satisfactory, many complained about the tutor’s poor guidance and lack of preparation. Additionally, it was noted that 64% of the first-year students were unable to adapt to the PBL system because they had been accustomed to conventional learning settings and that 43% of students were not adequately prepared for the sessions and thus were minimally involved in the discussion.

In a case study by Cónsul-giribet [ 27 ], newly graduated nursing professionals reported a lack of perceived theoretical basic science knowledge at the end of their program, despite learning through PBL. The nurses perceived that this lack of knowledge might affect their expertise, identity, and professional image.

Likewise, a study by McKendree [ 28 ] reported the outcomes of a workshop that explored the strengths and weaknesses of PBL in an allied health sciences curriculum in the UK. The workshop found that problems related to PBL were mainly caused by students, the majority of whom came from conventional educational backgrounds either during high school or their first degree. They felt anxious when they were involved in PBL, concerned about “not knowing when to stop” in exploring the learning needs. Apart from a lack of basic science knowledge, the knowledge acquired during PBL sessions remains unorganized [ 29 ]. Hence, tutors must guide students in overcoming this situation by instilling appropriate insights and essential skills for the achievement of the learning outcomes [ 30 ]. It was also evident that the combination of intention and motivation to learn and desirable learning behavior determined the quality of learning outcomes [ 31 , 32 ]. However, effective learning behaviors that help develop these skills have not been systematically described. Thus, this scoping review aimed to unearth the elements of effective learning behavior in the PBL context.

Scoping Review Protocol

This scoping review was performed using a protocol by Arksey and O’Malley [ 33 ]. The protocol comprises five phases: (i) identification of research questions, (ii) identification of relevant articles, (iii) selection of relevant studies, (iv) data collection and charting, and (v) collating, summarizing, and reporting the results.

Identification of Research Questions

This scoping review was designed to unearth the elements of effective learning behavior that can be generated from learning through PBL instruction. The review aimed to answer one research question: “What are the effective learning behavior elements related to PBL?” For the purpose of the review, an operational definition of effective learning behavior was constructed, whereby it was defined as any learning behavior that is related to PBL instruction and has been shown to successfully attain the desired learning outcomes (i.e., cognitive, skill, or affective)—either quantitatively or qualitatively—in any intervention conducted in higher education institutions.

The positive outcome variables include student viewpoint or perception, student learning experience and performance, lecturer viewpoint and expert judgment, and other indirect variables that may be important indicators of successful PBL learning (i.e., attendance to PBL session, participation in PBL activity, number of interactions in PBL activity, and improvement in communication skills in PBL).

Identification of Relevant Articles

An extensive literature search was conducted on articles published in English between 2015 and 2019. Three databases—Google Scholar, Scopus, and PubMed—were used for the literature search. Seven search terms with the Boolean combination were used, whereby the keywords were identified from the Medical Subject Headings (MeSH) and Education Resources Information Center (ERIC) databases. The search terms were tested and refined with multiple test searches. The final search terms with the Boolean operation were as follows: “problem-based learning” AND (“learning behavior” OR “learning behaviour”) AND (student OR “medical students” OR undergraduate OR “medical education”).

Selection of Relevant Articles

The articles from the three databases were exported manually into Microsoft Excel. The duplicates were removed, and the remaining articles were reviewed based on the inclusion and exclusion criteria. These criteria were tested on titles and abstracts to ensure their robustness in capturing the articles related to learning behavior in PBL. The shortlisted articles were reviewed by two independent researchers, and a consensus was reached either to accept or reject each article based on the set criteria. When a disagreement occurred between the two reviewers, the particular article was re-evaluated independently by the third and fourth researchers (M.S.B.Y and A.F.A.R), who have vast experience in conducting qualitative research. The sets of criteria for selecting abstracts and final articles were developed. The inclusion and exclusion criteria are listed in Table 1 .

Data Charting

The selected final articles were reviewed, and several important data were extracted to provide an objective summary of the review. The extracted data were charted in a table, including the (i) title of the article, (ii) author(s), (iii) year of publication, (iv) aim or purpose of the study, (v) study design and method, (iv) intervention performed, and (v) study population and sample size.

Collating, Summarizing, and Reporting the Results

A content analysis was performed to identify the elements of effective learning behaviors in the literature by A.S.A.G and S.N.H.H, who have experience in conducting qualitative studies. The initial step of content analysis was to read the selected articles thoroughly to gain a general understanding of the articles and extract the elements of learning behavior which are available in the articles. Next, the elements of learning behavior that fulfil the inclusion criteria were extracted. The selected elements that were related to each other through their content or context were grouped into subtheme categories. Subsequently, the combinations of several subthemes expressing similar underlying meanings were grouped into themes. Each of the themes and subthemes was given a name, which was operationally defined based on the underlying elements. The selected themes and subthemes were presented to the independent researchers in the team (M.S.B.Y and A.F.A.R), and a consensus was reached either to accept or reformulate each of the themes and subthemes. The flow of the scoping review methods for this study is illustrated in Fig.  1 .

The flow of literature search and article selection

Literature Search

Based on the keyword search, 1750 articles were obtained. Duplicate articles that were not original articles found in different databases and resources were removed. Based on the inclusion and exclusion criteria of title selection, the eligibility of 1750 abstracts was evaluated. The articles that did not fulfil the criteria were removed, leaving 328 articles for abstract screening. A total of 284 articles were screened according to the eligibility criteria for abstract selection. Based on these criteria, 284 articles were selected and screened according to the eligibility criteria for full article selection. Fourteen articles were selected for the final review. The information about these articles is summarized in Table 2 .

Study Characteristics

The final 14 articles were published between 2015 and 2019. The majority of the studies were conducted in Western Asian countries ( n  = 4), followed by China ( n  = 3), European countries ( n  = 2), Thailand ( n  = 2), Indonesia ( n  = 1), Singapore ( n  = 1), and South Africa ( n  = 1). Apart from traditional PBL, some studies incorporated other pedagogic modalities into their PBL sessions, such as online learning, blended learning, and gamification. The majority of the studies targeted a single-profession learner group, and one study was performed on mixed interprofessional health education learners.

Results of Thematic Analysis

The thematic analysis yielded three main themes of effective learning behavior: intrinsic empowerment, entrustment, and functional skills. Intrinsic empowerment overlies four proposed subthemes: proactivity, organization, diligence, and resourcefulness. For entrustment, there were four underlying subthemes: students as assessors, students as teachers, feedback-giving, and feedback-receiving. The functional skills theme contains four subthemes: time management, digital proficiency, data management, and collaboration.

Theme 1: Intrinsic Empowerment

Intrinsic empowerment enforces student learning behavior that can facilitate the achievement of learning outcomes. By empowering the development of these behaviors, students can become lifelong learners [ 34 ]. The first element of intrinsic empowerment is proactive behavior. In PBL, the students must be proactive in analyzing problems [ 35 , 36 ] and their learning needs [ 35 , 37 ], and this can be done by integrating prior knowledge and previous experience through a brainstorming session [ 35 , 38 ]. The students must be proactive in seeking guidance to ensure they stay focused and confident [ 39 , 40 ]. Finding ways to integrate content from different disciplines [ 35 , 41 ], formulate new explanations based on known facts [ 34 , 35 , 41 ], and incorporate hands-on activity [ 35 , 39 , 42 ] during a PBL session are also proactive behaviors.

The second element identified is “being organized” which reflects the ability of students to systematically manage their roles [ 43 ], ideas, and learning needs [ 34 ]. The students also need to understand the task for each learning role in PBL, such as chairperson or leader, scribe, recorder, and reflector. This role needs to be assigned appropriately to ensure that all members take part in the discussion [ 43 ]. Similarly, when discussing ideas or learning needs, the students need to follow the steps in the PBL process and organize and prioritize the information to ensure that the issues are discussed systematically and all aspects of the problems are covered accordingly [ 34 , 37 ]. This team organization and systematic thought process is an effective way for students to focus, plan, and finalize their learning tasks.

The third element of intrinsic empowerment is “being diligent.” Students must consistently conduct self-revision [ 40 ] and keep track of their learning plan to ensure the achievement of their learning goal [ 4 , 40 ]. The students must also be responsible for completing any given task and ensuring good understanding prior to their presentation [ 40 ]. Appropriate actions need to be undertaken to find solutions to unsolved problems [ 40 , 44 ]. This effort will help them think critically and apply their knowledge for problem-solving.

The fourth element identified is “being resourceful.” Students should be able to acquire knowledge from different resources, which include external resources (i.e., lecture notes, textbooks, journal articles, audiovisual instructions, the Internet) [ 38 , 40 , 45 ] and internal resources (i.e., students’ prior knowledge or experience) [ 35 , 39 ]. The resources must be evidence-based, and thus should be carefully selected by evaluating their cross-references and appraising them critically [ 37 ]. Students should also be able to understand and summarize the learned materials and explain them using their own words [ 4 , 34 ]. The subthemes of the intrinsic empowerment theme are summarized in Table 3 .

Theme 2: Entrustment

Entrustment emphasizes the various roles of students in PBL that can promote effective learning. The first entrusted role identified is “student as an assessor.” This means that students evaluate their own performance in PBL [ 46 ]. The evaluation of their own performance must be based on the achievement of the learning outcomes and reflect actual understanding of the content as well as the ability to apply the learned information in problem-solving [ 46 ].

The second element identified in this review is “student as a teacher.” To ensure successful peer teaching in PBL, students need to comprehensively understand the content of the learning materials and summarize the content in an organized manner. The students should be able to explain the gist of the discussed information using their own words [ 4 , 34 ] and utilize teaching methods to cater to differences in learning styles (i.e., visual, auditory, and kinesthetic) [ 41 ]. These strategies help capture their group members’ attention and evoke interactive discussions among them.

The third element of entrustment is to “give feedback.” Students should try giving constructive feedback on individual and group performance in PBL. Feedback on individual performance must reflect the quality of the content and task presented in the PBL. Feedback on group performance should reflect the ways in which the group members communicate and complete the group task [ 47 ]. To ensure continuous constructive feedback, students should be able to generate feedback questions beforehand and immediately deliver them during the PBL sessions [ 44 , 47 ]. In addition, the feedback must include specific measures for improvement to help their peers to take appropriate action for the future [ 47 ].

The fourth element of entrustment is “receive feedback.” Students should listen carefully to the feedback given and ask questions to clarify the feedback [ 47 ]. They need to be attentive and learn to deal with negative feedback [ 47 ]. Also, if the student does not receive feedback, they should request it either from peers or teachers and ask specific questions, such as what aspects to improve and how to improve [ 47 ]. The data on the subthemes of the entrustment theme are summarized in Table 4 .

Theme 3: Functional Skills

Functional skills refer to essential skills that can help students learn independently and competently. The first element identified is time management skills. In PBL, students must know how to prioritize learning tasks according to the needs and urgency of the tasks [ 40 ]. To ensure that students can self-pace their learning, a deadline should be set for each learning task within a manageable and achievable learning schedule [ 40 ].

Furthermore, students should have digital proficiency, the ability to utilize digital devices to support learning [ 38 , 40 , 44 ]. The student needs to know how to operate basic software (e.g., Words and PowerPoints) and the basic digital tools (i.e., social media, cloud storage, simulation, and online community learning platforms) to support their learning [ 39 , 40 ]. These skills are important for peer learning activities, which may require information sharing, information retrieval, online peer discussion, and online peer feedback [ 38 , 44 ].

The third functional skill identified is data management, the ability to collect key information in the PBL trigger and analyze that information to support the solution in a problem-solving activity [ 39 ]. Students need to work either individually or in a group to collect the key information from a different trigger or case format such as text lines, an interview, an investigation, or statistical results [ 39 ]. Subsequently, students also need to analyze the information and draw conclusions based on their analysis [ 39 ].

The fourth element of functional skill is collaboration. Students need to participate equally in the PBL discussion [ 41 , 46 ]. Through discussion, confusion and queries can be addressed and resolved by listening, respecting others’ viewpoints, and responding professionally [ 35 , 39 , 43 , 44 ]. In addition, the students need to learn from each other and reflect on their performance [ 48 ]. Table 5 summarizes the data on the subthemes of the functional skills theme.

This scoping review outlines three themes of effective learning behavior elements in the PBL context: intrinsic empowerment, entrustment, and functional skills. Hence, it is evident from this review that successful PBL instruction demands students’ commitment to empower themselves with value-driven behaviors, skills, and roles.

In this review, intrinsic empowerment is viewed as enforcement of students’ internal strength in performing positive learning behaviors related to PBL. This theme requires the student to proactively engage in the learning process, organize their learning activities systematically, persevere in learning, and be intelligently resourceful. One of the elements of intrinsic empowerment is the identification and analysis of problems related to complex scenarios. This element is aligned with a study by Meyer [ 49 ], who observed students’ engagement in problem identification and clarification prior to problem-solving activities in a PBL session related to multiple engineering design. Rubenstein and colleagues [ 50 ] discovered in a semi-structured interview the importance of undergoing a problem identification process before proposing a solution during learning. It was reported that the problem identification process in PBL may enhance the attainment of learning outcomes, specifically in the domain of concept understanding [ 51 ].

The ability of the students to acquire and manage learning resources is essential for building their understanding of the learned materials and enriching discussion among team members during PBL. This is aligned with a study by Jeong and Hmelo-Silver [ 52 ], who studied the use of learning resources by students in PBL. The study concluded that in a resource-rich environment, the students need to learn how to access and understand the resources to ensure effective learning. Secondly, they need to process the content of the resources, integrate various resources, and apply them in problem-solving activities. Finally, they need to use the resources in collaborative learning activities, such as sharing and relating to peer resources.

Wong [ 53 ] documented that excellent students spent considerably more time managing academic resources than low achievers. The ability of the student to identify and utilize their internal learning resources, such as prior knowledge and experience, is also important. A study by Lee et al. [ 54 ] has shown that participants with high domain-specific prior knowledge displayed a more systematic approach and high accuracy in visual and motor reactions in solving problems compared to novice learners.

During the discussion phase in PBL, organizing ideas—e.g., arranging relevant information gathered from the learning resources into relevant categories—is essential for communicating the idea clearly [ 34 ]. This finding is in line with a typology study conducted by Larue [ 55 ] on second-year nursing students’ learning strategies during a group discussion. The study discovered that although the content presented by the student is adequate, they unable to make further progress in the group discussion until they are instructed by the tutor on how to organize the information given into a category [ 55 ].

Hence, the empowerment of student intrinsic behavior may enhance students’ learning in PBL by allowing them to make a decision in their learning objectives and instilling confidence in them to achieve goals. A study conducted by Kirk et al. [ 56 ] proved that highly empowered students obtain better grades, increase learning participation, and target higher educational aspirations.

Entrustment is the learning role given to students to be engaging and identify gaps in their learning. This theme requires the student to engage in self-assessment, prepare to teach others, give constructive feedback, and value the feedback received. One of the elements of entrustment is the ability to self-assess. In a study conducted by Mohd et al. [ 57 ] looking at the factors in PBL that can strengthen the capability of IT students, they discovered that one of the critical factors that contribute to these skills is the ability of the student to perform self-assessment in PBL. As mentioned by Daud, Kassim, and Daud [ 58 ], the self-assessment may be more reliable if the assessment is performed based on the objectives set beforehand and if the criteria of the assessment are understood by the learner. This is important to avoid the fact that the result of the self-assessment is influenced by the students’ perception of themselves rather than reflecting their true performance. However, having an assessment based on the learning objective only focuses on the immediate learning requirements in the PBL. To foster lifelong learning skills, it should also be balanced with the long-term focus of assessment, such as utilizing the assessment to foster the application of knowledge in solving real-life situations. This is aligned with the review by Boud and Falchikov [ 59 ] suggesting that students need to become assessors within the concept of participation in practice, that is, the kind that is within the context of real life and work.

The second subtheme of entrustment is “students as a teacher” in PBL. In our review, the student needs to be well prepared with the teaching materials. A cross-sectional study conducted by Charoensakulchai and colleagues discovered that student preparation is considered among the important factors in PBL success, alongside other factors such as “objective and contents,” “student assessment,” and “attitude towards group work” [ 60 ]. This is also aligned with a study conducted by Sukrajh [ 61 ] using focus group discussion on fifth-year medical students to explore their perception of preparedness before conducting peer teaching activity. In this study, the student in the focus group expressed that the preparation made them more confident in teaching others because preparing stimulated them to activate and revise prior knowledge, discover their knowledge gaps, construct new knowledge, reflect on their learning, improve their memory, inspire them to search several resources, and motivate them to learn the topics.

The next element of “student as a teacher” is using various learning styles to teach other members in the group. A study conducted by Almomani [ 62 ] showed that the most preferred learning pattern by the high school student is the visual pattern, followed by auditory pattern and then kinesthetic. However, in the university setting, Hamdani [ 63 ] discovered that students prefer a combination of the three learning styles. Anbarasi [ 64 ] also explained that incorporating teaching methods based on the student’s preferred learning style further promotes active learning among the students and significantly improved the long-term retrieval of knowledge. However, among the three learning styles group, he discovered that the kinesthetic group with the kinesthetic teaching method showed a significantly higher post-test score compared to the traditional group with the didactic teaching method, and he concluded that this is because of the involvement of more active learning activity in the kinesthetic group.

The ability of students to give constructive feedback on individual tasks is an important element in promoting student contribution in PBL because feedback from peers or teachers is needed to reassure themselves that they are on the right track in the learning process. Kamp et al. [ 65 ] performed a study on the effectiveness of midterm peer feedback on student individual cognitive, collaborative, and motivational contributions in PBL. The experimental group that received midterm peer feedback combined with goal-setting with face-to-face discussion showed an increased amount of individual contributions in PBL. Another element of effective feedback is that the feedback is given immediately after the observed behavior. Parikh and colleagues survey student feedback in PBL environments among 103 final-year medical students in five Ontario schools, including the University of Toronto, McMaster University, Queens University, the University of Ottawa, and the University of Western Ontario. They discovered that there was a dramatic difference between McMaster University and other universities in the immediacy of feedback they practiced. Seventy percent of students at McMaster reported receiving immediate feedback in PBL, compared to less than 40 percent of students from the other universities, in which most of them received feedback within one week or several weeks after the PBL had been conducted [ 66 ]. Another study, conducted among students of the International Medical University of Kuala Lumpur examining the student expectation on feedback, discovered that immediate feedback is effective if the feedback is in written form, simple but focused on the area of improvement, and delivered by a content expert. If the feedback is delivered by a content non-expert and using a model answer, it must be supplemented with teacher dialogue sessions to clarify the feedback received [ 67 ].

Requesting feedback from peers and teachers is an important element of the PBL learning environment, enabling students to discover their learning gaps and ways to fill them. This is aligned with a study conducted by de Jong and colleagues [ 68 ], who discovered that high-performing students are more motivated to seek feedback than low-performing students. The main reason for this is because high-performing students seek feedback as a tool to learn from, whereas low-performing students do so as an academic requirement. This resulted in high-performing students collecting more feedback. A study by Bose and Gijselaers [ 69 ] examined the factors that promote feedback-seeking behavior in medical residency. They discovered that feedback-seeking behavior can be promoted by providing residents with high-quality feedback to motivate them to ask for feedback for improvement.

By assigning an active role to students as teachers, assessors, and feedback providers, teachers give them the ownership and responsibility to craft their learning. The learner will then learn the skills to monitor and reflect on their learning to achieve academic success. Furthermore, an active role encourages students to be evaluative experts in their own learning, and promoting deep learning [ 70 ].

Functional skills refer to essential abilities for competently performing a task in PBL. This theme requires the student to organize and plan time for specific learning tasks, be digitally literate, use data effectively to support problem-solving, and work together efficiently to achieve agreed objectives. One of the elements in this theme is to have a schedule of learning tasks with deadlines. In a study conducted by Tadjer and colleagues [ 71 ], they discovered that setting deadlines with a restricted time period in a group activity improved students’ cognitive abilities and soft skills. Although the deadline may initially cause anxiety, coping with it encourages students to become more creative and energetic in performing various learning strategies [ 72 , 73 ]. Ballard et al. [ 74 ] reported that students tend to work harder to complete learning tasks if they face multiple deadlines.

The students also need to be digitally literate—i.e., able to demonstrate the use of technological devices and tools in PBL. Taradi et al. [ 75 ] discovered that incorporating technology in learning—blending web technology with PBL—removes time and place barriers in the creation of a collaborative environment. It was found that students who participated in web discussions achieved a significantly higher mean grade on a physiology final examination than those who used traditional methods. Also, the incorporation of an online platform in PBL can facilitate students to develop investigation and inquiry skills with high-level cognitive thought processes, which is crucial to successful problem-solving [ 76 ].

In PBL, students need to work collaboratively with their peers to solve problems. A study by Hidayati et al. [ 77 ] demonstrated that effective collaborative skills improve cognitive learning outcomes and problem-solving ability among students who undergo PBL integrated with digital mind maps. To ensure successful collaborative learning in PBL, professional communication among students is pertinent. Research by Zheng and Huang [ 78 ] has proven that co-regulation (i.e., warm and responsive communication that provides support to peers) improved collaborative effort and group performance among undergraduate and master’s students majoring in education and psychology. This is also in line with a study by Maraj and colleagues [ 79 ], which showed the strong team interaction within the PBL group leads to a high level of team efficacy and academic self-efficacy. Moreover, strengthening communication competence, such as by developing negotiation skills among partners during discussion sessions, improves student scores [ 80 ].

PBL also includes opportunities for students to learn from each other (i.e., peer learning). A study by Maraj et al. [ 79 ] discovered that the majority of the students in their study perceived improvement in their understanding of the learned subject when they learned from each other. Another study by Lyonga [ 81 ] documented the successful formation of cohesive group learning, where students could express and share their ideas with their friends and help each other. It was suggested that each student should be paired with a more knowledgeable student who has mastered certain learning components to promote purposeful structured learning within the group.

From this scoping review, it is clear that functional skills equip the students with abilities and knowledge needed for successful PBL. Studies have shown that strong time management skills, digital literacy, data management, and collaborative skills lead to positive academic achievement [ 77 , 82 , 83 ].

Limitation of the Study

This scoping review is aimed to capture the recent effective learning behavior in problem-based learning; therefore, the literature before 2015 was not included. Without denying the importance of publication before 2015, we are relying on Okoli and Schabram [ 84 ] who highlighted the impossibility of retrieving all the published articles when conducting a literature search. Based on this ground, we decided to focus on the time frame between 2015 and 2019, which is aligned with the concepts of study maturity (i.e., the more mature the field, the higher the published articles and therefore more topics were investigated) by Kraus et al. [ 85 ]. In fact, it was noted that within this time frame, a significant number of articles have been found as relevant to PBL with the recent discovery of effective learning behavior. Nevertheless, our time frame did not include the timing of the coronavirus disease 19 (COVID-19) pandemic outbreak, which began at the end of 2019. Hence, we might miss some important elements of learning behavior that are required for the successful implementation of PBL during the COVID-19 pandemic.

Surprisingly, the results obtained from this study are also applicable for the PBL sessions administration during the COVID-19 pandemic situation as one of the functional skills identified is digital proficiency. This skill is indeed important for the successful implementation of online PBL session.

This review identified the essential learning behaviors required for effective PBL in higher education and clustered them into three main themes: (i) intrinsic empowerment, (ii) entrustment, and (iii) functional skills. These learning behaviors must coexist to ensure the achievement of desired learning outcomes. In fact, the findings of this study indicated two important implications for future practice. Firstly, the identified learning behaviors can be incorporated as functional elements in the PBL framework and implementation. Secondly, the learning behaviors change and adaption can be considered to be a new domain of formative assessment related to PBL. It is noteworthy to highlight that these learning behaviors could help in fostering the development of lifelong skills for future workplace challenges. Nevertheless, considerably more work should be carried out to design a solid guideline on how to systematically adopt the learning behaviors in PBL sessions, especially during this COVID-19 pandemic situation.

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This study was supported by Postgraduate Incentive Grant-PhD (GIPS-PhD, grant number: 311/PPSP/4404803).

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Ghani, A.S.A., Rahim, A.F.A., Yusoff, M.S.B. et al. Effective Learning Behavior in Problem-Based Learning: a Scoping Review. Med.Sci.Educ. 31 , 1199–1211 (2021). https://doi.org/10.1007/s40670-021-01292-0

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Analytical Thinking Interview Questions and Answers

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Analytical Thinking is more than just a buzzword in the job market—it's a vital skill that employers seek in candidates across industries. Be it a role in finance, marketing, engineering, or any other field: your ability to analyse information and draw meaningful conclusions can set you apart from the competition. So, if you are considering appearing for an interview, it’s better to prepare some interview questions beforehand. In this blog, we will provide you with the most asked Analytical Thinking Interview Questions and Answers, as well as tips on how to ace interviews. 

Table of Contents 

1) Situational Analytical Thinking Interview Questions and Answers 

2) Behavioural Analytical Thinking Interview Questions and Answers 

3) Analytical Thinking Interview Questions and Answers on Problem-solving 

4) Tips on how to ace your Analytical Thinking Interview 

5) Conclusion   

Situational Analytical Thinking Interview Questions and Answers

Firstly, let’s look at the most asked situational Analytical Thinking Interview Questions and Answers:

Describe a situation where you had to analyse complex data to solve a problem.

Your response could take the form of: “In my previous role as a Market Analyst, I encountered a challenge with inconsistent sales data compared to market trends. I examined  the data, utilised tools like Excel and data visualisation software, and pinpointed an underperforming product line. By adjusting our marketing strategy based on the analysis, we achieved a notable 15% sales increase in three months.” 

Tell me about a time when you had to make a decision based on incomplete information.

Feel free to provide your answer as: “While working as a Project Manager, a team member unexpectedly left, creating gaps in our project plan. I quickly assessed available resources, prioritised crucial tasks, and transparently communicated with stakeholders. Despite incomplete information, we successfully met project deadlines.” 

Can you describe a scenario in which you had to analyse a problem from multiple angles before arriving at a solution?

Your reply might follow the structure of: “In a cross-functional collaboration, a software issue arose. I brought together the development and customer support teams, examined user journey and error logs, and discovered a coding glitch compounded by a user interface (UI) design flaw. Addressing both aspects led to a comprehensive solution.” 

Share an example of a situation where you were required to identify underlying causes of a problem before proposing a solution.

You could shape your answer along the lines of: “As a Quality Assurance Engineer, I confronted inconsistent manufacturing results. Through rigorous data analysis, I traced the issue to a specific raw material batch. By addressing this root cause, we not only resolved the immediate problem but also enhanced the entire production process.” 

Describe a time when you were faced with a complex project with multiple intertwined components. How did you approach it?

Your response could take the form of: “During a product launch, I managed a multifaceted project by meticulously planning tasks and timelines, coordinating cross-functional teams, and maintaining open lines of communication. This approach ensured a smooth and timely launch that surpassed expectations.” 

Imagine if your team member has a solution to a problem, but your manager has a different approach. How would you handle helping your friend if they came for your advice?

Answer: You can frame your answer in a balanced way by including the following: “In such a situation, I would follow a balanced approach. I'd empathise with my team member and acknowledge their perspective, validating their ideas. Then, I would engage in open and honest communication, encouraging them to share their solution with our manager.

Moreover,  I'd emphasise the importance of teamwork and collaboration, explaining that combining both perspectives might lead to a more comprehensive solution. I'd offer to support my team member in presenting their idea to our manager, highlighting its potential benefits. Ultimately, my goal would be to facilitate effective communication between my team member and our manager, fostering a positive and collaborative work environment. This approach ensures that both viewpoints are considered, and the best solution can be reached.”

Behavioural Analytical Thinking Interview Questions and Answers

Now, let’s look at some of the most asked behavioural Analytical Thinking questions for interview, as well as their answers:

Give an example of a project where you identified key trends and insights.

 Your reply may adopt the style of: “In my role as a Marketing Analyst, I conducted a campaign analysis for a new product launch. By examining customer engagement data, I observed a significant uptick in online interactions from a specific demographic. Further analysis revealed that this group was drawn to the product's sustainability features. Utilising this insight, we tailored subsequent marketing efforts to highlight these eco-friendly aspects, resulting in a 20% increase in sales within two months.” 

Describe a scenario where you proposed a creative solution to a recurring problem.

You might consider framing your response as: “At my previous company, we consistently faced supply chain delays. I suggested implementing an automated tracking system that would provide real-time updates on shipments. After conducting thorough research and presenting the proposal to management, the system was adopted. This solution not only reduced delays by 30%, but it also enhanced transparency and improved overall efficiency.” 

Can you provide an example of a time when you had to analyse a situation quickly to make an important decision?

Share an instance where you successfully tackled a multifaceted problem by breaking it down into manageable parts., describe a situation where you used analytical thinking to turn a negative situation into a positive outcome..

Your response could take the form of: “In a customer-facing role, a client expressed dissatisfaction with our service. Instead of solely addressing the immediate issue, I analysed their past interactions and identified recurring pain points. I proposed a personalised solution that addressed these concerns. The client was impressed with our proactive approach, and their subsequent positive feedback demonstrated how Analytical Thinking can transform dissatisfied customers into loyal advocates.” 

Unlock your potential with our Decision-Making Skills Training - empower your choices and lead with confidence! 

Analytical Thinking Interview Questions and Answers on Problem-solving

It's time to explore some ofthe most asked Analytical Thinking Interview Questions on problem-solving as well as their sample answers:

How would you approach solving a problem with multiple possible solutions?

You might consider framing your response as: “When faced with a problem offering multiple solutions, I would begin by thoroughly understanding the problem's nuances and potential outcomes. Next, I would gather relevant data and analyse each solution's feasibility, considering factors like resources, timeline, and potential risks. By evaluating the pros and cons for each option, I can make an informed decision that aligns with the overarching goals and constraints.” 

Walk me through your process of breaking down a complex issue into manageable parts.

Your reply might follow the structure of: “When tackling a complex issue, my first step is to deconstruct it into its fundamental components. I identify the key aspects, dependencies, and potential challenges. From there, I prioritise the components based on their impact and interconnections. Breaking the problem down into smaller parts allows me to address each aspect systematically, preventing overwhelm and ensuring comprehensive problem-solving.” 

Can you share an example of a time when you implemented a solution that required both Analytical Thinking and creativity?

Describe a scenario where you encountered a roadblock during a project. how did you overcome it using analytical thinking.

You might consider framing your response as: “During a Software Development project, we encountered a critical bug just before the scheduled release. I initiated a root cause analysis, tracing the bug to a specific section of the code. I analysed logs, reviewed recent code changes, and consulted with team members to pinpoint the issue's source. Using this analytical approach, we were able to develop a precise fix, ensuring the release remained on schedule.” 

Can you provide an example of a time when you had to balance short-term problem-solving with long-term strategic thinking?

Your response could take the form of: “In a Strategic Planning role, I faced an urgent budget shortfall that threatened a high-priority project. While I needed a quick solution, I also recognised the importance of maintaining a long-term perspective.” 

Continue by saying, “I conducted a detailed analysis of our budget allocation, identified non-essential expenditures, and proposed temporary adjustments to secure project funding. This balance between immediate problem-solving and strategic thinking allowed us to overcome the crisis without compromising our future plans.”   

How do you weigh risks when making a decision?

You may answer the above question something like this: “I weigh risks when making decisions through a structured approach. First, I assess the decision's potential impact on our objectives and evaluate possible outcomes. I consider internal and external factors that influence success. I also gather input from team members and rely on data and research for insights. I use historical data to gauge risk likelihood.”

You can also add the following to your answer: “Additionally, I develop risk mitigation strategies, including contingency plans and performance indicators to monitor progress. This approach ensures well-informed, goal-aligned decisions that minimise potential setbacks.”  

What metrics do you regularly track (e.g., conversion rates, number of new customers, expenses)? What information do you research, and how do you use it?

Your answer may be framed along the following lines: “I regularly employ Customer Relationship Management (CRM) software to monitor customer interactions, track the progression of leads through the sales funnel, and measure conversion rates. This data provides insights into our sales team's performance, identifies areas for improvement, and guides our strategy to optimise lead conversion and revenue generation.”

Unlock your creative potential and enhance your Analytical Thinking skills with our comprehensive Creative and Analytical Thinking Training ! 

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