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The Importance of Critical Thinking Skills in Research

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Why is Critical Thinking Important: A Disruptive Force

Research anxiety seems to be taking an increasingly dominant role in the world of academic research. The pressure to publish or perish can warp your focus into thinking that the only good research is publishable research!

Today, your role as the researcher appears to take a back seat to the perceived value of the topic and the extent to which the results of the study will be cited around the world. Due to financial pressures and a growing tendency of risk aversion, studies are increasingly going down the path of applied research rather than basic or pure research . The potential for breakthroughs is being deliberately limited to incremental contributions from researchers who are forced to worry more about job security and pleasing their paymasters than about making a significant contribution to their field.

A Slow Decline

So what lead the researchers to their love of science and scientific research in the first place? The answer is critical thinking skills. The more that academic research becomes governed by policies outside of the research process, the less opportunity there will be for researchers to exercise such skills.

True research demands new ideas , perspectives, and arguments based on willingness and confidence to revisit and directly challenge existing schools of thought and established positions on theories and accepted codes of practice. Success comes from a recursive approach to the research question with an iterative refinement based on constant reflection and revision.

The importance of critical thinking skills in research is therefore huge, without which researchers may even lack the confidence to challenge their own assumptions.

A Misunderstood Skill

Critical thinking is widely recognized as a core competency and as a precursor to research. Employers value it as a requirement for every position they post, and every survey of potential employers for graduates in local markets rate the skill as their number one concern.

Related: Do you have questions on research idea or manuscript drafting? Get personalized answers on the FREE Q&A Forum!

When asked to clarify what critical thinking means to them, employers will use such phrases as “the ability to think independently,” or “the ability to think on their feet,” or “to show some initiative and resolve a problem without direct supervision.” These are all valuable skills, but how do you teach them?

For higher education institutions in particular, when you are being assessed against dropout, graduation, and job placement rates, where does a course in critical thinking skills fit into the mix? Student Success courses as a precursor to your first undergraduate course will help students to navigate the campus and whatever online resources are available to them (including the tutoring center), but that doesn’t equate to raising critical thinking competencies.

The Dependent Generation

As education becomes increasingly commoditized and broken-down into components that can be delivered online for maximum productivity and profitability, we run the risk of devaluing academic discourse and independent thought. Larger class sizes preclude substantive debate, and the more that content is broken into sound bites that can be tested in multiple-choice questions, the less requirement there will be for original thought.

Academic journals value citation above all else, and so content is steered towards the type of articles that will achieve high citation volume. As such, students and researchers will perpetuate such misuse by ensuring that their papers include only highly cited works. And the objective of high citation volume is achieved.

We expand the body of knowledge in any field by challenging the status quo. Denying the veracity of commonly accepted “facts” or playing devil’s advocate with established rules supports a necessary insurgency that drives future research. If we do not continue to emphasize the need for critical thinking skills to preserve such rebellion, academic research may begin to slowly fade away.

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Chapter 2 Thinking Like a Researcher

Conducting good research requires first retraining your brain to think like a researcher.

This requires visualizing the abstract from actual observations, mentally “connecting the dots” to identify hidden concepts and patterns, and synthesizing those patterns into generalizable laws and theories that apply to other contexts beyond the domain of the initial observations. Research involves constantly moving back and forth from an empirical plane where observations are conducted to a theoretical plane where these observations are abstracted into generalizable laws and theories. This is a skill that takes many years to develop, is not something that is taught in graduate or doctoral programs or acquired in industry training, and is by far the biggest deficit amongst Ph.D. students. Some of the mental abstractions needed to think like a researcher include unit of analysis, constructs, hypotheses, operationalization, theories, models, induction, deduction, and so forth, which we will examine in this chapter.

Unit of Analysis

One of the first decisions in any social science research is the unit of analysis of a scientific study. The unit of analysis refers to the person, collective, or object that is the target of the investigation. Typical unit of analysis include individuals, groups, organizations, countries, technologies, objects, and such. For instance, if we are interested in studying people’s shopping behavior, their learning outcomes, or their attitudes to new technologies, then the unit of analysis is the individual . If we want to study characteristics of street gangs or teamwork in organizations, then the unit of analysis is the group . If the goal of research is to understand how firms can improve profitability or make good executive decisions, then the unit of analysis is the firm . In this case, even though decisions are made by individuals in these firms, these individuals are presumed to represent their firm’s decision rather than their personal decisions. If research is directed at understanding differences in national cultures, then the unit of analysis becomes a country . Even inanimate objects can serve as units of analysis. For instance, if a researcher is interested in understanding how to make web pages more attractive to its users, then the unit of analysis is a web page (and not users). If we wish to study how knowledge transfer occurs between two firms, then our unit of analysis becomes the dyad (the combination of firms that is sending and receiving knowledge).

Understanding the units of analysis can sometimes be fairly complex. For instance, if we wish to study why certain neighborhoods have high crime rates, then our unit of analysis becomes the neighborhood , and not crimes or criminals committing such crimes. This is because the object of our inquiry is the neighborhood and not criminals. However, if we wish to compare different types of crimes in different neighborhoods, such as homicide, robbery, assault, and so forth, our unit of analysis becomes the crime . If we wish to study why criminals engage in illegal activities, then the unit of analysis becomes the individual (i.e., the criminal). Like, if we want to study why some innovations are more successful than others, then our unit of analysis is an innovation . However, if we wish to study how some organizations innovate more consistently than others, then the unit of analysis is the organization . Hence, two related research questions within the same research study may have two entirely different units of analysis.

Understanding the unit of analysis is important because it shapes what type of data you should collect for your study and who you collect it from. If your unit of analysis is a web page, you should be collecting data about web pages from actual web pages, and not surveying people about how they use web pages. If your unit of analysis is the organization, then you should be measuring organizational-level variables such as organizational size, revenues, hierarchy, or absorptive capacity. This data may come from a variety of sources such as financial records or surveys of Chief Executive Officers (CEO), who are presumed to be representing their organization (rather than themselves). Some variables such as CEO pay may seem like individual level variables, but in fact, it can also be an organizational level variable because each organization has only one CEO pay at any time. Sometimes, it is possible to collect data from a lower level of analysis and aggregate that data to a higher level of analysis. For instance, in order to study teamwork in organizations, you can survey individual team members in different organizational teams, and average their individual scores to create a composite team-level score for team-level variables like cohesion and conflict. We will examine the notion of “variables” in greater depth in the next section.

Concepts, Constructs, and Variables

We discussed in Chapter 1 that although research can be exploratory, descriptive, or explanatory, most scientific research tend to be of the explanatory type in that they search for potential explanations of observed natural or social phenomena. Explanations require development of concepts or generalizable properties or characteristics associated with objects, events, or people. While objects such as a person, a firm, or a car are not concepts, their specific characteristics or behavior such as a person’s attitude toward immigrants, a firm’s capacity for innovation, and a car’s weight can be viewed as concepts.

Knowingly or unknowingly, we use different kinds of concepts in our everyday conversations. Some of these concepts have been developed over time through our shared language. Sometimes, we borrow concepts from other disciplines or languages to explain a phenomenon of interest. For instance, the idea of gravitation borrowed from physics can be used in business to describe why people tend to “gravitate” to their preferred shopping destinations. Likewise, the concept of distance can be used to explain the degree of social separation between two otherwise collocated individuals. Sometimes, we create our own concepts to describe a unique characteristic not described in prior research. For instance, technostress is a new concept referring to the mental stress one may face when asked to learn a new technology.

Concepts may also have progressive levels of abstraction. Some concepts such as a person’s weight are precise and objective, while other concepts such as a person’s personality may be more abstract and difficult to visualize. A construct is an abstract concept that is specifically chosen (or “created”) to explain a given phenomenon. A construct may be a simple concept, such as a person’s weight , or a combination of a set of related concepts such as a person’s communication skill , which may consist of several underlying concepts such as the person’s vocabulary, syntax , and spelling . The former instance (weight) is a unidimensional construct , while the latter (communication skill) is a multi-dimensional construct (i.e., it consists of multiple underlying concepts). The distinction between constructs and concepts are clearer in multi-dimensional constructs, where the higher order abstraction is called a construct and the lower order abstractions are called concepts. However, this distinction tends to blur in the case of unidimensional constructs.

Constructs used for scientific research must have precise and clear definitions that others can use to understand exactly what it means and what it does not mean. For instance, a seemingly simple construct such as income may refer to monthly or annual income, before-tax or after-tax income, and personal or family income, and is therefore neither precise nor clear. There are two types of definitions: dictionary definitions and operational definitions. In the more familiar dictionary definition, a construct is often defined in terms of a synonym. For instance, attitude may be defined as a disposition, a feeling, or an affect, and affect in turn is defined as an attitude. Such definitions of a circular nature are not particularly useful in scientific research for elaborating the meaning and content of that construct. Scientific research requires operational definitions that define constructs in terms of how they will be empirically measured. For instance, the operational definition of a construct such as temperature must specify whether we plan to measure temperature in Celsius, Fahrenheit, or Kelvin scale. A construct such as income should be defined in terms of whether we are interested in monthly or annual income, before-tax or after-tax income, and personal or family income. One can imagine that constructs such as learning , personality , and intelligence can be quite hard to define operationally.

Theoretical plan with construct A and a proposition that leads to construct B, then the empirical plane with the independent variable leading to a hypothesis and a dependent variable.

Figure 2.1. The theoretical and empirical planes of research

A term frequently associated with, and sometimes used interchangeably with, a construct is a variable. Etymologically speaking, a variable is a quantity that can vary (e.g., from low to high, negative to positive, etc.), in contrast to constants that do not vary (i.e., remain constant). However, in scientific research, a variable is a measurable representation of an abstract construct. As abstract entities, constructs are not directly measurable, and hence, we look for proxy measures called variables. For instance, a person’s intelligence is often measured as his or her IQ (intelligence quotient) score , which is an index generated from an analytical and pattern-matching test administered to people. In this case, intelligence is a construct, and IQ score is a variable that measures the intelligence construct. Whether IQ scores truly measures one’s intelligence is anyone’s guess (though many believe that they do), and depending on whether how well it measures intelligence, the IQ score may be a good or a poor measure of the intelligence construct. As shown in Figure 2.1, scientific research proceeds along two planes: a theoretical plane and an empirical plane. Constructs are conceptualized at the theoretical (abstract) plane, while variables are operationalized and measured at the empirical (observational) plane. Thinking like a researcher implies the ability to move back and forth between these two planes.

Depending on their intended use, variables may be classified as independent, dependent, moderating, mediating, or control variables. Variables that explain other variables are called independent variables , those that are explained by other variables are dependent variables , those that are explained by independent variables while also explaining dependent variables are mediating variables (or intermediate variables), and those that influence the relationship between independent and dependent variables are called moderating variables . As an example, if we state that higher intelligence causes improved learning among students, then intelligence is an independent variable and learning is a dependent variable. There may be other extraneous variables that are not pertinent to explaining a given dependent variable, but may have some impact on the dependent variable. These variables must be controlled for in a scientific study, and are therefore called control variables .

Intelligence (independent variable) then effort (moderating variable) lead to academic achievement (mediating variable), then earning potential (dependent variable).

Figure 2.2. A nomological network of constructs

To understand the differences between these different variable types, consider the example shown in Figure 2.2. If we believe that intelligence influences (or explains) students’ academic achievement, then a measure of intelligence such as an IQ score is an independent variable, while a measure of academic success such as grade point average is a dependent variable. If we believe that the effect of intelligence on academic achievement also depends on the effort invested by the student in the learning process (i.e., between two equally intelligent students, the student who puts is more effort achieves higher academic achievement than one who puts in less effort), then effort becomes a moderating variable. Incidentally, one may also view effort as an independent variable and intelligence as a moderating variable. If academic achievement is viewed as an intermediate step to higher earning potential, then earning potential becomes the dependent variable for the independent variable academic achievement , and academic achievement becomes the mediating variable in the relationship between intelligence and earning potential. Hence, variable are defined as an independent, dependent, moderating, or mediating variable based on their nature of association with each other. The overall network of relationships between a set of related constructs is called a nomological network (see Figure 2.2). Thinking like a researcher requires not only being able to abstract constructs from observations, but also being able to mentally visualize a nomological network linking these abstract constructs.

Propositions and Hypotheses

Figure 2.2 shows how theoretical constructs such as intelligence, effort, academic achievement, and earning potential are related to each other in a nomological network. Each of these relationships is called a proposition. In seeking explanations to a given phenomenon or behavior, it is not adequate just to identify key concepts and constructs underlying the target phenomenon or behavior. We must also identify and state patterns of relationships between these constructs. Such patterns of relationships are called propositions. A proposition is a tentative and conjectural relationship between constructs that is stated in a declarative form. An example of a proposition is: “An increase in student intelligence causes an increase in their academic achievement.” This declarative statement does not have to be true, but must be empirically testable using data, so that we can judge whether it is true or false. Propositions are generally derived based on logic (deduction) or empirical observations (induction).

Because propositions are associations between abstract constructs, they cannot be tested directly. Instead, they are tested indirectly by examining the relationship between corresponding measures (variables) of those constructs. The empirical formulation of propositions, stated as relationships between variables, is called hypotheses (see Figure 2.1). Since IQ scores and grade point average are operational measures of intelligence and academic achievement respectively, the above proposition can be specified in form of the hypothesis: “An increase in students’ IQ score causes an increase in their grade point average.” Propositions are specified in the theoretical plane, while hypotheses are specified in the empirical plane. Hence, hypotheses are empirically testable using observed data, and may be rejected if not supported by empirical observations. Of course, the goal of hypothesis testing is to infer whether the corresponding proposition is valid.

Hypotheses can be strong or weak. “Students’ IQ scores are related to their academic achievement” is an example of a weak hypothesis, since it indicates neither the directionality of the hypothesis (i.e., whether the relationship is positive or negative), nor its causality (i.e., whether intelligence causes academic achievement or academic achievement causes intelligence). A stronger hypothesis is “students’ IQ scores are positively related to their academic achievement”, which indicates the directionality but not the causality. A still better hypothesis is “students’ IQ scores have positive effects on their academic achievement”, which specifies both the directionality and the causality (i.e., intelligence causes academic achievement, and not the reverse). The signs in Figure 2.2 indicate the directionality of the respective hypotheses.

Also note that scientific hypotheses should clearly specify independent and dependent variables. In the hypothesis, “students’ IQ scores have positive effects on their academic achievement,” it is clear that intelligence is the independent variable (the “cause”) and academic achievement is the dependent variable (the “effect”). Further, it is also clear that this hypothesis can be evaluated as either true (if higher intelligence leads to higher academic achievement) or false (if higher intelligence has no effect on or leads to lower academic achievement). Later on in this book, we will examine how to empirically test such cause-effect relationships. Statements such as “students are generally intelligent” or “all students can achieve academic success” are not scientific hypotheses because they do not specify independent and dependent variables, nor do they specify a directional relationship that can be evaluated as true or false.

Theories and Models

A theory is a set of systematically interrelated constructs and propositions intended to explain and predict a phenomenon or behavior of interest, within certain boundary conditions and assumptions. Essentially, a theory is a systemic collection of related theoretical propositions. While propositions generally connect two or three constructs, theories represent a system of multiple constructs and propositions. Hence, theories can be substantially more complex and abstract and of a larger scope than propositions or hypotheses.

I must note here that people not familiar with scientific research often view a theory as a speculation or the opposite of fact . For instance, people often say that teachers need to be less theoretical and more practical or factual in their classroom teaching. However, practice or fact are not opposites of theory, but in a scientific sense, are essential components needed to test the validity of a theory. A good scientific theory should be well supported using observed facts and should also have practical value, while a poorly defined theory tends to be lacking in these dimensions. Famous organizational research Kurt Lewin once said, “Theory without practice is sterile; practice without theory is blind.” Hence, both theory and facts (or practice) are essential for scientific research.

Theories provide explanations of social or natural phenomenon. As emphasized in Chapter 1, these explanations may be good or poor. Hence, there may be good or poor theories. Chapter 3 describes some criteria that can be used to evaluate how good a theory really is. Nevertheless, it is important for researchers to understand that theory is not “truth,” there is nothing sacrosanct about any theory, and theories should not be accepted just because they were proposed by someone. In the course of scientific progress, poorer theories are eventually replaced by better theories with higher explanatory power. The essential challenge for researchers is to build better and more comprehensive theories that can explain a target phenomenon better than prior theories.

A term often used in conjunction with theory is a model. A model is a representation of all or part of a system that is constructed to study that system (e.g., how the system works or what triggers the system). While a theory tries to explain a phenomenon, a model tries to represent a phenomenon. Models are often used by decision makers to make important decisions based on a given set of inputs. For instance, marketing managers may use models to decide how much money to spend on advertising for different product lines based on parameters such as prior year’s advertising expenses, sales , market growth, and competing products. Likewise, weather forecasters can use models to predict future weather patterns based on parameters such as wind speeds, wind direction, temperature, and humidity. While these models are useful, they may not necessarily explain advertising expenditure or weather forecasts. Models may be of different kinds, such as mathematical models, network models, and path models. Models can also be descriptive, predictive, or normative. Descriptive models are frequently used for representing complex systems, for visualizing variables and relationships in such systems. An advertising expenditure model may be a descriptive model. Predictive models (e.g., a regression model) allow forecast of future events. Weather forecasting models are predictive models. Normative models are used to guide our activities along commonly accepted norms or practices. Models may also be static if it represents the state of a system at one point in time, or dynamic, if it represents a system’s evolution over time.

The process of theory or model development may involve inductive and deductive reasoning. Recall from Chapter 1 that deduction is the process of drawing conclusions about a phenomenon or behavior based on theoretical or logical reasons and an initial set of premises. As an example, if a certain bank enforces a strict code of ethics for its employees (Premise 1) and Jamie is an employee at that bank (Premise 2), then Jamie can be trusted to follow ethical practices (Conclusion). In deduction, the conclusions must be true if the initial premises and reasons are correct.

In contrast, induction is the process of drawing conclusions based on facts or observed evidence. For instance, if a firm spent a lot of money on a promotional campaign (Observation 1), but the sales did not increase (Observation 2), then possibly the promotion campaign was poorly executed (Conclusion). However, there may be rival explanations for poor sales, such as economic recession or the emergence of a competing product or brand or perhaps a supply chain problem. Inductive conclusions are therefore only a hypothesis, and may be disproven. Deductive conclusions generally tend to be stronger than inductive conclusions, but a deductive conclusion based on an incorrect premise is also incorrect.

As shown in Figure 2.3, inductive and deductive reasoning go hand in hand in theory and model building. Induction occurs when we observe a fact and ask, “Why is this happening?”

In answering this question, we advance one or more tentative explanations (hypotheses). We then use deduction to narrow down the tentative explanations to the most plausible explanation based on logic and reasonable premises (based on our understanding of the phenomenon under study). Researchers must be able to move back and forth between inductive and deductive reasoning if they are to post extensions or modifications to a given model or theory, or built better ones, which are the essence of scientific research.

Emperical observations and theory/logic both lead to inductive and deductive reasoning which leads to preliminary conclusions and then the final model.

Figure 2.3. The model-building process

  • Social Science Research: Principles, Methods, and Practices. Authored by : Anol Bhattacherjee. Provided by : University of South Florida. Located at : http://scholarcommons.usf.edu/oa_textbooks/3/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

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  • What Is Critical Thinking? | Definition & Examples

What Is Critical Thinking? | Definition & Examples

Published on May 30, 2022 by Eoghan Ryan . Revised on May 31, 2023.

Critical thinking is the ability to effectively analyze information and form a judgment .

To think critically, you must be aware of your own biases and assumptions when encountering information, and apply consistent standards when evaluating sources .

Critical thinking skills help you to:

  • Identify credible sources
  • Evaluate and respond to arguments
  • Assess alternative viewpoints
  • Test hypotheses against relevant criteria

Table of contents

Why is critical thinking important, critical thinking examples, how to think critically, other interesting articles, frequently asked questions about critical thinking.

Critical thinking is important for making judgments about sources of information and forming your own arguments. It emphasizes a rational, objective, and self-aware approach that can help you to identify credible sources and strengthen your conclusions.

Critical thinking is important in all disciplines and throughout all stages of the research process . The types of evidence used in the sciences and in the humanities may differ, but critical thinking skills are relevant to both.

In academic writing , critical thinking can help you to determine whether a source:

  • Is free from research bias
  • Provides evidence to support its research findings
  • Considers alternative viewpoints

Outside of academia, critical thinking goes hand in hand with information literacy to help you form opinions rationally and engage independently and critically with popular media.

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Critical thinking can help you to identify reliable sources of information that you can cite in your research paper . It can also guide your own research methods and inform your own arguments.

Outside of academia, critical thinking can help you to be aware of both your own and others’ biases and assumptions.

Academic examples

However, when you compare the findings of the study with other current research, you determine that the results seem improbable. You analyze the paper again, consulting the sources it cites.

You notice that the research was funded by the pharmaceutical company that created the treatment. Because of this, you view its results skeptically and determine that more independent research is necessary to confirm or refute them. Example: Poor critical thinking in an academic context You’re researching a paper on the impact wireless technology has had on developing countries that previously did not have large-scale communications infrastructure. You read an article that seems to confirm your hypothesis: the impact is mainly positive. Rather than evaluating the research methodology, you accept the findings uncritically.

Nonacademic examples

However, you decide to compare this review article with consumer reviews on a different site. You find that these reviews are not as positive. Some customers have had problems installing the alarm, and some have noted that it activates for no apparent reason.

You revisit the original review article. You notice that the words “sponsored content” appear in small print under the article title. Based on this, you conclude that the review is advertising and is therefore not an unbiased source. Example: Poor critical thinking in a nonacademic context You support a candidate in an upcoming election. You visit an online news site affiliated with their political party and read an article that criticizes their opponent. The article claims that the opponent is inexperienced in politics. You accept this without evidence, because it fits your preconceptions about the opponent.

There is no single way to think critically. How you engage with information will depend on the type of source you’re using and the information you need.

However, you can engage with sources in a systematic and critical way by asking certain questions when you encounter information. Like the CRAAP test , these questions focus on the currency , relevance , authority , accuracy , and purpose of a source of information.

When encountering information, ask:

  • Who is the author? Are they an expert in their field?
  • What do they say? Is their argument clear? Can you summarize it?
  • When did they say this? Is the source current?
  • Where is the information published? Is it an academic article? Is it peer-reviewed ?
  • Why did the author publish it? What is their motivation?
  • How do they make their argument? Is it backed up by evidence? Does it rely on opinion, speculation, or appeals to emotion ? Do they address alternative arguments?

Critical thinking also involves being aware of your own biases, not only those of others. When you make an argument or draw your own conclusions, you can ask similar questions about your own writing:

  • Am I only considering evidence that supports my preconceptions?
  • Is my argument expressed clearly and backed up with credible sources?
  • Would I be convinced by this argument coming from someone else?

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Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

Critical thinking skills include the ability to:

You can assess information and arguments critically by asking certain questions about the source. You can use the CRAAP test , focusing on the currency , relevance , authority , accuracy , and purpose of a source of information.

Ask questions such as:

  • Who is the author? Are they an expert?
  • How do they make their argument? Is it backed up by evidence?

A credible source should pass the CRAAP test  and follow these guidelines:

  • The information should be up to date and current.
  • The author and publication should be a trusted authority on the subject you are researching.
  • The sources the author cited should be easy to find, clear, and unbiased.
  • For a web source, the URL and layout should signify that it is trustworthy.

Information literacy refers to a broad range of skills, including the ability to find, evaluate, and use sources of information effectively.

Being information literate means that you:

  • Know how to find credible sources
  • Use relevant sources to inform your research
  • Understand what constitutes plagiarism
  • Know how to cite your sources correctly

Confirmation bias is the tendency to search, interpret, and recall information in a way that aligns with our pre-existing values, opinions, or beliefs. It refers to the ability to recollect information best when it amplifies what we already believe. Relatedly, we tend to forget information that contradicts our opinions.

Although selective recall is a component of confirmation bias, it should not be confused with recall bias.

On the other hand, recall bias refers to the differences in the ability between study participants to recall past events when self-reporting is used. This difference in accuracy or completeness of recollection is not related to beliefs or opinions. Rather, recall bias relates to other factors, such as the length of the recall period, age, and the characteristics of the disease under investigation.

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Redefining Scientific Thinking for Higher Education pp 203–232 Cite as

Developing Scientific Thinking and Research Skills Through the Research Thesis or Dissertation

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This chapter explores higher level scientific thinking skills that research students need to develop during their research learning journeys towards their dissertation/thesis at postgraduate levels, and also final year undergraduate (Australian honours year) dissertation. A model of four quadrants is introduced. Practice and experience-informed examples are presented to show how higher order skills can be realised and embedded so that they become established ways of thinking, researching, creating, and expressing knowledge and understanding.

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Wisker, G. (2019). Developing Scientific Thinking and Research Skills Through the Research Thesis or Dissertation. In: Murtonen, M., Balloo, K. (eds) Redefining Scientific Thinking for Higher Education. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-24215-2_9

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Search catalog, critical thinking and academic research: intro.

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Critical Thinking and Academic Research

Academic research focuses on the creation of new ideas, perspectives, and arguments. The researcher seeks relevant information in articles, books, and other sources, then develops an informed point of view within this ongoing "conversation" among researchers.

The research process is not simply collecting data, evidence, or "facts," then piecing together this preexisting information into a paper. Instead, the research process is about inquiry—asking questions and developing answers through serious critical thinking and thoughtful reflection.

As a result, the research process is recursive, meaning that the researcher regularly revisits ideas, seeks new information when necessary, and reconsiders and refines the research question, topic, or approach. In other words, research almost always involves constant reflection and revision.

This guide is designed to help you think through various aspects of the research process. The steps are not sequential, nor are they prescriptive about what steps you should take at particular points in the research process. Instead, the guide should help you consider the larger, interrelated elements of thinking involved in research.

Research Anxiety?

Research is not often easy or straightforward, so it's completely normal to feel anxious, frustrated, or confused. In fact, if you feel anxious, it can be a good sign that you're engaging in the type of critical thinking necessary to research and write a high-quality paper.

Think of the research process not as one giant, impossibly complicated task, but as a series of smaller, interconnected steps. These steps can be messy, and there is not one correct sequence of steps that will work for every researcher. However, thinking about research in small steps can help you be more productive and alleviate anxiety.

Paul-Elder Framework

This guide is based on the "Elements of Reasoning" from the Paul-Elder framework for critical thinking. For more information about the Paul-Elder framework, click the link below.

Some of the content in this guide has been adapted from The Aspiring Thinker's Guide to Critical Thinking (2009) by Linda Elder and Richard Paul.

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Critical Thinking: A Model of Intelligence for Solving Real-World Problems

Diane f. halpern.

1 Department of Psychology, Claremont McKenna College, Emerita, Altadena, CA 91001, USA

Dana S. Dunn

2 Department of Psychology, Moravian College, Bethlehem, PA 18018, USA; ude.naivarom@nnud

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation bias, among others. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests. Similarly, some scholars argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Other investigators advocate for critical thinking as a model of intelligence specifically designed for addressing real-world problems. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which we use as an example of contemporary problems that need a new approach.

1. Introduction

The editors of this Special Issue asked authors to respond to a deceptively simple statement: “How Intelligence Can Be a Solution to Consequential World Problems.” This statement holds many complexities, including how intelligence is defined and which theories are designed to address real-world problems.

2. The Problem with Using Standardized IQ Measures for Real-World Problems

For the most part, we identify high intelligence as having a high score on a standardized test of intelligence. Like any test score, IQ can only reflect what is on the given test. Most contemporary standardized measures of intelligence include vocabulary, working memory, spatial skills, analogies, processing speed, and puzzle-like elements (e.g., Wechsler Adult Intelligence Scale Fourth Edition; see ( Drozdick et al. 2012 )). Measures of IQ correlate with many important outcomes, including academic performance ( Kretzschmar et al. 2016 ), job-related skills ( Hunter and Schmidt 1996 ), reduced likelihood of criminal behavior ( Burhan et al. 2014 ), and for those with exceptionally high IQs, obtaining a doctorate and publishing scholarly articles ( McCabe et al. 2020 ). Gottfredson ( 1997, p. 81 ) summarized these effects when she said the “predictive validity of g is ubiquitous.” More recent research using longitudinal data, found that general mental abilities and specific abilities are good predictors of several work variables including job prestige, and income ( Lang and Kell 2020 ). Although assessments of IQ are useful in many contexts, having a high IQ does not protect against falling for common cognitive fallacies (e.g., blind spot bias, reactance, anecdotal reasoning), relying on biased and blatantly one-sided information sources, failing to consider information that does not conform to one’s preferred view of reality (confirmation bias), resisting pressure to think and act in a certain way, among others. This point was clearly articulated by Stanovich ( 2009, p. 3 ) when he stated that,” IQ tests measure only a small set of the thinking abilities that people need.”

3. Which Theories of Intelligence Are Relevant to the Question?

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. For example, Grossmann et al. ( 2013 ) cite many studies in which IQ scores have not predicted well-being, including life satisfaction and longevity. Using a stratified random sample of Americans, these investigators found that wise reasoning is associated with life satisfaction, and that “there was no association between intelligence and well-being” (p. 944). (critical thinking [CT] is often referred to as “wise reasoning” or “rational thinking,”). Similar results were reported by Wirthwein and Rost ( 2011 ) who compared life satisfaction in several domains for gifted adults and adults of average intelligence. There were no differences in any of the measures of subjective well-being, except for leisure, which was significantly lower for the gifted adults. Additional research in a series of experiments by Stanovich and West ( 2008 ) found that participants with high cognitive ability were as likely as others to endorse positions that are consistent with their biases, and they were equally likely to prefer one-sided arguments over those that provided a balanced argument. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests (e.g., Sternberg 2019 ). Similarly, Stanovich and West ( 2014 ) argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Halpern and Butler ( 2020 ) advocate for CT as a useful model of intelligence for addressing real-world problems because it was designed for this purpose. Although there is much overlap among these more recent theories, often using different terms for similar concepts, we use Halpern and Butler’s conceptualization to make our point: Yes, intelligence (i.e., CT) can be enhanced and used for solving a real-world problem like COVID-19.

4. Critical Thinking as an Applied Model for Intelligence

One definition of intelligence that directly addresses the question about intelligence and real-world problem solving comes from Nickerson ( 2020, p. 205 ): “the ability to learn, to reason well, to solve novel problems, and to deal effectively with novel problems—often unpredictable—that confront one in daily life.” Using this definition, the question of whether intelligent thinking can solve a world problem like the novel coronavirus is a resounding “yes” because solutions to real-world novel problems are part of his definition. This is a popular idea in the general public. For example, over 1000 business managers and hiring executives said that they want employees who can think critically based on the belief that CT skills will help them solve work-related problems ( Hart Research Associates 2018 ).

We define CT as the use of those cognitive skills or strategies that increase the probability of a desirable outcome. It is used to describe thinking that is purposeful, reasoned, and goal directed--the kind of thinking involved in solving problems, formulating inferences, calculating likelihoods, and making decisions, when the thinker is using skills that are thoughtful and effective for the particular context and type of thinking task. International surveys conducted by the OECD ( 2019, p. 16 ) established “key information-processing competencies” that are “highly transferable, in that they are relevant to many social contexts and work situations; and ‘learnable’ and therefore subject to the influence of policy.” One of these skills is problem solving, which is one subset of CT skills.

The CT model of intelligence is comprised of two components: (1) understanding information at a deep, meaningful level and (2) appropriate use of CT skills. The underlying idea is that CT skills can be identified, taught, and learned, and when they are recognized and applied in novel settings, the individual is demonstrating intelligent thought. CT skills include judging the credibility of an information source, making cost–benefit calculations, recognizing regression to the mean, understanding the limits of extrapolation, muting reactance responses, using analogical reasoning, rating the strength of reasons that support and fail to support a conclusion, and recognizing hindsight bias or confirmation bias, among others. Critical thinkers use these skills appropriately, without prompting, and usually with conscious intent in a variety of settings.

One of the key concepts in this model is that CT skills transfer in appropriate situations. Thus, assessments using situational judgments are needed to assess whether particular skills have transferred to a novel situation where it is appropriate. In an assessment created by the first author ( Halpern 2018 ), short paragraphs provide information about 20 different everyday scenarios (e.g., A speaker at the meeting of your local school board reported that when drug use rises, grades decline; so schools need to enforce a “war on drugs” to improve student grades); participants provide two response formats for every scenario: (a) constructed responses where they respond with short written responses, followed by (b) forced choice responses (e.g., multiple choice, rating or ranking of alternatives) for the same situations.

There is a large and growing empirical literature to support the assertion that CT skills can be learned and will transfer (when taught for transfer). See for example, Holmes et al. ( 2015 ), who wrote in the prestigious Proceedings of the National Academy of Sciences , that there was “significant and sustained improvement in students’ critical thinking behavior” (p. 11,199) for students who received CT instruction. Abrami et al. ( 2015, para. 1 ) concluded from a meta-analysis that “there are effective strategies for teaching CT skills, both generic and content specific, and CT dispositions, at all educational levels and across all disciplinary areas.” Abrami et al. ( 2008, para. 1 ), included 341 effect sizes in a meta-analysis. They wrote: “findings make it clear that improvement in students’ CT skills and dispositions cannot be a matter of implicit expectation.” A strong test of whether CT skills can be used for real-word problems comes from research by Butler et al. ( 2017 ). Community adults and college students (N = 244) completed several scales including an assessment of CT, an intelligence test, and an inventory of real-life events. Both CT scores and intelligence scores predicted individual outcomes on the inventory of real-life events, but CT was a stronger predictor.

Heijltjes et al. ( 2015, p. 487 ) randomly assigned participants to either a CT instruction group or one of six other control conditions. They found that “only participants assigned to CT instruction improved their reasoning skills.” Similarly, when Halpern et al. ( 2012 ) used random assignment of participants to either a learning group where they were taught scientific reasoning skills using a game format or a control condition (which also used computerized learning and was similar in length), participants in the scientific skills learning group showed higher proportional learning gains than students who did not play the game. As the body of additional supportive research is too large to report here, interested readers can find additional lists of CT skills and support for the assertion that these skills can be learned and will transfer in Halpern and Dunn ( Forthcoming ). There is a clear need for more high-quality research on the application and transfer of CT and its relationship to IQ.

5. Pandemics: COVID-19 as a Consequential Real-World Problem

A pandemic occurs when a disease runs rampant over an entire country or even the world. Pandemics have occurred throughout history: At the time of writing this article, COVID-19 is a world-wide pandemic whose actual death rate is unknown but estimated with projections of several million over the course of 2021 and beyond ( Mega 2020 ). Although vaccines are available, it will take some time to inoculate most or much of the world’s population. Since March 2020, national and international health agencies have created a list of actions that can slow and hopefully stop the spread of COVID (e.g., wearing face masks, practicing social distancing, avoiding group gatherings), yet many people in the United States and other countries have resisted their advice.

Could instruction in CT encourage more people to accept and comply with simple life-saving measures? There are many possible reasons to believe that by increasing citizens’ CT abilities, this problematic trend can be reversed for, at least, some unknown percentage of the population. We recognize the long history of social and cognitive research showing that changing attitudes and behaviors is difficult, and it would be unrealistic to expect that individuals with extreme beliefs supported by their social group and consistent with their political ideologies are likely to change. For example, an Iranian cleric and an orthodox rabbi both claimed (separately) that the COVID-19 vaccine can make people gay ( Marr 2021 ). These unfounded opinions are based on deeply held prejudicial beliefs that we expect to be resistant to CT. We are targeting those individuals who beliefs are less extreme and may be based on reasonable reservations, such as concern about the hasty development of the vaccine and the lack of long-term data on its effects. There should be some unknown proportion of individuals who can change their COVID-19-related beliefs and actions with appropriate instruction in CT. CT can be a (partial) antidote for the chaos of the modern world with armies of bots creating content on social media, political and other forces deliberately attempting to confuse issues, and almost all media labeled “fake news” by social influencers (i.e., people with followers that sometimes run to millions on various social media). Here, are some CT skills that could be helpful in getting more people to think more critically about pandemic-related issues.

Reasoning by Analogy and Judging the Credibility of the Source of Information

Early communications about the ability of masks to prevent the spread of COVID from national health agencies were not consistent. In many regions of the world, the benefits of wearing masks incited prolonged and acrimonious debates ( Tang 2020 ). However, after the initial confusion, virtually all of the global and national health organizations (e.g., WHO, National Health Service in the U. K., U. S. Centers for Disease Control and Prevention) endorse masks as a way to slow the spread of COVID ( Cheng et al. 2020 ; Chu et al. 2020 ). However, as we know, some people do not trust governmental agencies and often cite the conflicting information that was originally given as a reason for not wearing a mask. There are varied reasons for refusing to wear a mask, but the one most often cited is that it is against civil liberties ( Smith 2020 ). Reasoning by analogy is an appropriate CT skill for evaluating this belief (and a key skill in legal thinking). It might be useful to cite some of the many laws that already regulate our behavior such as, requiring health inspections for restaurants, setting speed limits, mandating seat belts when riding in a car, and establishing the age at which someone can consume alcohol. Individuals would be asked to consider how the mandate to wear a mask compares to these and other regulatory laws.

Another reason why some people resist the measures suggested by virtually every health agency concerns questions about whom to believe. Could training in CT change the beliefs and actions of even a small percentage of those opposed to wearing masks? Such training would include considering the following questions with practice across a wide domain of knowledge: (a) Does the source have sufficient expertise? (b) Is the expertise recent and relevant? (c) Is there a potential for gain by the information source, such as financial gain? (d) What would the ideal information source be and how close is the current source to the ideal? (e) Does the information source offer evidence that what they are recommending is likely to be correct? (f) Have you traced URLs to determine if the information in front of you really came from the alleged source?, etc. Of course, not everyone will respond in the same way to each question, so there is little likelihood that we would all think alike, but these questions provide a framework for evaluating credibility. Donovan et al. ( 2015 ) were successful using a similar approach to improve dynamic decision-making by asking participants to reflect on questions that relate to the decision. Imagine the effect of rigorous large-scale education in CT from elementary through secondary schools, as well as at the university-level. As stated above, empirical evidence has shown that people can become better thinkers with appropriate instruction in CT. With training, could we encourage some portion of the population to become more astute at judging the credibility of a source of information? It is an experiment worth trying.

6. Making Cost—Benefit Assessments for Actions That Would Slow the Spread of COVID-19

Historical records show that refusal to wear a mask during a pandemic is not a new reaction. The epidemic of 1918 also included mandates to wear masks, which drew public backlash. Then, as now, many people refused, even when they were told that it was a symbol of “wartime patriotism” because the 1918 pandemic occurred during World War I ( Lovelace 2020 ). CT instruction would include instruction in why and how to compute cost–benefit analyses. Estimates of “lives saved” by wearing a mask can be made meaningful with graphical displays that allow more people to understand large numbers. Gigerenzer ( 2020 ) found that people can understand risk ratios in medicine when the numbers are presented as frequencies instead of probabilities. If this information were used when presenting the likelihood of illness and death from COVID-19, could we increase the numbers of people who understand the severity of this disease? Small scale studies by Gigerenzer have shown that it is possible.

Analyzing Arguments to Determine Degree of Support for a Conclusion

The process of analyzing arguments requires that individuals rate the strength of support for and against a conclusion. By engaging in this practice, they must consider evidence and reasoning that may run counter to a preferred outcome. Kozyreva et al. ( 2020 ) call the deliberate failure to consider both supporting and conflicting data “deliberate ignorance”—avoiding or failing to consider information that could be useful in decision-making because it may collide with an existing belief. When applied to COVID-19, people would have to decide if the evidence for and against wearing a face mask is a reasonable way to stop the spread of this disease, and if they conclude that it is not, what are the costs and benefits of not wearing masks at a time when governmental health organizations are making them mandatory in public spaces? Again, we wonder if rigorous and systematic instruction in argument analysis would result in more positive attitudes and behaviors that relate to wearing a mask or other real-world problems. We believe that it is an experiment worth doing.

7. Conclusions

We believe that teaching CT is a worthwhile approach for educating the general public in order to improve reasoning and motivate actions to address, avert, or ameliorate real-world problems like the COVID-19 pandemic. Evidence suggests that CT can guide intelligent responses to societal and global problems. We are NOT claiming that CT skills will be a universal solution for the many real-world problems that we confront in contemporary society, or that everyone will substitute CT for other decision-making practices, but we do believe that systematic education in CT can help many people become better thinkers, and we believe that this is an important step toward creating a society that values and practices routine CT. The challenges are great, but the tools to tackle them are available, if we are willing to use them.

Author Contributions

Conceptualization, D.F.H. and D.S.D.; resources, D.F.H.; data curation, writing—original draft preparation, D.F.H.; writing—review and editing, D.F.H. and D.S.D. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

No IRB Review.

Informed Consent Statement

No Informed Consent.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Critical Thinking in Academic Research - Second Edition

(4 reviews)

think ing research

Cindy Gruwell, University of West Florida

Robin Ewing, St. Cloud State University

Copyright Year: 2022

Last Update: 2023

Publisher: Minnesota State Colleges and Universities

Language: English

Formats Available

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Learn more about reviews.

Reviewed by Julie Jaszkowiak, Community Faculty, Metropolitan State University on 12/22/23

Organized in 11 parts, this his textbook includes introductory information about critical thinking and details about the academic research process. The basics of critical thinking related to doing academic research in Parts I and II. Parts III –... read more

Comprehensiveness rating: 5 see less

Organized in 11 parts, this his textbook includes introductory information about critical thinking and details about the academic research process. The basics of critical thinking related to doing academic research in Parts I and II. Parts III – XI provide specifics on various steps in doing academic research including details on finding and citing source material. There is a linked table of contents so the reader is able to jump to a specific section as needed. There is also a works cited page with information and links to works used for this textbook.

Content Accuracy rating: 5

The content of this textbook is accurate and error free. It contains examples that demonstrate concepts from a variety of disciplines such as “hard science” or “popular culture” that assist in eliminating bias. The authors are librarians so it is clear that their experience as such leads to clear and unbiased content.

Relevance/Longevity rating: 5

General concepts about critical thinking and academic research methodology is well defined and should not become obsolete. Specific content regarding use of citation tools and attribution structure may change but the links to various research sites allow for simple updates.

Clarity rating: 5

This textbook is written in a conversational manner that allows for a more personal interaction with the textbook. It is like the reader is having a conversation with a librarian. Each part has an introduction section that fully defines concepts and terms used for that part.

Consistency rating: 5

In addition to the written content, this textbook contains links to short quizzes at the end of each section. This is consistent throughout each part. Embedded links to additional information are included as necessary.

Modularity rating: 4

This textbook is arranged in 11 modular parts with each part having multiple sections. All of these are linked so a reader can go to a distinct part or section to find specific information. There are some links that refer back to previous sections in the document. It can be challenging to return to where you were once you have jumped to a different section.

Organization/Structure/Flow rating: 5

There is clear definition as to what information is contained within each of the parts and subsequent sections. The textbook follows the logical flow of the process of researching and writing a research paper.

Interface rating: 4

The pictures have alternative text that appears when you hover over the text. There is one picture on page 102 that is a link to where the downloaded picture is from. The pictures are clear and supportive of the text for a visual learner. All the links work and go to either the correct area of the textbook or to a valid website. If you are going to use the embedded links to go to other sections of the textbook you need to keep track of where you are as it can sometimes get confusing as to where you went based on clicking links.

Grammatical Errors rating: 4

This is not really a grammatical error but I did notice on some of the quizzes if you misspelled a work for fill in the blank it was incorrect. It was also sometimes challenging to come up with the correct word for the fill in the blanks.

Cultural Relevance rating: 5

There are no examples or text that are culturally insensitive or offensive. The examples are general and would be applicable to a variety of students study many different academic subjects. There are references and information to many research tools from traditional such as checking out books and articles from the library to more current such as blogs and other electronic sources. This information appeals to a wide expanse of student populations.

I really enjoyed the quizzes at the end of each section. It is very beneficial to test your knowledge and comprehension of what you just read. Often I had to return and reread the content more critically based on my quiz results! They are just the right length to not disrupt the overall reading of the textbook and cover the important content and learning objectives.

Reviewed by Sara Stigberg, Adjunct Reference Librarian, Truman College, City Colleges of Chicago on 3/15/23

Critical Thinking in Academic Research thoroughly covers the basics of academic research for undergraduates, including well-guided deeper dives into relevant areas. The authors root their introduction to academic research principles and practices... read more

Critical Thinking in Academic Research thoroughly covers the basics of academic research for undergraduates, including well-guided deeper dives into relevant areas. The authors root their introduction to academic research principles and practices in the Western philosophical tradition, focused on developing students' critical thinking skills and habits around inquiry, rationales, and frameworks for research.

This text conforms to the principles and frames of the Framework for Information Literacy for Higher Education, published by the Association of College and Research Libraries. It includes excellent, clear, step-by-step guides to help students understand rationales and techniques for academic research.

Essential for our current information climate, the authors present relevant information for students who may be new to academic research, in ways and with content that is not too broad or too narrow, or likely to change drastically in the near future.

The authors use clear and well-considered language and explanations of ideas and terms, contextualizing the scholarly research process and tools in a relatable manner. As mentioned earlier, this text includes excellent step-by-step guides, as well as illustrations, visualizations, and videos to instruct students in conducting academic research.

(4.75) The terminology and framework of this text are consistent. Early discussions of critical thinking skills are tied in to content in later chapters, with regard to selecting different types of sources and search tools, as well as rationales for choosing various formats of source references. Consciously making the theme of critical thinking as applied to the stages of academic research more explicit and frequent within the text would further strengthen it, however.

Modularity rating: 5

Chapters are divided in a logical, progressive manner throughout the text. The use of embedded links to further readings and some other relevant sections of the text are an excellent way of providing references and further online information, without overwhelming or side-tracking the reader.

Topics in the text are organized in logical, progressive order, transitioning cleanly from one focus to the next. Each chapter begins with a helpful outline of topics that will be covered within it.

There are no technical issues with the interface for this text. Interactive learning tools such as the many self-checks and short quizzes that are included throughout the text are a great bonus for reinforcing student learning, and the easily-accessible table of contents was very helpful. There are some slight inconsistencies across chapters, however, relative to formatting images and text and spacing, and an image was missing in the section on Narrowing a Topic. Justifying copy rather than aligning-left would prevent hyphenation, making the text more streamlined.

Grammatical Errors rating: 5

(4.75) A few minor punctuation errors are present.

The authors of this text use culturally-relevant examples and inclusive language. The chapter on Barriers to Critical Thinking works directly to break down bias and preconceived notions.

Overall, Critical Thinking in Academic Research is an excellent general textbook for teaching the whys and hows of academic research to undergraduates. A discussion of annotated bibliographies would be a great addition for future editions of the text. ---- (As an aside for the authors, I am curious if the anonymous data from the self-checks and quizzes is being collected and analyzed for assessment purposes. I'm sure it would be interesting!)

Reviewed by Ann Bell-Pfeifer, Program Director/ Instructor, Minnesota State Community and Technical College on 2/15/23

The book has in depth coverage of academic research. A formal glossary and index were not included. read more

Comprehensiveness rating: 4 see less

The book has in depth coverage of academic research. A formal glossary and index were not included.

The book appears error free and factual.

The content is current and would support students who are pursuing writing academic research papers.

Excellent explanations for specific terms were included throughout the text.

The text is easy to follow with a standardized format and structure.

The text contains headings and topics in each section.

It is easy to follow the format and review each section.

Interface rating: 5

The associated links were useful and not distracting.

No evidence of grammatical errors were found in the book.

The book is inclusive.

The book was informative, easy to follow, and sequential allowing the reader to digest each section before moving into another.

Reviewed by Jenny Inker, Assistant Professor, Virginia Commonwealth University on 8/23/22

This book provides a comprehensive yet easily comprehensible introduction to critical thinking in academic research. The author lays a foundation with an introduction to the concepts of critical thinking and analyzing and making arguments, and... read more

This book provides a comprehensive yet easily comprehensible introduction to critical thinking in academic research. The author lays a foundation with an introduction to the concepts of critical thinking and analyzing and making arguments, and then moves into the details of developing research questions and identifying and appropriately using research sources. There are many wonderful links to other open access publications for those who wish to read more or go deeper.

The content of the book appears to be accurate and free of bias.

The examples used throughout the book are relevant and up-to-date, making it easy to see how to apply the concepts in real life.

The text is very accessibly written and the content is presented in a simple, yet powerful way that helps the reader grasp the concepts easily. There are many short, interactive exercises scattered throughout each chapter of the book so that the reader can test their own knowledge as they go along. It would be even better if the author had provided some simple feedback explaining why quiz answers are correct or incorrect in order to bolster learning, but this is a very minor point and the interactive exercises still work well without this.

The book appears consistent throughout with regard to use of terminology and tone of writing. The basic concepts introduced in the early chapters are used consistently throughout the later chapters.

This book has been wonderfully designed into bite sized chunks that do not overwhelm the reader. This is perhaps its best feature, as this encourages the reader to take in a bit of information, digest it, check their understanding of it, and then move on to the next concept. I loved this!

The book is organized in a manner that introduces the basic architecture of critical thinking first, and then moves on to apply it to the subject of academic research. While the entire book would be helpful for college students (undergraduates particularly), the earlier chapters on critical thinking and argumentation also stand well on their own and would be of great utility to students in general.

This book was extremely easy to navigate with a clear, drop down list of chapters and subheadings on the left side of the screen. When the reader clicks on links to additional material, these open up in a new tab which keeps things clear and organized. Images and charts were clear and the overall organization is very easy to follow.

I came across no grammatical errors in the text.

Cultural Relevance rating: 4

This is perhaps an area where the book could do a little more. I did not come across anything that seemed culturally insensitive or offensive but on the other hand, the book might have taken more opportunities to represent a greater diversity of races, ethnicities, and backgrounds.

This book seems tailor made for undergraduate college students and I would highly recommend it. I think it has some use for graduate students as well, although some of the examples are perhaps little basic for this purpose. As well as using this book to guide students on doing academic research, I think it could also be used as a very helpful introduction to the concept of critical thinking by focusing solely on chapters 1-4.

Table of Contents

  • Introduction
  • Part I. What is Critical Thinking?
  • Part II. Barriers to Critical Thinking
  • Part III. Analyzing Arguments
  • Part IV. Making an Argument
  • Part V. Research Questions
  • Part VI. Sources and Information Needs
  • Part VII. Types of Sources
  • Part VIII. Precision Searching
  • Part IX. Evaluating Sources
  • Part X. Ethical Use and Citing Sources
  • Part XI. Copyright Basics
  • Works Cited
  • About the Authors

Ancillary Material

About the book.

Critical Thinking in Academic Research - 2nd Edition provides examples and easy-to-understand explanations to equip students with the skills to develop research questions, evaluate and choose the right sources, search for information, and understand arguments. This 2nd Edition includes new content based on student feedback as well as additional interactive elements throughout the text.

About the Contributors

Cindy Gruwell is an Assistant Librarian/Coordinator of Scholarly Communication at the University of West Florida. She is the library liaison to the department of biology and the College of Health which has extensive nursing programs, public health, health administration, movement, and medical laboratory sciences. In addition to supporting health sciences faculty, she oversees the Argo IRCommons (Institutional Repository) and provides scholarly communication services to faculty across campus. Cindy graduated with her BA (history) and MLS from the University of California, Los Angeles and has a Masters in Education from Bemidji State University. Cindy’s research interests include academic research support, publishing, and teaching.

Robin Ewing is a Professor/Collections Librarian at St. Cloud State University. Robin is the liaison to the College of Education and Learning Design. She oversees content selection for the Library’s collections. Robin graduated with her BBA (Management) and MLIS from the University of Oklahoma. She also has a Masters of Arts in Teaching from Bemidji State University. Robin’s research interests include collection analysis, assessment, and online teaching.

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  • Thinking about Research

As you consider research, it is important to know why you want to make this commitment. Do you want to participate more actively in cutting edge science that you have learned about in the classroom? Is there a particular field or topic you would like to learn more about? Do you want to gain specific skills? Do you want to explore research as a potential career, or as a component of a career? Do you want to experience part of the work environment in a medical facility? Do you want to get course credit? Do you want to embark on a project that could evolve into a senior honors thesis?

Think also about the type of research you may find most useful for your individual goal or set of goals. Would you like to help run scientific experiments? Would you like to help design and/or analyze the results of experiments? Would you like to conduct survey research? Would you like to do archival research in a library setting? Would you prefer to be part of a research team or to work alone? Would you like to do research with humans or animals? Would you like to work with a specific species of animal, or a particular population of humans (e.g., children, elderly, persons with a certain disorder)?

It is helpful to consult with others as you think through these questions. Faculty you already know, other faculty including members of the MBB Board of Faculty Advisors [link here, <mbb/advising>], academic advisors (especially in your concentration but also including Shawn Harriman), teaching fellows and resident tutors (who are usually themselves researchers), and fellow students who are already involved in research are all great sounding boards and sources of additional information and perspectives.

Finally, give some thought about what you can offer a research team. This will help you when you come to applying for specific positions. A current resume is always valuable. You may have specific research experience already, or have taken relevant course work. You may be a good team player with a track record of responsibility and accomplishing goals. You do not usually need to have training in the specific techniques used in a laboratory or research program, as most researchers expect to train their undergraduate assistants. Positions that do have specific expectations will note them in their job description.

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critical thinking skils

Student Success

How to improve your critical thinking and research skills.

Critical thinking doesn’t always come naturally to us. It requires analyzing the facts, gathering as much information as possible, thinking open-mindedly, and then forming a judgment.

Rest assured, you can teach yourself to think critically. Here are tips to help you get started.

Be aware of authors’ motivations

You can evaluate an author’s work if you’re aware of what drove that person to undertake the research and writing in the first place. Here are things to be aware of:

  • Avoid personal feelings
  • Be wary of phrases like always , a lot , or never unless you can attach a number to confirm the characterization
  • Steer clear of first-person (using “I”) and second-person (using “you”) pronouns unless you’re asked to reflect or give advice
  • Find credible sources ( more on this below!)
  • Read multiple articles from different perspectives

Find credible evidence

A rule of thumb for most writing is to make a claim, provide evidence to support the claim, and then use reasoning to tie it all together. How do you analyze your sources? Use critical thinking skills. Ask questions such as:

  • Did the researchers only study 10 people?
  • Is the writer representing a particular company or industry?
  • What other articles and studies has the writer published?
  • Is this article published in a scholarly journal, or on a website selling something?

Research well

It’s easier to find credible evidence when you’re looking in the right places. Here are key tips for researching well:

  • Use your school’s online library to find scholarly articles. Peer-reviewed articles have been reviewed by other professionals or scholars in the field and are generally the most accurate.
  • When you read something compelling, check out the reference page at the end of that article, and look up some of those sources.
  • When an author cites another source, try to find that original source, and read it for yourself.
  • Beware of bias, and consider the credibility of the authors you read.
  • Pay close attention to dates. If the research was completed more than five to ten years ago, it’s probably outdated.

Make the most of your findings

The key to using evidence in your paper is not just to sprinkle quotes throughout, but rather to integrate the research into your argument. Explain the significance and implications of that research. It’s one thing to write, “Carrots are good for you,” but it’s much more compelling to explain how and why carrots are good for you based on statistics and research. To demonstrate real critical thinking skills, synthesize what you read (citing it accurately), and incorporate it into your argument, paying special attention to the flow and structure. Read how other authors use information to gain your trust, and utilize their strategies to do the same for your reader.

Critical thinking leads to better research skills, which in turn lead to better writing. When you find credible evidence, it will support your claims more effectively, and you’ll learn to read and listen to information with a critical eye for bias and persuasion. As an added bonus, you’ll also learn to be a better conversationalist outside of school.

To get more insights into sharpening your critical thinking and research skills, watch our webinar:

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February 21, 2024

Why Writing by Hand Is Better for Memory and Learning

Engaging the fine motor system to produce letters by hand has positive effects on learning and memory

By Charlotte Hu

Student handwriting notes in class

FG Trade/Getty Images

Handwriting notes in class might seem like an anachronism as smartphones and other digital technology subsume every aspect of learning across schools and universities. But a steady stream of research continues to suggest that taking notes the traditional way—with pen and paper or even stylus and tablet—is still the best way to learn, especially for young children. And now scientists are finally zeroing in on why.

A recent study in Frontiers in Psychology monitored brain activity in students taking notes and found that those writing by hand had higher levels of electrical activity across a wide range of interconnected brain regions responsible for movement, vision, sensory processing and memory. The findings add to a growing body of evidence that has many experts speaking up about the importance of teaching children to handwrite words and draw pictures.

Differences in Brain Activity

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The new research, by Audrey van der Meer and Ruud van der Weel at the Norwegian University of Science and Technology (NTNU), builds on a foundational 2014 study . That work suggested that people taking notes by computer were typing without thinking, says van der Meer , a professor of neuropsychology at NTNU. “It’s very tempting to type down everything that the lecturer is saying,” she says. “It kind of goes in through your ears and comes out through your fingertips, but you don’t process the incoming information.” But when taking notes by hand, it’s often impossible to write everything down; students have to actively pay attention to the incoming information and process it—prioritize it, consolidate it and try to relate it to things they’ve learned before. This conscious action of building onto existing knowledge can make it easier to stay engaged and grasp new concepts .

To understand specific brain activity differences during the two note-taking approaches, the NTNU researchers tweaked the 2014 study’s basic setup. They sewed electrodes into a hairnet with 256 sensors that recorded the brain activity of 36 students as they wrote or typed 15 words from the game Pictionary that were displayed on a screen.

When students wrote the words by hand, the sensors picked up widespread connectivity across many brain regions. Typing, however, led to minimal activity, if any, in the same areas. Handwriting activated connection patterns spanning visual regions, regions that receive and process sensory information and the motor cortex. The latter handles body movement and sensorimotor integration, which helps the brain use environmental inputs to inform a person’s next action.

“When you are typing, the same simple movement of your fingers is involved in producing every letter, whereas when you’re writing by hand, you immediately feel that the bodily feeling of producing A is entirely different from producing a B,” van der Meer says. She notes that children who have learned to read and write by tapping on a digital tablet “often have difficulty distinguishing letters that look a lot like each other or that are mirror images of each other, like the b and the d.”

Reinforcing Memory and Learning Pathways

Sophia Vinci-Booher , an assistant professor of educational neuroscience at Vanderbilt University who was not involved in the new study, says its findings are exciting and consistent with past research. “You can see that in tasks that really lock the motor and sensory systems together, such as in handwriting, there’s this really clear tie between this motor action being accomplished and the visual and conceptual recognition being created,” she says. “As you’re drawing a letter or writing a word, you’re taking this perceptual understanding of something and using your motor system to create it.” That creation is then fed back into the visual system, where it’s processed again—strengthening the connection between an action and the images or words associated with it. It’s similar to imagining something and then creating it: when you materialize something from your imagination (by writing it, drawing it or building it), this reinforces the imagined concept and helps it stick in your memory.

The phenomenon of boosting memory by producing something tangible has been well studied. Previous research has found that when people are asked to write, draw or act out a word that they’re reading, they have to focus more on what they’re doing with the received information. Transferring verbal information to a different form, such as a written format, also involves activating motor programs in the brain to create a specific sequence of hand motions, explains Yadurshana Sivashankar , a cognitive neuroscience graduate student at the University of Waterloo in Ontario who studies movement and memory. But handwriting requires more of the brain’s motor programs than typing. “When you’re writing the word ‘the,’ the actual movements of the hand relate to the structures of the word to some extent,” says Sivashankar, who was not involved in the new study.

For example, participants in a 2021 study by Sivashankar memorized a list of action verbs more accurately if they performed the corresponding action than if they performed an unrelated action or none at all. “Drawing information and enacting information is helpful because you have to think about information and you have to produce something that’s meaningful,” she says. And by transforming the information, you pave and deepen these interconnections across the brain’s vast neural networks, making it “much easier to access that information.”

The Importance of Handwriting Lessons for Kids

Across many contexts, studies have shown that kids appear to learn better when they’re asked to produce letters or other visual items using their fingers and hands in a coordinated way—one that can’t be replicated by clicking a mouse or tapping buttons on a screen or keyboard. Vinci-Booher’s research has also found that the action of handwriting appears to engage different brain regions at different levels than other standard learning experiences, such as reading or observing. Her work has also shown that handwriting improves letter recognition in preschool children, and the effects of learning through writing “last longer than other learning experiences that might engage attention at a similar level,” Vinci-Booher says. Additionally, she thinks it’s possible that engaging the motor system is how children learn how to break “ mirror invariance ” (registering mirror images as identical) and begin to decipher things such as the difference between the lowercase b and p.

Vinci-Booher says the new study opens up bigger questions about the way we learn, such as how brain region connections change over time and when these connections are most important in learning. She and other experts say, however, that the new findings don’t mean technology is a disadvantage in the classroom. Laptops, smartphones and other such devices can be more efficient for writing essays or conducting research and can offer more equitable access to educational resources. Problems occur when people rely on technology too much , Sivashankar says. People are increasingly delegating thought processes to digital devices, an act called “ cognitive offloading ”—using smartphones to remember tasks, taking a photo instead of memorizing information or depending on a GPS to navigate. “It’s helpful, but we think the constant offloading means it’s less work for the brain,” Sivashankar says. “If we’re not actively using these areas, then they are going to deteriorate over time, whether it’s memory or motor skills.”

Van der Meer says some officials in Norway are inching toward implementing completely digital schools . She claims first grade teachers there have told her their incoming students barely know how to hold a pencil now—which suggests they weren’t coloring pictures or assembling puzzles in nursery school. Van der Meer says they’re missing out on opportunities that can help stimulate their growing brains.

“I think there’s a very strong case for engaging children in drawing and handwriting activities, especially in preschool and kindergarten when they’re first learning about letters,” Vinci-Booher says. “There’s something about engaging the fine motor system and production activities that really impacts learning.”

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Stanford Medicine study identifies distinct brain organization patterns in women and men

Stanford Medicine researchers have developed a powerful new artificial intelligence model that can distinguish between male and female brains.

February 20, 2024

sex differences in brain

'A key motivation for this study is that sex plays a crucial role in human brain development, in aging, and in the manifestation of psychiatric and neurological disorders,' said Vinod Menon. clelia-clelia

A new study by Stanford Medicine investigators unveils a new artificial intelligence model that was more than 90% successful at determining whether scans of brain activity came from a woman or a man.

The findings, published Feb. 20 in the Proceedings of the National Academy of Sciences, help resolve a long-term controversy about whether reliable sex differences exist in the human brain and suggest that understanding these differences may be critical to addressing neuropsychiatric conditions that affect women and men differently.

“A key motivation for this study is that sex plays a crucial role in human brain development, in aging, and in the manifestation of psychiatric and neurological disorders,” said Vinod Menon , PhD, professor of psychiatry and behavioral sciences and director of the Stanford Cognitive and Systems Neuroscience Laboratory . “Identifying consistent and replicable sex differences in the healthy adult brain is a critical step toward a deeper understanding of sex-specific vulnerabilities in psychiatric and neurological disorders.”

Menon is the study’s senior author. The lead authors are senior research scientist Srikanth Ryali , PhD, and academic staff researcher Yuan Zhang , PhD.

“Hotspots” that most helped the model distinguish male brains from female ones include the default mode network, a brain system that helps us process self-referential information, and the striatum and limbic network, which are involved in learning and how we respond to rewards.

The investigators noted that this work does not weigh in on whether sex-related differences arise early in life or may be driven by hormonal differences or the different societal circumstances that men and women may be more likely to encounter.

Uncovering brain differences

The extent to which a person’s sex affects how their brain is organized and operates has long been a point of dispute among scientists. While we know the sex chromosomes we are born with help determine the cocktail of hormones our brains are exposed to — particularly during early development, puberty and aging — researchers have long struggled to connect sex to concrete differences in the human brain. Brain structures tend to look much the same in men and women, and previous research examining how brain regions work together has also largely failed to turn up consistent brain indicators of sex.

test

Vinod Menon

In their current study, Menon and his team took advantage of recent advances in artificial intelligence, as well as access to multiple large datasets, to pursue a more powerful analysis than has previously been employed. First, they created a deep neural network model, which learns to classify brain imaging data: As the researchers showed brain scans to the model and told it that it was looking at a male or female brain, the model started to “notice” what subtle patterns could help it tell the difference.

This model demonstrated superior performance compared with those in previous studies, in part because it used a deep neural network that analyzes dynamic MRI scans. This approach captures the intricate interplay among different brain regions. When the researchers tested the model on around 1,500 brain scans, it could almost always tell if the scan came from a woman or a man.

The model’s success suggests that detectable sex differences do exist in the brain but just haven’t been picked up reliably before. The fact that it worked so well in different datasets, including brain scans from multiple sites in the U.S. and Europe, make the findings especially convincing as it controls for many confounds that can plague studies of this kind.

“This is a very strong piece of evidence that sex is a robust determinant of human brain organization,” Menon said.

Making predictions

Until recently, a model like the one Menon’s team employed would help researchers sort brains into different groups but wouldn’t provide information about how the sorting happened. Today, however, researchers have access to a tool called “explainable AI,” which can sift through vast amounts of data to explain how a model’s decisions are made.

Using explainable AI, Menon and his team identified the brain networks that were most important to the model’s judgment of whether a brain scan came from a man or a woman. They found the model was most often looking to the default mode network, striatum, and the limbic network to make the call.

The team then wondered if they could create another model that could predict how well participants would do on certain cognitive tasks based on functional brain features that differ between women and men. They developed sex-specific models of cognitive abilities: One model effectively predicted cognitive performance in men but not women, and another in women but not men. The findings indicate that functional brain characteristics varying between sexes have significant behavioral implications.

“These models worked really well because we successfully separated brain patterns between sexes,” Menon said. “That tells me that overlooking sex differences in brain organization could lead us to miss key factors underlying neuropsychiatric disorders.”

While the team applied their deep neural network model to questions about sex differences, Menon says the model can be applied to answer questions regarding how just about any aspect of brain connectivity might relate to any kind of cognitive ability or behavior. He and his team plan to make their model publicly available for any researcher to use.

“Our AI models have very broad applicability,” Menon said. “A researcher could use our models to look for brain differences linked to learning impairments or social functioning differences, for instance — aspects we are keen to understand better to aid individuals in adapting to and surmounting these challenges.”

The research was sponsored by the National Institutes of Health (grants MH084164, EB022907, MH121069, K25HD074652 and AG072114), the Transdisciplinary Initiative, the Uytengsu-Hamilton 22q11 Programs, the Stanford Maternal and Child Health Research Institute, and the NARSAD Young Investigator Award.

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit med.stanford.edu .

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Let dental hygientists give you Botox? What are lawmakers thinking?

Letter to the editor: senate bill 1269 puts patients at risk because it allows the wrong medical personnel to administer fillers and botox..

A tiny needle injects Botox into a patient in a Florida clinic on Wednesday, Jan. 24, 2024.

The Arizona Senate will consider a bill that could put Arizona patients at risk for complications from filler and Botox injections,  Senate Bill 1269 , which would allow dental hygienists to administer neurotoxins and dermal fillers for therapeutic or cosmetic purposes.

The medical procedures that dental hygienists want to perform use FDA-regulated devices, which, if misused, could cause complications, possibly leading to visual impairment, blindness or stroke.

These should only be performed by a physician or appropriately trained non-physician personnel under a trained physician’s direct, on-site supervision. This legislation jeopardizes patient safety.

With the growing demand for facial fillers and neuromodulators, providing patients with properly trained and supervised medical personnel is a safeguard Arizona should have for its citizenry.

Neil Fernandes, Chandler

Don't buy the Kroger merger spin

Despite the growing opposition to the Kroger-Albertsons merger,  Kroger continues to “vigorously defend”  the merger, saying that it is great for employees and consumers.

Surely they are not pushing so hard to benefit us all. They obviously stand to gain a lot by merging.

The more they try to spin it, the more we are against it. This merger needs to be blocked.

Rusty Duplessis, Casa Grande

Blame parents before social media

It is amusing to me how much politicians and parents blame technology companies for their children becoming addicted to, and adversely impacted by, social media usage and content.

Nowadays, it is easier to blame others rather than take responsibility.

Why do I say this? Observational learning is one of the most powerful ways children learn. And what are our children observing?

They are seeing adults looking at their phones when driving, walking, going to the bathroom, dining (including when with their partners and/or family), and even when walking with their children. They are learning that watching videos or texting is the most important thing in an adults’ life and must not be disturbed.

If we want our children to be less dependent on social media for their happiness, a good first step is for parents to model interaction with significant others rather than looking at what is on their cellphones. (Parents might also set limits on phone usage, but I’m doubtful the majority of parents are willing to do this).

Mark Loeser, Mesa

Rule change won't kill research

Doug Hockstad’s recent column inveighs  against a proposed federal rule change  that would grant greater flexibility in re-licensing of patents from federally sponsored research when the price of a product based on it is excessive.

He predicts the loss of “$4.7 billion in economic output and more than $172 million in tax revenues” over the next decade as government operatives trample out the last spark of innovation at Arizona universities.

Nothing could be further from the truth. The proposal has stringent guidelines of what inventions are even subject to consideration.

And it’s reasonable to consider whether the public benefit from making products of a taxpayer-funded invention available to and usable by the intended end-users — on whose behalf the initial funding was granted — should weigh against the profits of private individuals and corporations. (Nowhere in the rule do I see it applying to patents from privately funded research.)

Thanks, Doug, for bringing this to our attention. This rule reform is indeed an important issue. I’ll be contacting the White House to support its rapid adoption. 

Robert Altizer, Phoenix

Measles case is a wake-up call

The report of measles in public spaces in Maricopa Country (“ Traveler with measles visited public spots in Phoenix and Chandler. Were you exposed? ” Feb. 13) is a reminder that infectious diseases are a present threat, whether we think about them or not.

This highly contagious disease stays airborne more than two hours after an infected person leaves the area, and vaccination is the only way to protect children and families from its spread.

Measles vaccination rates still haven’t bounced back from the COVID-19 pandemic, especially in low- and middle-income countries with limited access to essential health services. We need continued funding support from Congress to fight measles and other infectious diseases because children’s lives are at risk.

I ask Sens. Mark Kelly and Kyrsten Sinema to protect foreign assistance in this year’s appropriations process and support the highest possible levels of funding for global vaccines programs for next year.

Cynthia Levin, St. Louis, Mo.

What’s on your mind?  Send us a letter to the editor  online or via email at  [email protected] .

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February 24, 2024

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Research examines 700 plant-based foods to see how healthy they really are

by Laura Marchese and Katherine Livingstone, The Conversation

veggie burger

If you're thinking about buying plant-based foods, a trip to the supermarket can leave you bewildered.

There are plant-based burgers, sausages and mince. The fridges are loaded with non-dairy milk, cheese and yogurt. Then there are the tins of beans and packets of tofu .

But how much is actually healthy?

Our nutritional audit of more than 700 plant-based foods for sale in Australian supermarkets has just been published . We found some products are so high in salt or saturated fat, we'd struggle to call them "healthy."

We took (several) trips to the supermarket

In 2022, we visited two of each of four major supermarket retailers across Melbourne to collect information on the available range of plant-based alternatives to meat and dairy products .

We took pictures of the products and their nutrition labels.

We then analyzed the nutrition information on the packaging of more than 700 of these products. This included 236 meat substitutes, 169 legumes and pulses, 50 baked beans, 157 dairy milk substitutes, 52 cheese substitutes and 40 non-dairy yogurts.

Plant-based meats were surprisingly salty

We found a wide range of plant-based meats for sale. So, it's not surprising we found large variations in their nutrition content.

Sodium, found in added salt and which contributes to high blood pressure , was our greatest concern.

The sodium content varied from 1 milligram per 100 grams in products such as tofu, to 2,000mg per 100g in items such as plant-based mince products.

This means we could eat our entire daily recommended sodium intake in just one bowl of plant-based mince.

An audit of 66 plant-based meat products in Australian supermarkets conducted in 2014 found sodium ranged from 316mg in legume-based products to 640mg in tofu products, per 100g. In a 2019 audit of 137 products, the range was up to 1,200mg per 100g.

In other words, the results of our audit seems to show a consistent trend of plant-based meats getting saltier .

What about plant-based milks?

Some 70% of the plant-based milks we audited were fortified with calcium , a nutrient important for bone health .

This is good news as a 2019–2020 audit of 115 plant-based milks from Melbourne and Sydney found only 43% of plant-based milks were fortified with calcium.

Of the fortified milks in our audit, almost three-quarters (73%) contained the recommended amount of calcium —at least 100mg per 100mL.

We also looked at the saturated fat content of plant-based milks.

Coconut-based milks had on average up to six times higher saturated fat content than almond, oat or soy milks.

Previous audits also found coconut-based milks were much higher in saturated fat than all other categories of milks.

A first look at cheese and yogurt alternatives

Our audit is the first study to identify the range of cheese and yogurt alternatives available in Australian supermarkets.

Calcium was only labeled on a third of plant-based yogurts, and only 20% of supermarket options met the recommended 100mg of calcium per 100g.

For plant-based cheeses, most (92%) were not fortified with calcium. Their sodium content varied from 390mg to 1,400mg per 100g, and saturated fat ranged from 0g to 28g per 100g.

So, what should we consider when shopping?

As a general principle, try to choose whole plant foods, such as unprocessed legumes, beans or tofu. These foods are packed with vitamins and minerals. They're also high in dietary fiber, which is good for your gut health and keeps you fuller for longer.

If opting for a processed plant-based food, here are five tips for choosing a healthier option.

1. Watch the sodium

Plant-based meat alternatives can be high in sodium, so look for products that have around 150–250mg sodium per 100g.

2. Pick canned beans and legumes

Canned chickpeas, lentils and beans can be healthy and low-cost additions to many meals . Where you can, choose canned varieties with no added salt, especially when buying baked beans.

3. Add herbs and spices to your tofu

Tofu can be a great alternative to meat. Check the label and pick the option with the highest calcium content. We found flavored tofu was higher in salt and sugar content than minimally processed tofu. So it's best to pick an unflavored option and add your own flavors with spices and herbs.

4. Check the calcium

When choosing a non-dairy alternative to milk, such as those made from soy, oat, or rice, check it is fortified with calcium. A good alternative to traditional dairy will have at least 100mg of calcium per 100g.

5. Watch for saturated fat

If looking for a lower saturated fat option, almond, soy, rice and oat varieties of milk and yogurt alternatives have much lower saturated fat content than coconut options. Pick those with less than 3g per 100g.

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