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The Importance of Students’ Motivation for Their Academic Achievement – Replicating and Extending Previous Findings

Ricarda steinmayr.

1 Department of Psychology, TU Dortmund University, Dortmund, Germany

Anne F. Weidinger

Malte schwinger.

2 Department of Psychology, Philipps-Universität Marburg, Marburg, Germany

Birgit Spinath

3 Department of Psychology, Heidelberg University, Heidelberg, Germany

Associated Data

The datasets generated for this study are available on request to the corresponding author.

Achievement motivation is not a single construct but rather subsumes a variety of different constructs like ability self-concepts, task values, goals, and achievement motives. The few existing studies that investigated diverse motivational constructs as predictors of school students’ academic achievement above and beyond students’ cognitive abilities and prior achievement showed that most motivational constructs predicted academic achievement beyond intelligence and that students’ ability self-concepts and task values are more powerful in predicting their achievement than goals and achievement motives. The aim of the present study was to investigate whether the reported previous findings can be replicated when ability self-concepts, task values, goals, and achievement motives are all assessed at the same level of specificity as the achievement criteria (e.g., hope for success in math and math grades). The sample comprised 345 11th and 12th grade students ( M = 17.48 years old, SD = 1.06) from the highest academic track (Gymnasium) in Germany. Students self-reported their ability self-concepts, task values, goal orientations, and achievement motives in math, German, and school in general. Additionally, we assessed their intelligence and their current and prior Grade point average and grades in math and German. Relative weight analyses revealed that domain-specific ability self-concept, motives, task values and learning goals but not performance goals explained a significant amount of variance in grades above all other predictors of which ability self-concept was the strongest predictor. Results are discussed with respect to their implications for investigating motivational constructs with different theoretical foundation.

Introduction

Achievement motivation energizes and directs behavior toward achievement and therefore is known to be an important determinant of academic success (e.g., Robbins et al., 2004 ; Hattie, 2009 ; Plante et al., 2013 ; Wigfield et al., 2016 ). Achievement motivation is not a single construct but rather subsumes a variety of different constructs like motivational beliefs, task values, goals, and achievement motives (see Murphy and Alexander, 2000 ; Wigfield and Cambria, 2010 ; Wigfield et al., 2016 ). Nevertheless, there is still a limited number of studies, that investigated (1) diverse motivational constructs in relation to students’ academic achievement in one sample and (2) additionally considered students’ cognitive abilities and their prior achievement ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). Because students’ cognitive abilities and their prior achievement are among the best single predictors of academic success (e.g., Kuncel et al., 2004 ; Hailikari et al., 2007 ), it is necessary to include them in the analyses when evaluating the importance of motivational factors for students’ achievement. Steinmayr and Spinath (2009) did so and revealed that students’ domain-specific ability self-concepts followed by domain-specific task values were the best predictors of students’ math and German grades compared to students’ goals and achievement motives. However, a flaw of their study is that they did not assess all motivational constructs at the same level of specificity as the achievement criteria. For example, achievement motives were measured on a domain-general level (e.g., “Difficult problems appeal to me”), whereas students’ achievement as well as motivational beliefs and task values were assessed domain-specifically (e.g., math grades, math self-concept, math task values). The importance of students’ achievement motives for math and German grades might have been underestimated because the specificity levels of predictor and criterion variables did not match (e.g., Ajzen and Fishbein, 1977 ; Baranik et al., 2010 ). The aim of the present study was to investigate whether the seminal findings by Steinmayr and Spinath (2009) will hold when motivational beliefs, task values, goals, and achievement motives are all assessed at the same level of specificity as the achievement criteria. This is an important question with respect to motivation theory and future research in this field. Moreover, based on the findings it might be possible to better judge which kind of motivation should especially be fostered in school to improve achievement. This is important information for interventions aiming at enhancing students’ motivation in school.

Theoretical Relations Between Achievement Motivation and Academic Achievement

We take a social-cognitive approach to motivation (see also Pintrich et al., 1993 ; Elliot and Church, 1997 ; Wigfield and Cambria, 2010 ). This approach emphasizes the important role of students’ beliefs and their interpretations of actual events, as well as the role of the achievement context for motivational dynamics (see Weiner, 1992 ; Pintrich et al., 1993 ; Wigfield and Cambria, 2010 ). Social cognitive models of achievement motivation (e.g., expectancy-value theory by Eccles and Wigfield, 2002 ; hierarchical model of achievement motivation by Elliot and Church, 1997 ) comprise a variety of motivation constructs that can be organized in two broad categories (see Pintrich et al., 1993 , p. 176): students’ “beliefs about their capability to perform a task,” also called expectancy components (e.g., ability self-concepts, self-efficacy), and their “motivational beliefs about their reasons for choosing to do a task,” also called value components (e.g., task values, goals). The literature on motivation constructs from these categories is extensive (see Wigfield and Cambria, 2010 ). In this article, we focus on selected constructs, namely students’ ability self-concepts (from the category “expectancy components of motivation”), and their task values and goal orientations (from the category “value components of motivation”).

According to the social cognitive perspective, students’ motivation is relatively situation or context specific (see Pintrich et al., 1993 ). To gain a comprehensive picture of the relation between students’ motivation and their academic achievement, we additionally take into account a traditional personality model of motivation, the theory of the achievement motive ( McClelland et al., 1953 ), according to which students’ motivation is conceptualized as a relatively stable trait. Thus, we consider the achievement motives hope for success and fear of failure besides students’ ability self-concepts, their task values, and goal orientations in this article. In the following, we describe the motivation constructs in more detail.

Students’ ability self-concepts are defined as cognitive representations of their ability level ( Marsh, 1990 ; Wigfield et al., 2016 ). Ability self-concepts have been shown to be domain-specific from the early school years on (e.g., Wigfield et al., 1997 ). Consequently, they are frequently assessed with regard to a certain domain (e.g., with regard to school in general vs. with regard to math).

In the present article, task values are defined in the sense of the expectancy-value model by Eccles et al. (1983) and Eccles and Wigfield (2002) . According to the expectancy-value model there are three task values that should be positively associated with achievement, namely intrinsic values, utility value, and personal importance ( Eccles and Wigfield, 1995 ). Because task values are domain-specific from the early school years on (e.g., Eccles et al., 1993 ; Eccles and Wigfield, 1995 ), they are also assessed with reference to specific subjects (e.g., “How much do you like math?”) or on a more general level with regard to school in general (e.g., “How much do you like going to school?”).

Students’ goal orientations are broader cognitive orientations that students have toward their learning and they reflect the reasons for doing a task (see Dweck and Leggett, 1988 ). Therefore, they fall in the broad category of “value components of motivation.” Initially, researchers distinguished between learning and performance goals when describing goal orientations ( Nicholls, 1984 ; Dweck and Leggett, 1988 ). Learning goals (“task involvement” or “mastery goals”) describe people’s willingness to improve their skills, learn new things, and develop their competence, whereas performance goals (“ego involvement”) focus on demonstrating one’s higher competence and hiding one’s incompetence relative to others (e.g., Elliot and McGregor, 2001 ). Performance goals were later further subdivided into performance-approach (striving to demonstrate competence) and performance-avoidance goals (striving to avoid looking incompetent, e.g., Elliot and Church, 1997 ; Middleton and Midgley, 1997 ). Some researchers have included work avoidance as another component of achievement goals (e.g., Nicholls, 1984 ; Harackiewicz et al., 1997 ). Work avoidance refers to the goal of investing as little effort as possible ( Kumar and Jagacinski, 2011 ). Goal orientations can be assessed in reference to specific subjects (e.g., math) or on a more general level (e.g., in reference to school in general).

McClelland et al. (1953) distinguish the achievement motives hope for success (i.e., positive emotions and the belief that one can succeed) and fear of failure (i.e., negative emotions and the fear that the achievement situation is out of one’s depth). According to McClelland’s definition, need for achievement is measured by describing affective experiences or associations such as fear or joy in achievement situations. Achievement motives are conceptualized as being relatively stable over time. Consequently, need for achievement is theorized to be domain-general and, thus, usually assessed without referring to a certain domain or situation (e.g., Steinmayr and Spinath, 2009 ). However, Sparfeldt and Rost (2011) demonstrated that operationalizing achievement motives subject-specifically is psychometrically useful and results in better criterion validities compared with a domain-general operationalization.

Empirical Evidence on the Relative Importance of Achievement Motivation Constructs for Academic Achievement

A myriad of single studies (e.g., Linnenbrink-Garcia et al., 2018 ; Muenks et al., 2018 ; Steinmayr et al., 2018 ) and several meta-analyses (e.g., Robbins et al., 2004 ; Möller et al., 2009 ; Hulleman et al., 2010 ; Huang, 2011 ) support the hypothesis of social cognitive motivation models that students’ motivational beliefs are significantly related to their academic achievement. However, to judge the relative importance of motivation constructs for academic achievement, studies need (1) to investigate diverse motivational constructs in one sample and (2) to consider students’ cognitive abilities and their prior achievement, too, because the latter are among the best single predictors of academic success (e.g., Kuncel et al., 2004 ; Hailikari et al., 2007 ). For effective educational policy and school reform, it is crucial to obtain robust empirical evidence for whether various motivational constructs can explain variance in school performance over and above intelligence and prior achievement. Without including the latter constructs, we might overestimate the importance of motivation for achievement. Providing evidence that students’ achievement motivation is incrementally valid in predicting their academic achievement beyond their intelligence or prior achievement would emphasize the necessity of designing appropriate interventions for improving students’ school-related motivation.

There are several studies that included expectancy and value components of motivation as predictors of students’ academic achievement (grades or test scores) and additionally considered students’ prior achievement ( Marsh et al., 2005 ; Steinmayr et al., 2018 , Study 1) or their intelligence ( Spinath et al., 2006 ; Lotz et al., 2018 ; Schneider et al., 2018 ; Steinmayr et al., 2018 , Study 2, Weber et al., 2013 ). However, only few studies considered intelligence and prior achievement together with more than two motivational constructs as predictors of school students’ achievement ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). Kriegbaum et al. (2015) examined two expectancy components (i.e., ability self-concept and self-efficacy) and eight value components (i.e., interest, enjoyment, usefulness, learning goals, performance-approach, performance-avoidance goals, and work avoidance) in the domain of math. Steinmayr and Spinath (2009) investigated the role of an expectancy component (i.e., ability self-concept), five value components (i.e., task values, learning goals, performance-approach, performance-avoidance goals, and work avoidance), and students’ achievement motives (i.e., hope for success, fear of failure, and need for achievement) for students’ grades in math and German and their GPA. Both studies used relative weights analyses to compare the predictive power of all variables simultaneously while taking into account multicollinearity of the predictors ( Johnson and LeBreton, 2004 ; Tonidandel and LeBreton, 2011 ). Findings showed that – after controlling for differences in students‘ intelligence and their prior achievement – expectancy components (ability self-concept, self-efficacy) were the best motivational predictors of achievement followed by task values (i.e., intrinsic/enjoyment, attainment, and utility), need for achievement and learning goals ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). However, Steinmayr and Spinath (2009) who investigated the relations in three different domains did not assess all motivational constructs on the same level of specificity as the achievement criteria. More precisely, students’ achievement as well as motivational beliefs and task values were assessed domain-specifically (e.g., math grades, math self-concept, math task values), whereas students’ goals were only measured for school in general (e.g., “In school it is important for me to learn as much as possible”) and students’ achievement motives were only measured on a domain-general level (e.g., “Difficult problems appeal to me”). Thus, the importance of goals and achievement motives for math and German grades might have been underestimated because the specificity levels of predictor and criterion variables did not match (e.g., Ajzen and Fishbein, 1977 ; Baranik et al., 2010 ). Assessing students’ goals and their achievement motives with reference to a specific subject might result in higher associations with domain-specific achievement criteria (see Sparfeldt and Rost, 2011 ).

Taken together, although previous work underlines the important roles of expectancy and value components of motivation for school students’ academic achievement, hitherto, we know little about the relative importance of expectancy components, task values, goals, and achievement motives in different domains when all of them are assessed at the same level of specificity as the achievement criteria (e.g., achievement motives in math → math grades; ability self-concept for school → GPA).

The Present Research

The goal of the present study was to examine the relative importance of several of the most important achievement motivation constructs in predicting school students’ achievement. We substantially extend previous work in this field by considering (1) diverse motivational constructs, (2) students’ intelligence and their prior achievement as achievement predictors in one sample, and (3) by assessing all predictors on the same level of specificity as the achievement criteria. Moreover, we investigated the relations in three different domains: school in general, math, and German. Because there is no study that assessed students’ goal orientations and achievement motives besides their ability self-concept and task values on the same level of specificity as the achievement criteria, we could not derive any specific hypotheses on the relative importance of these constructs, but instead investigated the following research question (RQ):

RQ. What is the relative importance of students’ domain-specific ability self-concepts, task values, goal orientations, and achievement motives for their grades in the respective domain when including all of them, students’ intelligence and prior achievement simultaneously in the analytic models?

Materials and Methods

Participants and procedure.

A sample of 345 students was recruited from two German schools attending the highest academic track (Gymnasium). Only 11th graders participated at one school, whereas 11th and 12th graders participated at the other. Students of the different grades and schools did not differ significantly on any of the assessed measures. Students represented the typical population of this type of school in Germany; that is, the majority was Caucasian and came from medium to high socioeconomic status homes. At the time of testing, students were on average 17.48 years old ( SD = 1.06). As is typical for this kind of school, the sample comprised more girls ( n = 200) than boys ( n = 145). We verify that the study is in accordance with established ethical guidelines. Approval by an ethics committee was not required as per the institution’s guidelines and applicable regulations in the federal state where the study was conducted. Participation was voluntarily and no deception took place. Before testing, we received written informed consent forms from the students and from the parents of the students who were under the age of 18 on the day of the testing. If students did not want to participate, they could spend the testing time in their teacher’s room with an extra assignment. All students agreed to participate. Testing took place during regular classes in schools in 2013. Tests were administered by trained research assistants and lasted about 2.5 h. Students filled in the achievement motivation questionnaires first, and the intelligence test was administered afterward. Before the intelligence test, there was a short break.

Ability Self-Concept

Students’ ability self-concepts were assessed with four items per domain ( Schöne et al., 2002 ). Students indicated on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree) how good they thought they were at different activities in school in general, math, and German (“I am good at school in general/math/German,” “It is easy to for me to learn in school in general/math/German,” “In school in general/math/German, I know a lot,” and “Most assignments in school/math/German are easy for me”). Internal consistency (Cronbach’s α) of the ability self-concept scale was high in school in general, in math, and in German (0.82 ≤ α ≤ 0.95; see Table 1 ).

Means ( M ), Standard Deviations ( SD ), and Reliabilities (α) for all measures.

Task Values

Students’ task values were assessed with an established German scale (SESSW; Subjective scholastic value scale; Steinmayr and Spinath, 2010 ). The measure is an adaptation of items used by Eccles and Wigfield (1995) in different studies. It assesses intrinsic values, utility, and personal importance with three items each. Students indicated on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree) how much they valued school in general, math, and German (Intrinsic values: “I like school/math/German,” “I enjoy doing things in school/math/German,” and “I find school in general/math/German interesting”; Utility: “How useful is what you learn in school/math/German in general?,” “School/math/German will be useful in my future,” “The things I learn in school/math/German will be of use in my future life”; Personal importance: “Being good at school/math/German is important to me,” “To be good at school/math/German means a lot to me,” “Attainment in school/math/German is important to me”). Internal consistency of the values scale was high in all domains (0.90 ≤ α ≤ 0.93; see Table 1 ).

Goal Orientations

Students’ goal orientations were assessed with an established German self-report measure (SELLMO; Scales for measuring learning and achievement motivation; Spinath et al., 2002 ). In accordance with Sparfeldt et al. (2007) , we assessed goal orientations with regard to different domains: school in general, math, and German. In each domain, we used the SELLMO to assess students’ learning goals, performance-avoidance goals, and work avoidance with eight items each and their performance-approach goals with seven items. Students’ answered the items on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree). All items except for the work avoidance items are printed in Spinath and Steinmayr (2012) , p. 1148). A sample item to assess work avoidance is: “In school/math/German, it is important to me to do as little work as possible.” Internal consistency of the learning goals scale was high in all domains (0.83 ≤ α ≤ 0.88). The same was true for performance-approach goals (0.85 ≤ α ≤ 0.88), performance-avoidance goals (α = 0.89), and work avoidance (0.91 ≤ α ≤ 0.92; see Table 1 ).

Achievement Motives

Achievement motives were assessed with the Achievement Motives Scale (AMS; Gjesme and Nygard, 1970 ; Göttert and Kuhl, 1980 ). In the present study, we used a short form measuring “hope for success” and “fear of failure” with the seven items per subscale that showed the highest factor loadings. Both subscales were assessed in three domains: school in general, math, and German. Students’ answered all items on a 4-point scale ranging from 1 (does not apply at all) to 4 (fully applies). An example hope for success item is “In school/math/German, difficult problems appeal to me,” and an example fear of failure item is “In school/math/German, matters that are slightly difficult disconcert me.” Internal consistencies of hope for success and fear of failure scales were high in all domains (hope for success: 0.88 ≤ α ≤ 0.92; fear of failure: 0.90 ≤ α ≤ 0.91; see Table 1 ).

Intelligence

Intelligence was measured with the basic module of the Intelligence Structure Test 2000 R, a well-established German multifactor intelligence measure (I-S-T 2000 R; Amthauer et al., 2001 ). The basic module of the test offers assessments of domain-specific intelligence for verbal, numeric, and figural abilities as well as an overall intelligence score (a composite of the three facets). The overall intelligence score is thought to measure reasoning as a higher order factor of intelligence and can be interpreted as a measure of general intelligence, g . Its construct validity has been demonstrated in several studies ( Amthauer et al., 2001 ; Steinmayr and Amelang, 2006 ). In the present study, we used the scores that were closest to the domains we investigated: overall intelligence, numerical intelligence, and verbal intelligence (see also Steinmayr and Spinath, 2009 ). Raw values could range from 0 to 60 for verbal and numerical intelligence, and from 0 to 180 for overall intelligence. Internal consistencies of all intelligence scales were high (0.71 ≤ α ≤ 0.90; see Table 1 ).

Academic Achievement

For all students, the school delivered the report cards that the students received 3 months before testing (t0) and 4 months after testing (t2), at the end of the term in which testing took place. We assessed students’ grades in German and math as well as their overall grade point average (GPA) as criteria for school performance. GPA was computed as the mean of all available grades, not including grades in the nonacademic domains Sports and Music/Art as they did not correlate with the other grades. Grades ranged from 1 to 6, and were recoded so that higher numbers represented better performance.

Statistical Analyses

We conducted relative weight analyses to predict students’ academic achievement separately in math, German, and school in general. The relative weight analysis is a statistical procedure that enables to determine the relative importance of each predictor in a multiple regression analysis (“relative weight”) and to take adequately into account the multicollinearity of the different motivational constructs (for details, see Johnson and LeBreton, 2004 ; Tonidandel and LeBreton, 2011 ). Basically, it uses a variable transformation approach to create a new set of predictors that are orthogonal to one another (i.e., uncorrelated). Then, the criterion is regressed on these new orthogonal predictors, and the resulting standardized regression coefficients can be used because they no longer suffer from the deleterious effects of multicollinearity. These standardized regression weights are then transformed back into the metric of the original predictors. The rescaled relative weight of a predictor can easily be transformed into the percentage of variance that is uniquely explained by this predictor when dividing the relative weight of the specific predictor by the total variance explained by all predictors in the regression model ( R 2 ). We performed the relative weight analyses in three steps. In Model 1, we included the different achievement motivation variables assessed in the respective domain in the analyses. In Model 2, we entered intelligence into the analyses in addition to the achievement motivation variables. In Model 3, we included prior school performance indicated by grades measured before testing in addition to all of the motivation variables and intelligence. For all three steps, we tested for whether all relative weight factors differed significantly from each other (see Johnson, 2004 ) to determine which motivational construct was most important in predicting academic achievement (RQ).

Descriptive Statistics and Intercorrelations

Table 1 shows means, standard deviations, and reliabilities. Tables 2 –4 show the correlations between all scales in school in general, in math, and in German. Of particular relevance here, are the correlations between the motivational constructs and students’ school grades. In all three domains (i.e., school in general/math/German), out of all motivational predictor variables, students’ ability self-concepts showed the strongest associations with subsequent grades ( r = 0.53/0.61/0.46; see Tables 2 –4 ). Except for students’ performance-avoidance goals (−0.04 ≤ r ≤ 0.07, p > 0.05), the other motivational constructs were also significantly related to school grades. Most of the respective correlations were evenly dispersed around a moderate effect size of | r | = 0.30.

Intercorrelations between all variables in school in general.

Intercorrelations between all variables in German.

Intercorrelations between all variables in math.

Relative Weight Analyses

Table 5 presents the results of the relative weight analyses. In Model 1 (only motivational variables) and Model 2 (motivation and intelligence), respectively, the overall explained variance was highest for math grades ( R 2 = 0.42 and R 2 = 0.42, respectively) followed by GPA ( R 2 = 0.30 and R 2 = 0.34, respectively) and grades in German ( R 2 = 0.26 and R 2 = 0.28, respectively). When prior school grades were additionally considered (Model 3) the largest amount of variance was explained in students’ GPA ( R 2 = 0.73), followed by grades in German ( R 2 = 0.59) and math ( R 2 = 0.57). In the following, we will describe the results of Model 3 for each domain in more detail.

Relative weights and percentages of explained criterion variance (%) for all motivational constructs (Model 1) plus intelligence (Model 2) plus prior school achievement (Model 3).

Beginning with the prediction of students’ GPA: In Model 3, students’ prior GPA explained more variance in subsequent GPA than all other predictor variables (68%). Students’ ability self-concept explained significantly less variance than prior GPA but still more than all other predictors that we considered (14%). The relative weights of students’ intelligence (5%), task values (2%), hope for success (4%), and fear of failure (3%) did not differ significantly from each other but were still significantly different from zero ( p < 0.05). The relative weights of students’ goal orientations were not significant in Model 3.

Turning to math grades: The findings of the relative weight analyses for the prediction of math grades differed slightly from the prediction of GPA. In Model 3, the relative weights of numerical intelligence (2%) and performance-approach goals (2%) in math were no longer different from zero ( p > 0.05); in Model 2 they were. Prior math grades explained the largest share of the unique variance in subsequent math grades (45%), followed by math self-concept (19%). The relative weights of students’ math task values (9%), learning goals (5%), work avoidance (7%), and hope for success (6%) did not differ significantly from each other. Students’ fear of failure in math explained the smallest amount of unique variance in their math grades (4%) but the relative weight of students’ fear of failure did not differ significantly from that of students’ hope for success, work avoidance, and learning goals. The relative weights of students’ performance-avoidance goals were not significant in Model 3.

Turning to German grades: In Model 3, students’ prior grade in German was the strongest predictor (64%), followed by German self-concept (10%). Students’ fear of failure in German (6%), their verbal intelligence (4%), task values (4%), learning goals (4%), and hope for success (4%) explained less variance in German grades and did not differ significantly from each other but were significantly different from zero ( p < 0.05). The relative weights of students’ performance goals and work avoidance were not significant in Model 3.

In the present studies, we aimed to investigate the relative importance of several achievement motivation constructs in predicting students’ academic achievement. We sought to overcome the limitations of previous research in this field by (1) considering several theoretically and empirically distinct motivational constructs, (2) students’ intelligence, and their prior achievement, and (3) by assessing all predictors at the same level of specificity as the achievement criteria. We applied sophisticated statistical procedures to investigate the relations in three different domains, namely school in general, math, and German.

Relative Importance of Achievement Motivation Constructs for Academic Achievement

Out of the motivational predictor variables, students’ ability self-concepts explained the largest amount of variance in their academic achievement across all sets of analyses and across all investigated domains. Even when intelligence and prior grades were controlled for, students’ ability self-concepts accounted for at least 10% of the variance in the criterion. The relative superiority of ability self-perceptions is in line with the available literature on this topic (e.g., Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ; Steinmayr et al., 2018 ) and with numerous studies that have investigated the relations between students’ self-concept and their achievement (e.g., Möller et al., 2009 ; Huang, 2011 ). Ability self-concepts showed even higher relative weights than the corresponding intelligence scores. Whereas some previous studies have suggested that self-concepts and intelligence are at least equally important when predicting students’ grades (e.g., Steinmayr and Spinath, 2009 ; Weber et al., 2013 ; Schneider et al., 2018 ), our findings indicate that it might be even more important to believe in own school-related abilities than to possess outstanding cognitive capacities to achieve good grades (see also Lotz et al., 2018 ). Such a conclusion was supported by the fact that we examined the relative importance of all predictor variables across three domains and at the same levels of specificity, thus maximizing criterion-related validity (see Baranik et al., 2010 ). This procedure represents a particular strength of our study and sets it apart from previous studies in the field (e.g., Steinmayr and Spinath, 2009 ). Alternatively, our findings could be attributed to the sample we investigated at least to some degree. The students examined in the present study were selected for the academic track in Germany, and this makes them rather homogeneous in their cognitive abilities. It is therefore plausible to assume that the restricted variance in intelligence scores decreased the respective criterion validities.

When all variables were assessed at the same level of specificity, the achievement motives hope for success and fear of failure were the second and third best motivational predictors of academic achievement and more important than in the study by Steinmayr and Spinath (2009) . This result underlines the original conceptualization of achievement motives as broad personal tendencies that energize approach or avoidance behavior across different contexts and situations ( Elliot, 2006 ). However, the explanatory power of achievement motives was higher in the more specific domains of math and German, thereby also supporting the suggestion made by Sparfeldt and Rost (2011) to conceptualize achievement motives more domain-specifically. Conceptually, achievement motives and ability self-concepts are closely related. Individuals who believe in their ability to succeed often show greater hope for success than fear of failure and vice versa ( Brunstein and Heckhausen, 2008 ). It is thus not surprising that the two constructs showed similar stability in their relative effects on academic achievement across the three investigated domains. Concerning the specific mechanisms through which students’ achievement motives and ability self-concepts affect their achievement, it seems that they elicit positive or negative valences in students, and these valences in turn serve as simple but meaningful triggers of (un)successful school-related behavior. The large and consistent effects for students’ ability self-concept and their hope for success in our study support recommendations from positive psychology that individuals think positively about the future and regularly provide affirmation to themselves by reminding themselves of their positive attributes ( Seligman and Csikszentmihalyi, 2000 ). Future studies could investigate mediation processes. Theoretically, it would make sense that achievement motives defined as broad personal tendencies affect academic achievement via expectancy beliefs like ability self-concepts (e.g., expectancy-value theory by Eccles and Wigfield, 2002 ; see also, Atkinson, 1957 ).

Although task values and learning goals did not contribute much toward explaining the variance in GPA, these two constructs became even more important for explaining variance in math and German grades. As Elliot (2006) pointed out in his hierarchical model of approach-avoidance motivation, achievement motives serve as basic motivational principles that energize behavior. However, they do not guide the precise direction of the energized behavior. Instead, goals and task values are commonly recruited to strategically guide this basic motivation toward concrete aims that address the underlying desire or concern. Our results are consistent with Elliot’s (2006) suggestions. Whereas basic achievement motives are equally important at abstract and specific achievement levels, task values and learning goals release their full explanatory power with increasing context-specificity as they affect students’ concrete actions in a given school subject. At this level of abstraction, task values and learning goals compete with more extrinsic forms of motivation, such as performance goals. Contrary to several studies in achievement-goal research, we did not demonstrate the importance of either performance-approach or performance-avoidance goals for academic achievement.

Whereas students’ ability self-concept showed a high relative importance above and beyond intelligence, with few exceptions, each of the remaining motivation constructs explained less than 5% of the variance in students’ academic achievement in the full model including intelligence measures. One might argue that the high relative importance of students’ ability self-concept is not surprising because students’ ability self-concepts more strongly depend on prior grades than the other motivation constructs. Prior grades represent performance feedback and enable achievement comparisons that are seen as the main determinants of students’ ability self-concepts (see Skaalvik and Skaalvik, 2002 ). However, we included students’ prior grades in the analyses and students’ ability self-concepts still were the most powerful predictors of academic achievement out of the achievement motivation constructs that were considered. It is thus reasonable to conclude that the high relative importance of students’ subjective beliefs about their abilities is not only due to the overlap of this believes with prior achievement.

Limitations and Suggestions for Further Research

Our study confirms and extends the extant work on the power of students’ ability self-concept net of other important motivation variables even when important methodological aspects are considered. Strength of the study is the simultaneous investigation of different achievement motivation constructs in different academic domains. Nevertheless, we restricted the range of motivation constructs to ability self-concepts, task values, goal orientations, and achievement motives. It might be interesting to replicate the findings with other motivation constructs such as academic self-efficacy ( Pajares, 2003 ), individual interest ( Renninger and Hidi, 2011 ), or autonomous versus controlled forms of motivation ( Ryan and Deci, 2000 ). However, these constructs are conceptually and/or empirically very closely related to the motivation constructs we considered (e.g., Eccles and Wigfield, 1995 ; Marsh et al., 2018 ). Thus, it might well be the case that we would find very similar results for self-efficacy instead of ability self-concept as one example.

A second limitation is that we only focused on linear relations between motivation and achievement using a variable-centered approach. Studies that considered different motivation constructs and used person-centered approaches revealed that motivation factors interact with each other and that there are different profiles of motivation that are differently related to students’ achievement (e.g., Conley, 2012 ; Schwinger et al., 2016 ). An important avenue for future studies on students’ motivation is to further investigate these interactions in different academic domains.

Another limitation that might suggest a potential avenue for future research is the fact that we used only grades as an indicator of academic achievement. Although, grades are of high practical relevance for the students, they do not necessarily indicate how much students have learned, how much they know and how creative they are in the respective domain (e.g., Walton and Spencer, 2009 ). Moreover, there is empirical evidence that the prediction of academic achievement differs according to the particular criterion that is chosen (e.g., Lotz et al., 2018 ). Using standardized test performance instead of grades might lead to different results.

Our study is also limited to 11th and 12th graders attending the highest academic track in Germany. More balanced samples are needed to generalize the findings. A recent study ( Ben-Eliyahu, 2019 ) that investigated the relations between different motivational constructs (i.e., goal orientations, expectancies, and task values) and self-regulated learning in university students revealed higher relations for gifted students than for typical students. This finding indicates that relations between different aspects of motivation might differ between academically selected samples and unselected samples.

Finally, despite the advantages of relative weight analyses, this procedure also has some shortcomings. Most important, it is based on manifest variables. Thus, differences in criterion validity might be due in part to differences in measurement error. However, we are not aware of a latent procedure that is comparable to relative weight analyses. It might be one goal for methodological research to overcome this shortcoming.

We conducted the present research to identify how different aspects of students’ motivation uniquely contribute to differences in students’ achievement. Our study demonstrated the relative importance of students’ ability self-concepts, their task values, learning goals, and achievement motives for students’ grades in different academic subjects above and beyond intelligence and prior achievement. Findings thus broaden our knowledge on the role of students’ motivation for academic achievement. Students’ ability self-concept turned out to be the most important motivational predictor of students’ grades above and beyond differences in their intelligence and prior grades, even when all predictors were assessed domain-specifically. Out of two students with similar intelligence scores, same prior achievement, and similar task values, goals and achievement motives in a domain, the student with a higher domain-specific ability self-concept will receive better school grades in the respective domain. Therefore, there is strong evidence that believing in own competencies is advantageous with respect to academic achievement. This finding shows once again that it is a promising approach to implement validated interventions aiming at enhancing students’ domain-specific ability-beliefs in school (see also Muenks et al., 2017 ; Steinmayr et al., 2018 ).

Data Availability

Ethics statement.

In Germany, institutional approval was not required by default at the time the study was conducted. That is, why we cannot provide a formal approval by the institutional ethics committee. We verify that the study is in accordance with established ethical guidelines. Participation was voluntarily and no deception took place. Before testing, we received informed consent forms from the parents of the students who were under the age of 18 on the day of the testing. If students did not want to participate, they could spend the testing time in their teacher’s room with an extra assignment. All students agreed to participate. We included this information also in the manuscript.

Author Contributions

RS conceived and supervised the study, curated the data, performed the formal analysis, investigated the results, developed the methodology, administered the project, and wrote, reviewed, and edited the manuscript. AW wrote, reviewed, and edited the manuscript. MS performed the formal analysis, and wrote, reviewed, and edited the manuscript. BS conceived the study, and wrote, reviewed, and edited the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding. We acknowledge financial support by Deutsche Forschungsgemeinschaft and Technische Universität Dortmund/TU Dortmund University within the funding programme Open Access Publishing.

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Essay About Achievements: Top 5 Examples and 6 Prompts

Are you having problems writing your essay about achievements? Then, continue reading this article for samples and prompts to guide you in your writing.

Achievement influences our expectations and self-growth. It’s also often connected with an individual’s progress in life. It gives way for recognition in attaining a goal through standards. 

Achievement acknowledges successes, productiveness, and involvement. But sometimes, achieving doesn’t result in a feeling of satisfaction. Writing an achievement essay is usually based on experiences from yourself or others. You can explore different viewpoints, such as what they consider an “achievement,” how to overcome weaknesses, or why they want a specific achievement. Below are 5 examples and 6 writing prompts to assist you in your essay:

1. The Greatest Achievements In Life by Gerard Reese

2. greatest professional or academic achievement by james taylor , 3. essay on achievements from my professional life by bdoan, 4. my accomplishment by taylor wood, 5. when my weakness became my greatest accomplishment by jay merrill logan, 6 writing prompts on essay about achievements, 1. ways to achieve within different settings, 2. achievements in the small things, 3. how to build confidence, 4. the power of overcoming fear, 5. steps to be successful, 6. guide to building a strong character.

“Nobody succeeds on the first try, we take our mistakes and learn from them. Mistakes are the things that help us strive for greatness, which is why failure should not be viewed as something negative, but more as something we can use to attain [what] we want in life.”

Reese’s piece on achievement talks about learning from failure and trying again until you reach success. Time and failure are contributors to our achievements. He emphasizes that failure can be a steward and teacher to help us get where we want to be. He also provides lists of individuals who encountered crises in their lives until they reached their most successful phases. 

“My father always instilled in me the importance of education. He knew very well that in order for his children to be successful he needed to set them up for success and place them in a position where we would be afforded the opportunity to succeed.”

Family significantly impacts one’s interpretation of what achievements are about. Taylor’s essay highlights the idea of what his father taught him about education and success. He mentions how he embarked through life while keeping his father’s acknowledgment of his potential in the field he has chosen. His essay shows that family shapes one’s belief about what’s considered a successful life.

“I consider the experience in Japan as a big achievement and an important step in my career. The fact that I could master the complex situation gave me much self-confidence and showed that I could manage people successfully even in difficult situations. Today, this unique ability of handling teams attributed me as a strong leader for my people.”

Bdoan’s essay focuses on past experiences and how she handled cultural differences and beliefs, leading to her successful professional life. To achieve fulfillment in work, she breaks the barrier, communicates effectively, and embraces Japanese culture, which she set as a significant setting stone in her career life.

“Through the influence of my best friend, I have motivated myself to spend two hours during the night before I go to sleep to master the lessons the teacher has discussed in class. This helped me greatly since I would no longer have to cram and study everything for the exams later.”

Wood’s essay highlights the external factors that contributed to his achievements. External factors can lead a person to success or frustration. Through a piece of great advice, he changed his lifestyle by allowing himself to move forward and build a quality life. He compares this to Newton’s First law of motion, which he quoted and put at the beginning of his essay.

“…the more I thought about my own greatest personal academic achievement, I realized it was simply getting an A in a college history class my freshman year. Succeeding in this upper-level history class set the tone for all my future college courses and gave me the confidence I needed to achieve greatness, and I am not even a history major.”

Logan talks about his worst subject, History. He recounts how he approached his professor and overcame his weakness. This essay points out that words from others can influence self-growth and confidence. He says he developed faith in his study during college and attained his most outstanding accomplishment.

Are you having problems connecting your ideas smoothly? See this guide on transition words for essays.

After reading through the samples above, it’s time to explore your desired achievement subjects. Here are six prompts about achievements you can use:

Everyone sets expectations for themselves, dependent on the environment they’re in. It can be at work, school, or home. In these cases, the result is just as important as the process.

You can focus your essay on a relatable viewpoint, such as a student who wants to get A+ grades or an office worker who wants to get the Employee of the Month Award. Discuss ways they can excel in their surroundings. Your essay will serve as a guide to help them grow personally and professionally.

Achievements don’t need to be grand. Sometimes, simply getting out of bed is an achievement, especially for those suffering from mental illnesses such as depression. Center your essay on the simple things that can be considered achievements in their way. 

Your essay will not only serve as a reminder that it’s essential to appreciate the small things. It will also comfort those who are going through a hard time.

This topic asks you to highlight the relationship between confidence and achievements. You can interview someone confident in themselves. Ask for tips on building confidence and relay them to your readers while explaining the opportunities they can get by believing in themselves more.

In this busy world, fear is one of the most significant setbacks for people in accomplishing their goals in life. In this essay, you can explain to your readers how acknowledging their fears will help them advance.  

You can also conceptualize the effect of anxiety in achieving your desires and help you set your standard in developing self-growth. Feel free to share your experience with fears and how you plan to deal with them.

To be successful is everyone’s goal. However, sharing steps and tips on how to achieve success is general prompt many writes about. To make your piece stand out, you can tailor it to a group of individuals. For example, a student’s image of success is going on stage and graduating with honors.

Someone’s character is critical to achieving achievements. You can write about a well-known individual who went against the usual route of how success is reached. Such as Steve Jobs, who founded Apple but was a college dropout. 

There are many ways to reach a goal. Tell your readers that they don’t need to follow the conventional method of accomplishing things to get their hands on the achievements they crave.

Do you want to be more confident with your writing? Here are 11 essay writing tips you need to learn today!

• A-Z Publications

Annual Review of Developmental Psychology

Volume 3, 2021, review article, achievement motivation: what we know and where we are going.

• Allan Wigfield 1 , Katherine Muenks 2 , and Jacquelynne S. Eccles 3
• View Affiliations Hide Affiliations Affiliations: 1 Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland 20742-1131, USA; email: [email protected] 2 Department of Educational Psychology, University of Texas at Austin, Austin, Texas 78712, USA 3 School of Education, University of California, Irvine, California 92697, USA
• Vol. 3:87-111 (Volume publication date December 2021) https://doi.org/10.1146/annurev-devpsych-050720-103500
• First published as a Review in Advance on September 08, 2021
• Copyright © 2021 by Annual Reviews. All rights reserved

We review work on the development of children's and adolescents’ achievement motivation, focusing on recent advances in the empirical work in the field and commenting on the status of current theories prominent in the literature. We first focus on the main theories guiding the field and the development of motivational beliefs, values, and goals; intrinsic and extrinsic motivation; identity and motivation; and motivation and emotion. We provide our views on future directions for theory development and what we believe are the critical next steps in developmental research. We then discuss the burgeoning intervention work designed to enhance different aspects of children's motivation: their competence beliefs and mindsets, intrinsic motivation, valuing of achievement, and growth mindsets. We also provide suggestions for next steps in this area in order to guide the field forward. We close with a brief consideration of neuroscience approaches to motivation.

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August 8, 2022

Writing a Powerful Leadership/Achievement Essay [Sample Essay]

Essays that ask you to write about significant achievements fall under the category of

what are known as behavioral or experiential questions . The basic assumption behind these questions is that past behavior is a great predictor of future behavior . They are all varieties on the theme of “Tell us about a time when you…” These questions are meant to take the measure of your managerial potential.

Let’s look at how one candidate effectively addressed this essay question from  Stanford GSB  (*this question is not from the current application):

Tell us about a time when you made a lasting impact on your organization.

This writer avoids writing about leadership in any generic way and zeroes in on the specific aspects of his contributions and their impact:

Leadership essay example: The Change Agent

When I was invited to become the Vice President and General Manager at Third Way Associates (TWA)* two years ago, the company was in financial and administrative disorder. Employee retention was poor, and TWA took too long to pay vendors because of poor communication and accounting processes. Cash flow was managed based on immediate needs rather than by the logic of budgets planned by project and city. Sloppy expense reports that were turned in with no receipts were reimbursed to employees.

TWA founders Scott W ____ and Glenn L ____ had good intentions, but spent most of their time selling sponsorships and getting new clients rather than directing and managing the company. As we begin 20XX, TWA is much healthier in every way. Under my direction, vendors are paid in an average of 20 days from date of invoice, instead of 60 days or more. Our cash flow is better administered since I introduced very specific detailed area budgets with over 125 budget lines per city. Because I can give the company founders much better stability and macromanagement vision, the three of us are able to look more to the future rather than simply put out fires.

Despite the difficult economy in 20XX, we not only retained our same clients but also signed several new client agreements for three years or more, including a two-year contract with Big Shoe Company worth $1.3 million. I’ve brought fresh accounts and industries into TWA, including ____ Airlines and Drink Y, among others. Combined, these accounts generated more than $500,000 in 20XX, and we estimate close to $1 million dollars in the following year.

Since my arrival, we have a much wider and broader sales menu which has been crucial to generate more revenue. I’ve expanded our most popular sports events to 25 cities, giving our clients new investment opportunities. These events range from recreational soccer clinic tours to professional soccer games broadcast on TV.

I also expanded our field staff, and at present we have 25 strong and reliable managers who report directly to me from each city. Despite the economy, 20XX was not a bad year for TWA, and this year promises to be even better if we continue our current strategy and continue to work as a team.

Leadership essay analysis

In every paragraph, this writer mentions concrete measures he took to introduce order to a chaotic company that was trying to grow. From instituting budgets with line items, an improved accounts payable system, and recruiting additional big-name accounts, the writer proves how his efforts strengthened the organization.

How can you maximize on your thought leadership experiences?

As you choose among your own experiences as essay material, think about these questions to help you frame answers of substance:

• What was the obstacle, challenge, or problem that you solved in this accomplishment? A tight client deadline? A complex merger transaction? A new product launch amidst fierce competition?
• What did you do to rise to the challenge you are writing about? Motivate your team to work overtime? Sell senior management on the deal’s long-term upside? Identify a marketing profile for your product that no competitor can match?
• What facts demonstrate that your intervention created a happy ending? Did your team submit the project deliverables three days early despite being 20% understaffed? Your client approved the $500 million merger, the largest ever in its industry? Your new product has 20% market share after only one year? What was the impact of your leadership?

Don’t forget about your people leadership skills

What we’ve spoken about until this point revolves mostly on skilled problem-solving, or “thought leadership.” But respected businesspeople need to be equally or even more talented at something we didn’t have a formal name for: people leadership. By effectively leading the thinking of client firms’ problems as well as motivating them to work long hours to develop solutions to these problems and collaborate with clients on implementing them, these businesspeople prove to have what it takes to be exemplary leaders.

So don’t forget to include strong elements of people leadership in your essays. Here are several to keep in mind:

• Rallying others around a vision. Did you convince your team or group to follow a specific path/solution? How did you do it? Successful clients have talked about handling dissenting opinions diplomatically or presenting their teams’ detailed quantitative evidence for a recommendation. The more you can show that you understood your audience and tailored the content and form of your message to them, the better.
• Harnessing others’ strengths – and expanding them. Did you provide team members tasks they could handle comfortably based on their capabilities, as well as opportunities to broaden their skills? For example, you may have handed your quant jock teammate the most complicated operations analysis as well as responsibility for leading a key client meeting. In this way, you leverage teammates’ strengths while helping them develop new ones.
• Getting through tough times. Did you model for your team enviable cool in pressure-cooker situations, maybe helping them keep the big-picture goal in mind or lightening the mood with humor? Did you reward teammates with praise, pizza, or both for working long into the night? Did you pitch in on others’ responsibilities as deadlines loomed? Helping your team handle stress while managing your own is a cornerstone of strong leadership.

Use your words

Another tip: Look for opportunities to incorporate strong verbs that illustrate your strengths in these areas. Good examples of leadership might incorporate several of the following:

• Establishing a goal or vision
• Obtaining buy-in
• Taking responsibility

The old adage, “Show, don’t tell,” remains a classic bit of wisdom in the writing process. Make that a guiding principle not only in your leadership/achievement essays, but throughout your application.

For personalized advice tailored just for you, check out our MBA Admissions Consulting & Editing services and work one-on-one with a pro who will help you discover your competitive advantage and use it to get accepted.

Related Resources:

• School-Specific MBA Application Essay Tips • Tone Up Your Writing: Confidence vs Arrogance • “I’m Smart, Really I Am!” Proving Character Traits in Your Essays

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Achievement Motivation

Achievement motivation definition.

The term achievement motivation may be defined by independently considering the words achievement and motivation. Achievement refers to competence (a condition or quality of effectiveness, ability, sufficiency, or success). Motivation refers to the energization (instigation) and direction (aim) of behavior. Thus, achievement motivation may be defined as the energization and direction of competence-relevant behavior or why and how people strive toward competence (success) and away from incompetence (failure).

The task of achievement motivation researchers is to explain and predict any and all behavior that involves the concept of competence. Importantly, their task is not to explain and predict any and all behavior that takes place in achievement situations. Much behavior that takes place in achievement situations has little or nothing to do with competence; limiting the achievement motivation literature to behavior involving competence is necessary for the literature to have coherence and structure. That being said, competence concerns and strivings are ubiquitous in daily life and are present in many situations not typically considered achievement situations. Examples include the following: a recreational gardener striving to grow the perfect orchid, a teenager seeking to become a better conversationalist, a politician working to become the most powerful leader in her state, and an elderly person concerned about losing his or her skills and abilities. Thus, the study of achievement motivation is quite a broad endeavor.

Many different achievement motivation variables have been studied over the years. Prominent among these variables are the following: achievement aspirations (the performance level one desires to reach or avoid not reaching; see research by Kurt Lewin, Ferdinand Hoppe), achievement needs/motives (general, emotion-based dispositions toward success and failure; see research by David McClelland, John Atkinson), test anxiety (worry and nervousness about the possibility of poor performance; see research by Charles Spielberger, Martin Covington), achievement attributions (beliefs about the cause of success and failure; see research by Bernard Weiner, Heinz Heckhausen), achievement goals (representations of success or failure outcomes that people strive to attain or avoid; see research by Carol Dweck, John Nicholls), implicit theories of ability (beliefs about the nature of competence and ability; see research by Carol Dweck, Robert Sternberg), perceived competence (beliefs about what one can and cannot accomplish; see research by Albert Bandura; Susan Harter), and competence valuation (importance judgments regarding the attainment of success or the avoidance of failure; see research by Jacqueline Eccles, Judy Harackiewicz). Achievement motivation researchers seek to determine both the antecedents and consequences of these different variables.

Many achievement motivation researchers focus on one of the aforementioned variables in their work, but others strive to integrate two or more of these constructs into an overarching conceptual framework. One such model that has received significant research attention of late is the hierarchical model of approach-avoidance achievement motivation (see research by Andrew Elliot and colleagues); this model is described in the following paragraphs.

Achievement goals are the centerpiece of the model, and these goals are differentiated according to two basic aspects of competence: how it is defined and how it is valenced. Competence is defined by the standard used to evaluate it, and three such standards are identified: an absolute (i.e., task-inherent) standard, an intrapersonal (i.e., the individual’s past attainment or maximum possible attainment) standard, and an interpersonal (i.e., normative) standard. At present, absolute and intraper-sonal standards are collapsed together within a “mastery goal” category, and normative standards are placed within a “performance goal” category. Competence is valenced by whether it is focused on a positive possibility that one would like to approach (success) or a negative possibility that one would like to avoid (failure).

Putting the definition and valence aspects of competence together yields four basic achievement goals that are presumed to comprehensively cover the range of competence-based strivings. Mastery-approach goals represent striving to approach absolute or intrapersonal competence, for example, striving to improve one’s performance. Mastery-avoidance goals represent striving to avoid absolute or intrapersonal incompetence, for example, striving not to do worse than one has done previously. Performance-approach goals represent striving to approach interpersonal competence, for example, striving to do better than others. Performance-avoidance goals represent striving to avoid interpersonal incompetence, for example, striving to avoid doing worse than others.

These achievement goals are posited to have an important and direct impact on the way people engage in achievement activities and, accordingly, the outcomes they incur. Broadly stated, mastery-approach and performance-approach goals are predicted to lead to adaptive behavior and different types of positive outcomes (e.g., mastery-approach goals are thought to optimally facilitate creativity and continuing interest, and performance-approach goals are thought to optimally facilitate performance attainment). Mastery-avoidance and, especially, performance-avoidance goals, on the other hand, are predicted to lead to maladaptive behavior and negative outcomes such as selecting easy instead of optimally challenging tasks, quitting when difficulty or failure is encountered, and performing poorly. A substantial amount of research over the past decade has supported these predictions.

Achievement goals are viewed as concrete, situation-specific variables that explain the specific aim or direction of people’s competence pursuits. Other variables are needed to explain why people orient toward different definitions and valences of competence in the first place, and why they adopt particular types of achievement goals. Higher-order variables such as achievement needs/motives, implicit theories of ability, general competence perceptions, and features of the achievement environment (e.g., norm-based vs. task-based performance evaluation, harsh vs. lenient performance evaluation) are used to explain achievement goal adoption. These variables are not posited to have a direct influence on achievement outcomes, but they are expected to have an indirect influence by prompting achievement goals that, in turn, exert a direct influence on achievement outcomes.

Achievement needs/motives may be used as an illustrative example. Two types of achievement needs/motives have been identified: the need for achievement, which is the dispositional tendency to experience pride upon success, and fear of failure, which is the dispositional tendency to experience shame upon failure. The need for achievement is predicted to lead to mastery-approach and performance-approach goals, whereas fear of failure is predicted to lead to mastery-avoidance and performance-avoidance goals. Fear of failure is also predicted to lead to performance-approach goals, a need/motive to goal combination that represents an active striving toward success to avoid failure (i.e., active avoidance). The need for achievement and fear of failure are posited to have an indirect influence on achievement outcomes through their impact on achievement goal adoption. A number of empirical studies have provided evidence in support of these predictions, as well as many other hierarchically based predictions (involving other higher-order variables) derived from the model.

Models of achievement motivation are of theoretical importance because they help to explain and predict competence-relevant behavior in a systematic and generative fashion. Such models are also of practical importance because they highlight how factors besides intelligence and ability have a substantial impact on achievement outcomes. Competence is widely considered a basic need that all individuals require on a regular basis for psychological and physical well-being to accrue. The bad news from the achievement motivation literature is that many people exhibit motivation in achievement situations that leads to maladaptive behavior, undesirable achievement outcomes, and, ultimately, ill-being. The good news from the achievement motivation literature is that motivation is amenable to change.

References:

• Covington, M. V. (1992). Making the grade: A self-worth perspective on motivation and school reform. Cambridge, UK: Cambridge University Press.
• Elliot, A. J., & Dweck, C. S. (Eds.). (2005). Handbook of competence and motivation. New York: Guilford Press.
• Heckhausen, H., Schmalt, H.-D., & Schneider, K. (1985). Achievement motivation in perspective (M. Woodruff & R. Wicklund, Trans.). New York: Academic Press.
• McClelland, D. C., Atkinson, J. W., Clark, R. A., & Lowell, E. L. (1953). The achievement motive. New York: Appleton-Century-Crofts.
• Nicholls, J. G. (1989). The competitive ethos and democratic education. Cambridge, MA: Harvard University Press.

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Article contents

Achievement motivation in education.

• Judith Meece Judith Meece The University of North Carolina at Chapel Hill
•  and  Charlotte Agger Charlotte Agger Indiana University
• https://doi.org/10.1093/acrefore/9780190264093.013.7
• Published online: 26 April 2018

Achievement motivation theories are used to understand gender discrepancies in motivation across various academic domains. Early on in the field of motivation research, researchers commonly used an attribution framework to study achievement-related outcomes among men and women. Self-efficacy theory and a revised expectancy-value theory of achievement-related choices dominate the current literature on gender differences and achievement motivation. Current trends in research on gender and academic motivation include the shifting and expanding of theoretical frameworks, a new focus on the motivation and achievement of male students, and the use of advanced methodologies and cross-national data to conduct comparative research on gender and patterns of motivation.

• academic motivation
• educational attainment
• motivation theory
• international trends

Introduction

This article provides an overview of research on gender and academic motivation. Due to the authors’ expertise, the primary focus is on youth in the United States; however, a brief mention of international studies is included as well. The article begins with current research findings on gender and educational attainment. It then provides overviews of historical and contemporary theories of achievement motivation, and concludes with a presentation of current and future trends in research regarding gender and academic motivation.

Gender-Related Trends in Academic Achievement and Educational Attainment in the United States and Abroad

Over the past several decades, educational researchers have documented trends in girls’ and boys’ academic achievement and educational attainment (see Agger & Meece, 2015 , for a review). Most notably, within the United States girls have caught up with, and surpassed, their male counterparts regarding performance on school-based and national assessments. Currently, girls are also more likely to complete secondary schooling and graduate from college with a bachelor’s degree (DiPrete & Buchmann, 2013 ; Meece & Askew, 2012 ). However, despite this progress on school-based and national assessments and college completion rates, girls lag behind boys in terms of their participation in mathematics-intensive fields during the postsecondary years and beyond (National Science Foundation [NSF], 2013 ; Watt, 2008 ). Men continue to enter physical science fields (e.g., physics) at greater rates than women (NSF, 2013 ) and continue to pursue these disciplines at greater rates than women beyond college.

Outside of the United States and other industrialized nations, there is less research on gender-related trends in academic achievement and educational attainment. However, there is a small base of literature that has used cross-national data such as the Trends in International Mathematics and Science Study (TIMSS) and the Program for International Student Assessment (PISA) to study gender and achievement. Using these two data sources, researchers have documented patterns of gender-related achievement that are similar to those found in the United States. First, international studies show trends favoring girls on literacy-focused assessments and in terms of grade point averages and college graduation rates (Agger & Meece, 2015 ). In other domains, such as mathematics, boys tend to outperform girls on international assessments, although gender differences are quite small (less than 5%) in countries such as Finland, Slovenia, Sweden, Indonesia, and Russia (Organisation for Economic Co-operation and Development [OECD], 2011 ).

These gender-related patterns mainly appear in Western or industrialized countries. In developing counties, girls have much poorer educational outcomes (OECD, 2011 ), which is a result of numerous and compounding factors including poverty, geographic isolation, early marriage and pregnancy, gender-based violence, and cultural norms surrounding the status and roles of women (United Nations Educational, Scientific and Cultural Organization [UNESCO], 2015 ).

Moreover, even within industrialized countries, such as the United States, there is considerable variation in academic achievement and educational attainment within gender groups related to cultural norms, racial stereotypes, economic resources, and discriminatory practices. As described in the next section, current research on gender and achievement motivation is beginning to examine these larger sociocultural influences on academic achievement and educational attainment.

Historical Perspectives on Gender and Achievement Motivation

Research on gender and achievement motivation has a long history in the fields of education, educational psychology, and psychology. Motivation is defined as a “process by which achievement-related activities are instigated, sustained, or terminated” (Schunk, Meece, & Pintrich, 2014 , p. 5). In the field of education, achievement motivation researchers have studied the processes that influence an individual’s choice, engagement, performance, and level of educational attainment. Whereas early theories of achievement motivation focused on gender-related personality traits, more contemporary theories focus on the formation of self-perceptions, beliefs, and identities as sources of achievement motivation.

Early Theories

Early theories of achievement motivation centered on differences in the achievement motives of men and women. Researchers conceptualized achievement motives as personality dispositions that were formed early on and remained stable over time (Schunk et al., 2014 ). In early studies, McClelland and colleagues ( 1953 ) used the Thematic Apperception Test (TAT) to assess achievement motives in college-age men and women. The TAT measure asked study participants to view and evaluate different pictures. The pictures depicted men and women in different ambiguous situations. After participants were shown the pictures, they were asked to provide a report of what they saw. Researchers showed male students pictures of two men at a machine and a man at a drafting table and researchers showed female students pictures of two women in a laboratory and a woman upholstering a chair. College students were also asked to write stories about a male (female) student who was at the top of his (her) medical class. The TAT’s operating assumption was that study participants would project their motives and desires onto the pictures and stories. For example, success-oriented people would create stories that involved a significant amount of achievement imagery. Results of the study showed that, in general, college men responded to the TAT assessments with more achievement imagery compared to their female counterparts. Based on study findings, researchers concluded that women were less success-oriented than men. In a further analysis of men’s and women’s responses, Horner ( 1972 ) reported that 65% of the college women and 8% of the college men wrote stories that showed anxiety about success in academic situations. Horner ( 1975 ) argued that “most women have a motive to avoid success, that is, a disposition to become anxious about achieving success because they expect negative consequences such as social rejection and/or feelings of being unfeminine” (p. 207). Accordingly, women’s fear of success, and how this fear could lead to diminished achievement, were topics that generated much research in the 1970s (see Frieze, Parsons, Johnson, Ruble, & Zellman, 1978 ).

By the late 1970s, the previous work on achievement motives and fears of success had been discredited. Problems related to biased research methodologies and findings that were not generalizable across different samples surfaced (Frieze et al., 1978 ). In addition to these problems, the work was also criticized because it cast male achievement as the standard to which female achievement was compared. Furthermore, the work on achievement motives and fears of success was criticized because it did not consider how gendered socialization patterns and other proximal and distal forces shape men’s and women’s academic and occupational choices (Eccles, 1994 ).

Attribution Theory

During the 1970s and early 1980s, attribution theory was the prevailing theory of motivation and was heavily utilized to understand differences in achievement motivation across gender. Attribution theory served as the transition into cognitive perspectives on motivation due to its emphasis on cognitive processes involved in interpreting successes and failures in achievement situations (Meece, Glienke, & Burg, 2006 ). This emphasis was different from earlier theories, which included personality dispositions (e.g., motives to avoid success and fear of failure). Attribution theory also served as the springboard for developmental studies of children’s conceptions of ability and definitions of success (Dweck & Elliot, 1983 ; Nicholls, 1984 ).

Weiner ( 1979 ) played a major role in developing attribution theory and applying it to educational settings. In attribution theory, individuals are viewed as “naive scientists,” trying to understand their own behaviors and also the behavior of others around them. Weiner ( 1985 , 1986 ) argued that the two chief causal ascriptions people make related to success and failure are ability and effort. Weiner also argued that attributions were related to a variety of additional achievement-related beliefs such as expectations for success, achievement striving, and the affect (e.g., anxiety) associated with achievement.

An attribution framework was widely applied in studies examining gender differences in achievement motivation. Across various age groups, male participants were shown to attribute their successes to internal causes such as ability, whereas female participants attributed their failures to internal causes (Bar-Tal, 1978 ; Crandall, Kathkowsky, & Crandall, 1965 ; Frieze, 1975 ; McMahan, 1973 ). Later on, these gender-related findings were more consistently reported for sex-typed domains such as mathematics and science (Eccles et al., 1983 ; Frieze, Whiteley, Hanusa, & McHugh, 1982 ; Parsons [Eccles], Meece, Adler, & Kaczala, 1982 ; Wolleat, Pedro, Becker, & Fennema, 1980 ). In the end, researchers concluded that gender differences in causal attributions patterns were dependent on the type of academic domain, the students’ ability level, and the kinds of research methodologies employed (Parsons [Eccles] et al., 1982 ).

A related area of attribution research includes studies of learned helplessness. Learned helplessness occurs when individuals attribute their failure to a lack of ability and show decreases in effort when confronted with failure (Licht & Dweck, 1984 ). Researchers argued that girls may be more prone to learned helplessness than boys, particularly in the domain of mathematics and other male sex-typed domains, due to a tendency to attribute failure to a lack of ability (Dweck, 1986 ; Eccles et al., 1982 ; Farmer & Vispoel, 1990 ). However, findings were not consistently found across studies. For example, Eccles [Parsons] et al. ( 1982 ) used authentic learning tasks (e.g., number sequences) to examine gender differences in learned helplessness among students in Grades 8–10. These researchers found gender differences in attributions to ability for successes and failures on math problems, but these causal attribution patterns did not explain gender differences in persistence, expectancy judgments, or error rates (see also Kloosterman, 1990 ). Empirical studies provided limited support for greater learned helplessness among girls than boys.

Grounded in attribution theory, studies on students’ mindsets have shed some light on potential reasons for the underrepresentation of women in math and science fields. Work by Dar-Nimrod and Heine ( 2006 ) and Good, Rattan, and Dweck ( 2007 ; cited in Dweck, 2008 ) showed that differences in women’s math performance and feelings of belonging depended on whether they held a growth-mindset (i.e., holding the belief that you can significantly change your intelligence level) versus fixed-mindset (i.e., holding belief that your intelligence and ability levels are fixed). These researchers documented that female students who maintained a growth-mindset performed better on math tasks (Dar-Nimrod & Heine, 2006 ) and were less susceptible to the negative effects of stereotypes; when they were faced with negative stereotypes, they still felt that they belonged in math, intended to pursue math courses, and continued to earn high grades (Good et al., 2007 ).

To summarize, research using attribution theory sought to understand the low expectancy patterns, achievement anxiety, and learned helplessness that inhibited female achievement. Despite numerous studies, research on gender differences in causal attributions and learned helplessness is inconclusive and equivocal. Gender differences in attributions depend on the particular methodology used, the specific academic domain, the academic abilities of students, the achievement task, and the context in which the research occurs. Additionally, when gender differences are found, they are often small in magnitude and do not strongly predict behavioral responses (Eccles et al., 1983 ; Eccles [Parsons] et al., 1982 , 1984 ; Hyde, 2014 ).

Contemporary Theories of Achievement Motivation

After the introduction of attribution theory in the 1970s, subsequent theories emphasized the role of cognitive processes in explaining gender differences in achievement motivation. Two theories have dominated research in this area: self-efficacy theory (Bandura, 1977 ) and a revised expectancy-value theory of achievement-related choices (Eccles et al., 1983 ).

Self-Efficacy Theory

The construct of self-efficacy was introduced more than 40 years ago (Bandura, 1977 ). Since its introduction, educational researchers and those studying academic motivation and self-regulated learning have heavily drawn upon self-efficacy theory. Self-efficacy refers to a person’s judgment of their confidence to learn, perform academic tasks, or succeed in academic endeavors (Bandura, 1986 ). Unlike more global beliefs such as self-concept, self-confidence, and locus of control, self-efficacy involves judgments concerning one’s ability to attain a certain level of performance in a particular activity or situation (Meece, Wigfield, & Eccles, 1990 ; Schunk, 1984 ). For example, in one study, respondents were asked to rate their level of confidence for solving a certain number of mathematics problems correctly, for obtaining a certain grade in a course, for comprehending reading passages of different levels of difficulty, or for learning technical terms in biology (Pajares, 1996b ). Research has consistently shown that self-efficacy beliefs are important mediators of all types of achievement-related behaviors, such as effort and task persistence, self-regulatory strategies, course enrollment, and career choices (Bong & Skaalvik, 2003 ; Fast et al., 2010 ; Pajares, 1996b ; Pintrich & Schunk, 2002 ; Schunk & Pajares, 2002 ).

Motivation researchers have used self-efficacy theory to understand gender differences in motivation and achievement. The majority of this research has focused on academic areas that are traditionally sex-typed as male or female. A plethora of studies documents that boys tend to report higher self-efficacy and expectancy beliefs than girls surrounding their performance in math and science (Anderman & Young, 1994 ; Pajares, 1996a , 1996b ; Pintrich & De Groot, 1990 ; Zimmerman & Martinez-Pons, 1990 ), as well as computer science (Busch, 1995 ). The results of Huang’s ( 2013 ) meta-analysis of 187 studies of gender differences in self-efficacy beliefs showed a consistent pattern favoring male students with learning tasks related to mathematics, science, computer science, and social sciences. However, effect sizes were reported as small (.08), with the exception of respondents over the age of 23 years. In contrast, when the context is changed, and the academic domain is reading or writing, the gender difference is reversed and girls are favored (Huang, 2013 ; Pajares & Valiante, 2001a , 2001b ; Williams & Takaku, 2011 ).

Self-efficacy researchers have identified several confounding factors that may contribute to gender differences in self-efficacy. First, gender differences were nonsignificant when previous achievement was controlled for; that is, when self-efficacy beliefs of students are analyzed at the same level of academic ability, fewer differences in self-beliefs appear (Pajares, 1996a ). Second, the measurement process itself may be responsible for differences. Researchers have observed that boys tend to be more “self-congratulatory” in their responses (i.e., expressing overconfidence), whereas girls tend to be more modest (Wigfield, Eccles, & Pintrich, 1996 ). Additionally, recent studies have explored gender differences in sources of self-efficacy. Mastery experiences tend to be predictive of both girls’ and boys’ self-efficacy beliefs in school settings (Usher & Pajares, 2006 , 2008 ). Given the positive influence of self-efficacy on achievement and motivation, a better understanding of gender- and age-related differences in the development of self-efficacy beliefs is needed.

Contemporary Expectancy-Value Theory

Building on the work of Atkinson ( 1957 , 1964 ) and Weiner ( 1985 ), Eccles and colleagues ( 1983 ) proposed a social cognitive model of achievement choice for understanding adolescent performance and choice in the domain of mathematics. Eccles et al.’s ( 1983 ) model has several unique features that take it beyond traditional expectancy-value models. First, it elaborates upon both the expectancy and value components. Eccles and colleagues challenged Atkinson’s premise that expectancies and values are inversely related. Second, it stresses the fluid nature of the processes underlying choice. The new model identifies developmental sources of children’s and adult’s expectancy and value beliefs. More specifically, the development of expectancies and task values are influenced, directly and interactively, by proximal psychological constructs (e.g., goals and affective memories) as well as by socialization agents such as parents, peers, and teachers. Last, the Eccles et al. ( 1983 ) model of achievement motivation emphasizes the role of the cultural milieu of the developing child.

Motivation researchers have used expectancy-value theory as a framework to examine gender differences in motivation and achievement behavior. Originating with the research of Atkinson ( 1957 ), expectancy-value theory proposes that individuals are most likely to approach and perform achievement activities when they expect to succeed and when they attach value to that task. The Eccles et al. ( 1983 ) model has been applied to different achievement domains (mathematics, science, and sports) as well as career choices and trajectories of young adults. To date, research has identified gender-related differences in key components of the expectancy-value model.

Competency Beliefs

In the Eccles et al. ( 1983 ) expectancy-value model of academic choice, competency beliefs are defined as estimations of one’s ability to perform or to succeed at an activity. Research with children, adolescents, and adults has shown that competency beliefs have a particularly strong relation to academic performance (Eccles et al., 1983 ; Wigfield & Eccles, 1995 ). Over the past few decades, much has been learned about children’s competency beliefs and gender differences associated with these perceptions. First, as early as first grade, children begin to engage in making judgments about their abilities in a variety of domains, including mathematics, reading, music, and sports (Eccles, Wigfield, Harold, & Blumenfeld, 1993 ). Second, small gender differences in children’s competency beliefs also emerge in early elementary school (Eccles et al., 1993 ). These gender differences tend to align with gender-role stereotyped domains and tend to occur on novel tasks. The results of several studies show that boys hold more positive competence beliefs for sports and mathematics, whereas girls hold more positive competence beliefs for instrumental music and reading (Eccles et al., 1993 ; Jacobs et al., 2002 ). These gender differences emerge even though boys and girls are performing equally well in these domains (Eccles et al., 1993 ). However, the sizes of these differences are relatively small and should be interpreted with caution, given that they are dependent on other factors such as stage of development, type of activity, country where the research was conducted, subpopulations within the country, and historical time period (Wigfield et al., 2015 ).

Cross-sectional and longitudinal research has indicated that children report declines in their competency beliefs as they progress through schooling (Wigfield & Eccles, 2000 ; Wigfield, Eccles, Yoon, & Harold, 1997 ), although the precise rate of change is dependent on domain and gender. This research has documented the fact that girls’ perceptions of the math abilities decline at a slower rate than boys’, leading to an overall decrease in the gender gap for mathematics competence over time (Fredericks & Eccles, 2002 ; Jacobs et al., 2002 ). In domains other than mathematics, such as language arts, boys’ competence steadily declines in elementary school, and by middle school there are significant differences in boys’ and girls’ competency ratings for language arts. However, these language arts gaps become somewhat small by high school (Jacobs et al., 2002 ). In sports domains, gender differences favoring boys remain stable across all grades of school (Fredericks & Eccles, 2002 ; Jacobs et al., 2002 ).

Value Beliefs

In the Eccles et al.’s ( 1983 ) expectancy-value model of achievement choices, the influence of competence perceptions is moderated by the value attached to achievement activities. Task value is comprised of four components: (1) perceived importance of being good at an activity; (2) perceived usefulness of the activity for obtaining short- or long-term goals; (3) perceived interest or liking of the activity; and (4) perceived cost of engaging in the activity (e.g., time taken away from other activities, amount of effort needed to succeed, etc.). By fifth grade, children are able to differentiate what activities may not hold much interest for them but are necessary to achieving a short- or long-term goal (Eccles et al., 1993 ). The subjective value of a particular achievement-related activity predicts engagement and participation rates. For example, the value adolescents attach to mathematics predicts their decision to enroll in optional mathematics courses (Eccles, 1994 ; Feather, 1988 ; Meece et al., 1990 ). Similarly, the value attached to sports predicts participation in athletic activities (Eccles & Harold, 1991 ).

Beginning with elementary school, gender differences are evident in the value children and adolescents attach to different academic domains. As with competency beliefs, the patterns follow gender norms and stereotypes. In a longitudinal study of first- through fourth-grade students, Eccles and her colleagues ( 1993 ) reported gender differences favoring boys in the valuing of sports activities ( d = .04), whereas girls placed greater value than boys on musical and reading activities ( d ’s = .06 and .03, respectively). Interestingly, there were no gender differences in the value attached to mathematics for elementary school children. In this study, task values were defined as a composite score representing the perceived interest, enjoyment, importance, and usefulness of an academic domain.

Subsequent studies with older children and adolescents show similar patterns of gender differences in achievement task values. When values were defined as liking of an achievement domain (mathematics, English, and sports), Wigfield and his colleagues ( 1991 ) reported that students’ perceptions of the value of mathematics, reading, and sports declined at the transition to junior high school (Grade 7). In general, young adolescents placed more value on social activities and sports than on English and mathematics. As with younger students, girls reported more liking than boys for English ( d = .50), whereas boys placed greater value than girls on sports ( d = .49). However, more recent research indicates that boys and girls now value math equally, but girls report less interest in physical and computer sciences and engineering compared to boys and do not enroll in these courses during the postsecondary years (Eccles, 2013 ; Wang, Eccles, & Kenny, 2013 ). International studies show similar trends. In many countries, girls report valuing math as much as boys do, but they also believe that they are not as good at math and do not aspire to careers involving the physical sciences, computers, and technology at the same rates as boys do (Jerrim & Schoon, 2014 )

Summary of Contemporary Theories

Contemporary theories of achievement motivation emphasize motivation beliefs, goals, and aspirations. Of the theories examined in this section, Eccles et al.’s ( 1983 ) expectancy-value model of achievement behavior has been the most widely applied in studies of gender differences in achievement motivation. Research using this framework has documented how boys and girls begin school with varying interests and differing views of their abilities. Boys begin school with higher perceptions of their math abilities, whereas girls report higher perceptions of their language arts abilities. Over the course of schooling, gender gaps in the perceptions for mathematics decrease and increase for language arts. In addition, gender differences can vary depending on how task value is defined. For example, when task values are defined as interest and importance, there are no gender differences in students’ valuing of mathematics. Although it seems more likely that declines in competency and value beliefs might happen during or directly after schooling transitions, analyses using growth modeling procedures indicate that the most rapid period of decline in both competency and value perceptions occurs in the elementary school years (Jacobs et al., 2002 ). Additionally, numerous studies have shown that children’s and adolescents’ competence beliefs are important predictors of their performance in different domains. In contrast, value perceptions are a stronger predictor of students’ choice to participate in an activity or task. Predictive relations for competency and value perceptions are found as early as first grade and increase with age (Eccles, 1994 ; Eccles et al., 1983 ; Eccles, Adler, & Meece, 1984 ; Meece et al., 1990 ; Wigfield & Eccles, 1992 ).

Current and Future Trends in Research

Thus far, this article has discussed findings from research on gender and academic motivation both in the United States and abroad and has provided historical and contemporary overviews of theories of achievement motivation. We will now shift to an exploration of current and future trends in research about gender and academic motivation. These current and future trends in research include an altering and expanding of theoretical frameworks, an increased focus on the achievement and motivation of male students, and the proliferation of new methodologies and sources of data.

Shifting and Expanding of Theoretical Frameworks

A decade ago, Perry, Turner, and Meyer ( 2006 ) asserted that “contextual understandings are more integral to research on motivation today, reflecting the general shift in educational research toward situated and social perspectives on learning” (p. 328). Since then, researchers have begun to incorporate more contextual variables into the study of student motivation, answering the call of Perry and colleagues ( 2006 ) and others.

One theoretical framework that has been used to study the intersection of contextual variables is the Eccles et al. ( 1983 ) developmental model of achievement motivation. The Eccles et al. ( 1983 ) model has a strong socialization component, which has been used to examine how socialization experiences create and reinforce gender-related differences in motivation and achievement. For example, Eccles, Wong, and Peck ( 2006 ) looked at the intersection of ethnicity, motivation, and achievement and reported that daily racial discrimination during seventh and eighth grades predicted declines in grades, academic ability self-concepts, and academic task values. In another study, Graham, Taylor, and Hudley ( 1998 ) studied how gender, ethnicity, and discrimination related to motivation. Graham and her colleagues ( 1998 ) found that African American boys demonstrated a higher likelihood of devaluing academic success under conditions of racial discrimination. On the other hand, African American girls placed more emphasis on relationships and approval from peers and teachers when self-concepts were threatened by ethnic discrimination. Work by Benner and Graham ( 2009 ) featured a Latino sample and documented how perceptions of discrimination were higher for boys and that, cumulatively, higher levels of discrimination had an effect on academic outcomes via the influence on perceptions of school climate. As schools become increasingly ethnically diverse, research that reflects the unique contributions of ethnicity, social class, and community is imperative.

Educational researchers are beginning to integrate variables from different contexts in researching gender and motivation. Hyde ( 2014 ) argues that future research focused on gender should move toward intersectionality and situated contexts. Intersectionality refers to simultaneously considering multiple categories of identity, difference, and disadvantage, such as gender, race, class, and sexual orientation (Cole, 2009 ). This perspective is rooted in the idea that gender cannot be studied or understood apart from context, such as the context of ethnicity or social class. Similarly, a situated perspective on research is, as Turner and Nolen ( 2015 ) wrote, “one that interprets individuals’ beliefs and behaviors as arising through their participation in social, cultural, and historical contexts or systems” (p. 168). These paradigms may also be applied to work on gender and academic motivation. One example of taking a situated perspective related to gender and motivation is illustrated by Nolen, Horn, and Ward ( 2015 ). These researchers showed how a situative study of a girl’s motivation to become a skilled chess player would include both her interest in becoming competent at chess moves and also her inclination to develop these skills in a local park with elders. They explained that a situated study would consider the fact that the majority of expert chess players are male, how this puts the girl in a particular social position, and how her interactions with others before, during, and after playing chess were integral in studying her chess-related motivation and engagement.

More Research on Male Students

Most of the early work on gender and academic motivation was focused on explaining why girls lagged behind boys in their performance in and motivation for math and science. Research conducted in the 1980s and 1990s highlighted the discrepancies between boys’ and girls’ achievement in and motivation for these academic subjects. As girls achieved relative parity with boys on national and school-based assessments in math and science, another trend began to take shape: boys’ underperformance in school (Cornwell, Mustard, & Van Parys, 2013 ; Taylor & Lorimer, 2003 ) and on national assessments (NCES, 2012 ). Male students currently graduate high school and college at lower rates and do not demonstrate clear aspirations for higher education compared to their female counterparts (Meece & Askew, 2012 ).

Researchers have applied motivation theories to explain these gender-differentiated trends in academic motivation and achievement. For example, Jacobs et al. ( 2002 ) conducted a longitudinal study of 761 students from 10 Midwestern schools and found declines in both girls’ and boys’ competency beliefs, which varied based on domain and gender. These researchers found that boys’ and girls’ perceptions of ability in language arts were similar at the beginning of elementary school, but boys’ ability beliefs declined more rapidly started in the late elementary school. Jacobs et al. ( 2002 ) also documented declines in value-related beliefs across the school years for mathematics and language arts subjects. Specifically, boys demonstrated a more rapid decline in language arts than girls. Although these declines in competency and value beliefs may explain gender differences in academic achievement, Jacobs and colleagues ( 2002 ) did not specifically examine those relations. Given the trends in boys’ lower academic motivation and achievement, there is a clear need for more research that looks at the mechanisms underlying male students’ underperformance.

Researchers have also used motivation theories to study gender and academic outcomes beyond elementary and middle school. However, studies utilizing motivational constructs to investigate postsecondary aspirations, college enrollment patterns, and postsecondary attainment are few in number. In one very recent study, Meece, Askew, Agger, Hutchins, and Byun ( 2014 ) used a nationwide sample of rural youth to investigate how familial, geographic, and economic variables influenced gender-related differences in educational and occupational aspirations. Findings revealed a favoring of girls in terms of educational aspirations, occupational aspirations, and aspirations for nontraditional careers. The study also showed that key motivation variables, particularly school-related values and perceptions of parental educational expectations, predicted rural youths’ gender-related aspirations. Focusing on African American adolescents in the Southeast, another study by Wood, Kurtz-Costes, and Copping ( 2011 ) used an expectancy-value framework to test a model linking parental expectations, youths’ motivation, and youths’ postsecondary educational progress. They found gender differences in the youths’ pathways to college, and findings highlighted the importance of academic motivation as a resource for African American boys along their educational trajectories. In another study, using the Michigan Study of Adolescent Life Transitions, Wang ( 2012 ) looked at the moderating influence of gender in a longitudinal analysis of classroom environment, motivational beliefs, high school course enrollment, and career aspirations. Consistent with prior research based on Eccles et al. ( 1983 ) expectancy-value theory, Wang reported that girls, compared to boys, reported lower math expectancies and intentions to consider careers in math-related fields, even though girls enrolled in just as many math courses, received relatively equivalent grades, and attached similar levels of task values to math as their male peers. Results of the study suggest that classroom influences may play a role in explaining these discrepancies. Taken together, these studies suggest that studies examining gender differences in educational attainment need to include a broad array of sociocultural influences that extend beyond personal beliefs related to academic competencies and values.

New Methodologies and Cross-Cultural Data

This section outlines several recent methodological approaches used by researchers to investigate gender and academic motivation. It also provides information on the proliferation of cross-national datasets researchers are using to explore patterns of gender-related academic motivation and achievement across cultures.

Person-Centered Approaches

Researchers studying gender and motivation continue to apply increasingly sophisticated quantitative and qualitative methodologies. Person-centered approaches, which take into account both the actual and relative level of one variable to another to form homogeneous groups, are used more and more in work on student motivation. Currently, these approaches are largely used to investigate motivation profiles and achievement (e.g., Conley, 2012 ; Luo, Paris, Hogan, & Luo, 2011 ; Wang & Peck, 2013 ). A recent study by Wang, Eccles, and Kenny ( 2013 ) performed latent profile analysis of math and verbal scores to create competence profiles of students. These researchers used profiles to predict occupations at age 33 and found that mathematically capable individuals who also exhibited high verbal skills were less likely to be in STEM careers, compared to individuals with high math skills and moderate verbal skills. Future work could use these new techniques to study gendered patterns of dropout, persistence, and choice. It is also important to continue utilizing mixed methods approaches to studying the more nuanced and layered influences of social context on motivation.

Using Cross-Cultural Data

Although several studies using cross-national data were mentioned at the beginning of this article, a large limitation of much of the gender-related achievement motivation work lies in its limited scope. Research on gender-related motivation patterns has generally stemmed from theory and empirical research generated in the United States and in other industrialized countries (e.g., England, Australia, Germany, and Canada). For example, Watt et al. ( 2012 ) examined how gender-related motivational processes affect high school mathematics participation, educational aspirations, and career plans using samples from Australia, Canada, and the United States. However, outside of these industrialized nations, and among more developing nations in particular, there is a dearth of information about the role of student motivation in schooling, especially as it relates to gender.

Some researchers have argued that the scarcity of cross-cultural research has led to Western models of achievement motivation, which are further criticized as being culturally entrenched in an ideology of individualism (Otsuka & Smith, 2005 ). Cross-national studies are beginning to arise and address whether current findings related to academic motivation and gender can be generalized across myriad nations and cultures (e.g., De Castella, Byrne, & Covington, 2013 ). This work is especially needed in developing nations.

This article on achievement motivation in education provided historical and contemporary overviews of theories of achievement motivation, discussed findings from research on gender and academic motivation both in the United States and abroad, and outlined current and future trends in research. Moving forward, these current and future trends in research include an altering and expanding of theoretical frameworks, an increased focus on the achievement and motivation of male students, and the proliferation of new methodologies (e.g., person-centered approaches) and sources of data (e.g., cross-national data). Theories of achievement motivation have significantly evolved over the last several decades, and research grounded in these theories influences and informs teaching practices, parent involvement activities in schools, and educational interventions targeted at students, administrators, teachers, and parents.

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Test Anxiety: An Integration of the Test Anxiety and Achievement Motivation Research Traditions

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• Published: 01 February 2023
• Volume 35 , article number  13 , ( 2023 )

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• Ser Hong Tan   ORCID: orcid.org/0000-0003-1735-6276 1 &
• Joyce S. Pang   ORCID: orcid.org/0000-0002-1105-3031 2  

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Test anxiety refers to a specific type of anxiety that is experienced in tests, exams, and other similar testing situations that evaluate one’s achievement. Research in test anxiety has been pursued under two traditions—the test anxiety and achievement motivation research traditions—more or less independently. The test anxiety research tradition is focused on the conceptualization and operationalization of test anxiety as a multidimensional construct. Under the achievement motivation research tradition, researchers who followed Atkinson’s research conceptualized test anxiety as a component of fear of failure while other researchers drew clear distinctions between the two constructs. The objective of this paper is to discuss the integration of the test anxiety and achievement motivation research traditions in order to further advance the understanding of the test anxiety construct. To this end, this paper begins with a brief review of the test anxiety and achievement motivation research traditions individually. The brief review highlights the lack of attention paid to the motivational component of test anxiety as a limitation of the test anxiety research tradition—this can be complemented by the achievement motivation research tradition which focuses on the motivational properties of test anxiety. We describe how the two traditions could be integrated by examining the relationships between the hope of success and test anxiety as well as by incorporating motivational properties into the test anxiety construct. The theoretical, research, and application implications of the integration of the two traditions are discussed.

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Tan, S.H., Pang, J.S. Test Anxiety: An Integration of the Test Anxiety and Achievement Motivation Research Traditions. Educ Psychol Rev 35 , 13 (2023). https://doi.org/10.1007/s10648-023-09737-1

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Formative vs. summative assessment: impacts on academic motivation, attitude toward learning, test anxiety, and self-regulation skill

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As assessment plays an important role in the process of teaching and learning, this research explored the impacts of formative and summative assessments on academic motivation, attitude toward learning, test anxiety, and self-regulation skill of EFL students in Iran. To fulfill the objectives of this research, 72 Iranian EFL learners were chosen based on the convenience sampling method assigned to two experimental groups (summative group and formative group) and a control group. Then, the groups took the pre-tests of test anxiety, motivation, and self-regulation skill. Then, one experimental group was trained by following the rules of the formative assessment and the other experimental group was taught according to the summative assessment. The control group was instructed without using any preplanned assessment. After a 15-session treatment, the post-tests of the test anxiety, motivation, and self-regulation skill were administered to all groups to assess the impacts of the instruction on their language achievement. Lastly, a questionnaire of attitude was administered to both experimental groups to examine their attitudes towards the impacts of formative and summative assessment on their English learning improvement. The outcomes of one-way ANOVA and Bonferroni tests revealed that both summative and formative assessments were effective but the formative one was more effective on academic motivation, test anxiety, and self-regulation skill. The findings of one sample t -test indicated that the participants had positive attitudes towards summative and formative assessments. Based on the results, it can be concluded that formative assessment is an essential part of teaching that should be used in EFL instructional contexts. The implications of this study can help students to detect their own weaknesses and target areas that need more effort and work.

Introduction

In teaching and learning, assessment is defined as a procedure applied by instructors and students during instruction through which teachers provide necessary feedbacks to modify ongoing learning and teaching to develop learners’ attainment of planned instructional aims (Robinowitz, 2010 ). According to Popham ( 2008 ), assessment is an intended procedure in which evidence of learners’ status is utilized by educators to adjust their ongoing instructional processes or applied by learners to change their present instructional strategies. Assessment intends to improve learning and it is used to reduce the gap between students’ present instructional situation and their target learning objectives (Heritage, 2012 ).

Two types of assessment are formative and summative. According to Glazer ( 2014 ), summative assessment is generally applied to give learners a numerical score with limited feedback. Therefore, summative assessment is commonly used to measure learning and is rarely used for learning. Educators can make the summative assessment more formative by giving learners the opportunity to learn from exams. This would mean supplying pupils with feedback on exams and making use of the teaching potentiality of exams. Wininger ( 2005 ) proposed an amalgamation of assessment techniques between summative assessment and formative assessment. This marriage between summative assessment and formative assessment is referred to as summative-formative assessment. Based on Wininger, summative-formative assessment is used to review the exam with examinees so they can get feedback on comprehension. Formative-summative assessment occurs in two primary forms: using a mock exam before the final or using the final exam before the retake.

Formative assessment allows for feedback which improves learning while summative assessment measures learning. Formative assessment refers to frequent, interactive assessments of students’ development and understanding to recognize their needs and adjust teaching appropriately (Alahmadi et al., 2019 ). According to Glazer ( 2014 ), formative assessment is generally defined as tasks that allow pupils to receive feedback on their performance during the course. In the classroom, teachers use assessments as a diagnostic tool at the termination of lessons or the termination of units. In addition, teachers can use assessments for teaching, by identifying student misconceptions and bridging gaps in learning through meaningful feedback (Dixson & Worrell, 2016 ). Unfortunately, numerous instructors consider formative assessments as a tool to measure students’ learning, while missing out on its teaching potential. Testing and teaching can be one or the same which will be discussed further in this research (Remmi & Hashim, 2021 ).

According to Black et al. ( 2004 ), using formative tests for formative purposes improves classroom practice whereby students can be encouraged in both reflective and active review of course content. In general terms, formative assessment is concerned with helping students to develop their learning (Buyukkarci & Sahinkarakas, 2021 ). Formative assessment can be considered as a pivotal and valid part of the blending of assessment and teaching (Ozan & Kıncal, 2018 ). Formative assessment helps students gain an understanding of the assessment process and provides them with feedback on how to refine their efforts for improvement. However, in practice, assessment for learning is still in its infancy, and many instructors still struggle with providing productive and timely feedback (Clark, 2011 ).

Using the mentioned assessments can positively affect the test anxiety of the students. Test anxiety signifies the extent to which the students experience apprehension, fear, uneasiness, panic tension, and restlessness while even thinking of forthcoming tests or exams (Ahmad, 2012 ). Anxiety can also be regarded as a product of hesitation about imminent events or situations (Craig et al., 2000 ). Test anxiety is the emotional reaction or status of stress that happens before exams and remains throughout the period of the exams (Sepehrian, 2013 ). Anxiety can commonly be connected to coercions to self-efficacy and evaluations of circumstances as threatening or reactions to a resource of stress to continue (Pappamihiel, 2002 ).

The other variable which can influence the consequences of tests or testing sessions in EFL settings is the attitudes of students towards English culture, English language, and English people. Kara ( 2009 ) stated that attitude about learning together with beliefs and opinions have a significant impact on learners’ behaviors and consequently on their performances. Those learners who have desirable beliefs about language learning are willing to rise more positive attitudes toward language learning. On the other hand, having undesirable beliefs can result in negative attitudes, class anxiety, and low cognitive achievements (Chalak & Kassaian, 2010 ; Tella et al., 2010 ). There are both negative and positive attitudes towards learning. Positive attitudes can develop learning and negative attitudes can become barriers to learning because students have these attitudes as they have difficulties in learning or they just feel that what is presented to them is boring. While a negative attitude toward learning can lead to poor performances of students, a positive attitude can result in appropriate and good performances of students (Ellis, 1994 ).

Woods ( 2015 ) says that instructors should regularly utilize formative assessment to advance the learners’ self-regulation skills and boost their motivation. Motivation is referred to the reasons why people have different behaviors in different situations. Motivation is considered as the intensity and direction of the students’ attempts. The intensity of attempt is referred to the extent that students try to reach their objectives and the direction of attempt is referred to the objectives that students intend to reach (Ahmadi et al., 2009 ; Paul & Elder, 2013 ). Motivation is an inborn phenomenon that is influenced by four agents such as aim (the aim of behaviors, purposes, and tendencies), instrument (instruments used to reach objectives), situation (environmental and outer stimulants), and temper (inner state of the organism). To reach their goals, people first should acquire the essential incentives. For instance, academic accomplishment motivation is significant to scholars (Firouznia et al., 2009 ).

Wiliam ( 2014 ) also asserts that self-regulation learning can be a crucial part of a productive formative assessment concerning the techniques of explaining, sharing, and understanding the instructional goals and students’ success and responsibility for their own learning. Self-regulation skill requires learners to dynamically utilize their cognitive skills; try to achieve their learning aims; receive support from their classmates, parents, and instructors when needed; and most significantly, be responsible for their own learning (Ozan & Kıncal, 2018 ). This research aimed to explore the impacts of using summative and formative assessments of Iranian EFL learners’ academic motivation, attitude toward learning, test anxiety, and self-regulation skill. This study is significant as it compared the effects of two kinds of assessments namely formative and summative on academic motivation, attitude toward learning, test anxiety, and self-regulation skill. As this research investigated the effects of the mentioned assessments on four emotional variables simultaneously, it can be considered as a novel study.

Review of the literature

In the field of teaching English as a foreign language, several researchers and experts defined the term “assessment” as a pivotal component of the process of teaching. According to Brown ( 2003 ), assessment is a process of collecting data about learners’ capabilities to conduct learning tasks. That is, assessment is the way instructors use to gather data about their methods and their pupils’ improvement. Furthermore, the assessment process has got an inseparable component from teaching, since it is impossible to think of teaching without assessments. Brown ( 2003 ) defined assessment in relation to testing. The differences between them refer to the fact that the latter occurs at an identified point of time while the former is an ongoing process that occurs regularly (Brown, 2003 ).

Other scholars explained the meaning of assessment by distinguishing it from evaluation. Regarding the difference between the two, Nunan ( 1992 ) asserted that assessment is referred to the procedures and processes whereby teachers determine what students can do in the target language and added evaluation is referred to a wider range of processes that may or may not include assessment data. In this way, then, assessment is process-oriented while evaluation is product-oriented. Palomba and Banta ( 1999 ) defined assessment as “the systematic collection, review, and use of information about educational programs undertaken to improve learning and development” (p.4). All in all, assessing students’ performances means recognizing and gathering information, receiving feedback, and analyzing and modifying the learning processes. The main goal, thus, is to overcome barriers to learning. Assessment is then used to interpret the performances of students, develop learning, and modify teaching (Aouine, 2011 ; Ghahderijani et al., 2021 ).

Two types of assessment are formative and summative. Popham ( 2008 ) said that it is not the nature of the tests to be labeled as summative or formative but the use to which that tests’ outcomes will be put. That is to say, the summative-formative manifestation of assessment does not stop at being a typology but it expands to be purposive due to the nature of assessment. Summative assessment, then, has been referred to as some criteria. Cizek ( 2010 ) suggests that two criteria can define the summative assessment: (1) it is conducted at the termination of some units and (2) its goal is mainly to characterize the performances of the students or systems. Its major goal is to gain measurement of attainment to be utilized in making decisions.

Through Cizek’s definition, a summative assessment seeks to judge the learners’ performances in every single course. Thus, providing diagnostic information is not what this type of assessment is concerned with. Significantly, the judgments made about the students, teachers, or curricula are meant to grade, certificate, evaluate, and research on how effective curricula are, and these are the purposes of summative assessment according to Cizek ( 2010 ).

According to Black and Wiliam ( 2006 ), summative assessment is given occasionally to assess what pupils know and do not know. This type of assessment is done after the learning has been finalized and provides feedback and information that summarize the learning and teaching process. Typically, no more formal learning is occurring at this stage, other than incidental learning that may happen via completing the assignments and projects (Wuest & Fisette, 2012 ). Summative assessment measures what students have learned and mostly is conducted at the end of a course of instruction (Abeywickrama & Brown, 2010 ; Liu et al., 2021 ; Rezai et al., 2022 ).

For Woods ( 2015 ), the summative assessment provides information to judge the general values of the instructional programs, while the outcomes of formative assessment are used to facilitate the instructional programs. Based on Shepard ( 2006 ), a summative assessment must accomplish its major purpose of documenting what learners know and can do but, if carefully created, should also efficaciously fulfill a secondary objective of learning support.

Brown ( 2003 ) claimed that summative assessment aims at measuring or summarizing what students have learned. This means looking back and taking stock of how well that students have fulfilled goals but does not essentially pave the way to future improvement. Furthermore, the summative assessment also known as assessment of learning is clarified by Spolsky and Halt ( 2008 ) who state that assessment of learning is less detailed, and intends to find out the educational programs or students’ outcomes. Thus, summative assessment is applied to evaluating different language skills and learners’ achievements. Even though summative assessment has a main role in the learners’ evaluation, it is not sufficient to know their advancement and to detect the major areas of weaknesses, and this is the essence of formative assessment (Pinchok & Brandt, 2009 ; Vadivel et al., 2021 ).

The term ‘formative assessment’ has been proposed for years and defined by many researchers. A clearer definition is provided by Brown ( 2003 ) in which he claims that formative assessment is referred to the evaluation of learners in the process of “forming” their skills and competencies to help them to keep up that growth process. It is also described as comprising all those activities conducted by instructors or by their learners that supply information to be utilized as feedback to adjust the learning and teaching activities in which they are involved (Fox et al., 2016 ).

Formative assessments aim to gain immediate feedback on students learning through which strengths and weaknesses of students can be diagnosed. Comprehensively, Wiliam ( 2011 ) suggests: Practices in the classrooms are formative to the extent that evidence about students’ accomplishments is elicited, interpreted, and utilized by instructors, students, or their classmates, to decide about the subsequent steps in the education that are probably to be better or better founded, than the decisions they would have taken in the absence of the evidence that was elicited.

Through this definition, formative assessment actively involves both students’ and teachers’ participation as a key component to develop students’ performance. The assessment for learning, which is based on the aim behind using it, is assessing learners’ progress (McCallum & Milner, 2021 ). Therefore, it is all about gathering data about learners’ achievement to recognize their progress in skills, requirements, and capabilities as their weaknesses and strengths before, during, and after the educational courses to develop students’ learning and achievement (Douglas & Wren, 2008 ).

Besides, Popham ( 2008 ) considered the formative assessment as a strategic procedure in which educators or pupils utilize assessment-based evidence to modify what they are presently performing. That describes it as the planned process that is not randomly occurring. Therefore, formative assessment is an ongoing procedure that provides learners with constructive timely feedback, helping them achieve their learning goals and enhancing their achievements (Vogt et al., 2020 ). Formative assessment is a helpful technique that can provide students with formative help by evaluating the interactions between assessment and learning (Chan, 2021 ; Masita & Fitri, 2020 ).

Some criteria related to formative assessment have been presented by Cizek ( 2010 ). In his opinion, formative assessment attempts to identify students’ levels whether high or low, to provide more help for educators to plan subsequent instruction, to make it easier for students to continue their own learning, review their work, and be able to evaluate themselves. To make learners responsible for their learning and do their research Formative assessment, to Cizek, is a sufficient tool and area for learners and teachers to make proficiency in the learning-teaching process. All in all, concerning specific objectives, formative assessment is a goal-oriented process.

Tahir et al. ( 2012 ) stated that formative assessment is a diagnostic use of assessment that can provide feedback to instructors and learners throughout the instructional process. Marsh ( 2007 ) claimed that formative tests are a type of strategy which are prepared to recognize students’ learning problems to provide a remedial procedure to develop the performances of the majority of the learners. The information that is provided for the learners should be utilized for the assessment to be explained as a formative one. The Assessment Reform Group (ARG) ( 2007 ) explains formative assessment as the procedure to look for and interpret the evidence for instructors and their students to make decisions about where the students fit in their learning, where they need to go, and how best to get there. Kathy ( 2013 ) also argued that formative tests aim to analyze the students’ learning problems to develop their academic attainment.

The theory that is behind our study is the sociocultural theory stating that knowledge is generated in a cooperative way within social contexts. It views learning as a condition wherein learners generate their meanings from the materials and content delivered to them, rather than trying to memorize the information (Vygotsky, 1978 ). Based on sociocultural theory, learning can occur successfully when teachers and students have more interactions with each other.

Some empirical studies are reported here. Alahmadi et al. ( 2019 ) aimed to examine whether a formative speaking assessment produced any effect on learners’ performances in the summative test. Besides, they aimed to observe students’ learning and to provide useful feedbacks that can be applied by educators to develop learners’ achievement and assist them to detect their weaknesses and strengths in speaking skills. Their results indicated that formative assessment helped Saudi learners to solve the problems they encounter in speaking tests.

Mahshanian et al. ( 2019 ) highlighted the significance of summative assessment in conjunction with teacher-based (formative) assessments on the learners’ performances. To do this study, 170 EFL students at the advanced level were chosen and grouped based on the kind of assessment they had received. The subjects in this research were administered exams for two main reasons. First, a general proficiency test was given to put the students at different levels of proficiency. Second, for comparing students’ development according to different kinds of assessments within a 4-month learning duration, an achievement test of the course was administered both as the pre-test and the post-test. The data gained via the scores of the participants on the achievement test received analyses and then compared by utilizing ANCOVA, ANOVA, and t- tests. Based on the outcomes of this research, we can conclude that an amalgamation of summative and formative assessments can result in better achievements for EFL students than either summative or formative assessments discretely.

Imen ( 2020 ) attempted to determine the effects of formative assessments on EFL learners’ writing skills. Indeed, the goal of this study was to recognize the effects of formative assessments on developing the writing skills of first-year master’s students at Abdel Elhamid Ibn Badis University, in Mostaganem. This research also attempted to reveal an essential issue that is the lack of the execution of formative assessments in the writing classrooms. To verify the hypotheses, two tools were applied in this study to gather the data, the teachers’ questionnaire and the students’ questionnaire. The findings of the study revealed that the formative assessment was not extensively used in teaching and learning writing skills, at the University of Mostaganem. The results of both questionnaires showed that if the students were evaluated formatively, their writing skills could be highly enhanced.

Ashdale ( 2020 ) attempted to examine the influences of a particular formative assessment named as Progress Trackers, by comparing a control group that did not receive the Progress Tracker with an experimental group that received the formative-based assessment. The research findings revealed that there were no substantial differences between the experimental and control groups based on the results of the pre-test and the post-test scores. While not statistically significant, the experimental group showed a larger increase in the learners with at least a 60% development in achievement. The lack of significant differences between the experimental group and the control group could be created by the uselessness of the formative assessments or the inability to exclude other factors in the class contexts. This could comprise the uses of other formative assessments applied in both groups, delivery of content, and execution of the formative assessments.

Persaud Singh and Ewert ( 2021 ) investigated the effects of quizzes and mock exams as a formative assessment on working adult learners’ achievement using a quasi-experimental quantitative design. One experimental group received both quizzes and mock exams, another group received mock exams only, and a control group received neither. The data gathered received analyses by utilizing t -tests and ANOVA. The findings indicated noticeable differences in the levels of achievement for the groups receiving formative assessments in comparison to the control participants. The “mock exam” group outperformed slightly than the “quizzes and mock exam” group.

Al Tayib Umar and Abdulmlik Ameen ( 2021 ) traced the effects of formative assessment on Saudi EFL students’ achievement in medical English. The research also tried to figure out teachers’ and students’ attitudes toward formative assessment. The participants involved in this research were 98 students selected among the Preparatory Year learners at a Saudi university. They were assigned to an experimental group and a control group. The experimental students were given their English for Specific Purposes (ESP) courses following the formative assessment techniques whereas the control group was trained in their ESP courses by traditional assessment rules. The experimental group teachers were given intensive training courses in Saudi Arabia and abroad on how to use formative assessment principles in the classrooms. At the end of the experiment that continued for 120 days, the control and experimental groups sat for the end of term examination which was designed for all candidates in the Preparatory College. Grades of all participants in the two groups in the final exam were compared. The performance of the experimental group was found to be meaningfully higher than that of the control group. Instructors’ and students’ attitudes towards formative assessment were positive.

Hamedi et al. ( 2022 ) investigated the effects of using formative assessment by Kahoot application on Iranian EFL students’ vocabulary knowledge as well as their burnout levels. This study was conducted on 60 participants who were in two groups of experimental and control. The results indicated that using formative assessment generated significant effects on of Iranian EFL students’ vocabulary knowledge.

In conclusion, the above studies confirmed the positive effects of summative and formative assessment on language learning. Yet, there are a few kinds of research on comparing the effects of the summative and formative assessments on Iranian EFL learners’ academic motivation, attitude toward learning, test anxiety, and self-regulation skill. Most studies in the domain of assessment examined the effects of the summative and formative assessments on the main skills (reading, speaking, writing, and listening) and they did not pay much attention to the psychosocial variables; therefore, this research posed two questions to cover the existing gap.

RQ1. Does using formative and summative assessments positively affect Iranian EFL learners’ test anxiety, academic motivation, and self-regulation skill?

RQ2. Do Iranian EFL learners present positive attitudes toward learning through formative and summative assessments?

Methodology

Design of the study, participants.

The participants of this research were 72 Iranian EFL students who have studied English since 2016. The male EFL learners were selected based on the convenience sampling method by administering the Preliminary English Test (PET). They were selected from the Parsian English language institute, located in Ahvaz city, Iran. The participants’ general English proficiency was intermediate and their age average was 21 years old. The participants were divided into two experimental groups (summative and formative) and a control group.

Instrumentations

For homogenizing the subjects in terms of general English proficiency, we gave a version of the PET test, extracted from the book PET Practice Test (Quintana, 2008 ). Because of some limitations, only the sections of reading, grammar, and vocabulary of the test were used in this study. We piloted the test on another similar group and allotted 60 min for answering all its items. Its validity was accepted by some English experts and its reliability was .91.

Britner and Pajares’ ( 2006 ) Science Anxiety Scale (SAS) was used as the other instrument to assess the participants’ test anxiety. Some wordings of the items were changed to make them suitable for measuring test anxiety. There were 12 items in this test that required the participants to consider the items (e.g., I am worried that I will get weak scores in most of the exams) and answer a 6-point scale ranging from certainly false to certainly true. Based on Cronbach’s alpha formula, the reliability index of the anxiety test was .79.

The other tool used in this study was the Self-Regulatory Strategies Scale (SRSS) which was developed by Kadıoğlu et al. ( 2011 ) to assess the self-regulation skills of the participants. The SRSS was a 6-point Likert instrument including never, seldom, occasionally, often, frequently, and constantly. The SRSS consisted of 29 statements in eight dimensions. The results of Cronbach’s alpha formula showed that the reliability of the SRSS was .82.

We used the Attitude/Motivation Test Battery (AMTB) of Gardner ( 2004 ) to evaluate the respondents’ English learning motivation. This measuring instrument had 26 items each with six responses: Highly Disagree, Moderately Disagree, Somewhat Disagree, Somewhat Agree, Moderately Agree, and Highly Agree. We used the Cronbach alpha to measure the reliability of the motivation questionnaire ( r = .87). It should be noted that the motivation questionnaire, the SAS, and the SRSS were used as the pre-tests and post-tests of the research.

The last tool employed in this research was an attitude questionnaire examining the participants’ attitudes towards the effectiveness of summative and formative assessment on their English learning enhancement. The researchers themselves created 17-point Likert- items for this questionnaire and the reliability of this instrument was .80. Likert scale was utilized in the questionnaire to show the amount of disagreement and agreement from 1 to 5 that were highly disagree, disagree, no idea, agree, and highly agree. The validities of all mentioned tools were substantiated by a group of English specialists.

Collecting the needed data

To start the study, first, the PET was administered to 96 EFL learners and 72 intermediate participants were selected among them. As stated previously, the participants were divided into two experimental groups (summative and formative) and one control group. After that, the pretests of test anxiety, motivation, and self-regulation skill were administered to the participants of all groups. After pretesting process, the treatment was conducted on the groups differently; each group received special instruction.

One experimental group was instructed based on the rules of the formative assessment, in the formative group, the teacher (researcher) assisted the students to participate in evaluating their learning via using self and peer assessment. Besides, the teacher’s comprehensive and descriptive elicitation and feedbacks of information about students’ learning were significant in formative class. In fact, there were no tests at the termination of the term and the teacher was flexible concerning the students’ mistakes and provided them with constructive feedback including metalinguistic clues, elicitation, correction, repletion, clarification request, recast, and repletion.

In the summative class, the teacher assessed the students’ learning by giving mid-term and final exams. The teacher did not provide any elaborative feedback, and his feedback was limited to yes/no and true/ false. The control group neither received a formative-based instruction nor a summative-based instruction. The teacher of the control group instructed them without utilizing any preplanned assessments. They finished the course without any formative and summative assessments. After the treatment, the post-tests of the test anxiety, motivation, and self-regulation skill were given to all groups to assess the influences of the intervention on their language achievement. In the final step, the questionnaire of attitude was distributed among both experimental groups to check their opinions about the impacts of summative and formative assessment on their English learning improvement.

The whole study lasted 23 sessions; each took 50 min. In one session, the PET test was administered and in the next three sessions, three pre-tests were conducted. During 15 sessions, the treatment was carried out; in three sessions, three post-tests were given to the participants, and in the last session the attitudinal questionnaire was administered to examine the participants’ attitudes towards the effectiveness of summative and formative assessment of their English learning achievement.

Data analysis

Having prepared all needed data via the procedures mentioned above, some statistical steps were taken to provide answers to the questions raised in this study. First, the data were analyzed descriptively to compute the means of the groups. Second, some one-way ANOVA and Bonferroni tests were used for analyzing the data inferentially. Third, one sample t- test was utilized to analyze the motivation questionnaire data.

Results and discussion

After checking and getting sure about the normality distribution of the data by using the Kolmogorov-Smirnov test, we used several one-way ANOVA tests and reported their results in the following tables:

As we see in Table 1 , the mean scores of all groups are almost similar. They got almost equal scores on their anxiety pre-test and the three groups were at the same level of anxiety before conducting the instruction. This claim is verified in the following table with the help of one-way ANOVA.

According to the Sig value in Table 2 , there is not a noticeable difference between the test anxiety of all three groups. They were at the same anxiety level at the outset of the study. The inferential statistics show that all the participants had an equal amount of anxiety before they had received the treatment.

As is seen in Table 3 , the mean scores of all groups are different on the anxiety post-tests. Based on the descriptive statistics, the groups gained different scores on their anxiety post-test and the experimental groups obtained better scores than the control group. This claim is substantiated in the following table by using a one-way ANOVA test.

Table 4 depicts that the Sig value is less than .00; accordingly, one can conclude that there is a noticeable difference between the test anxiety post-tests of all three groups. They were at different anxiety levels at the end of the research. It seems that the experimental groups outdid the control group on the post-test.

In Table 5 , the test anxiety level of all groups is compared. This table shows that there are remarkable differences between the anxiety post-tests of the control group and both experimental groups. Also, this table shows that the formative group outdid the control and summative groups. The formative group had the best performance among the three groups of this study.

As observed in Table 6 , all three groups’ performances on the self-regulation pre-tests are almost the same; their mean scores are almost equal. We used a one-way ANOVA to check the groups’ performances on the self-regulation pre-tests.

In Table 7 , the inferential statistics of all groups on the self-regulation pre-tests are shown. As Sig (.96) is higher than (0.05), the differences between the three groups are not meaningfully significant. Based on this table, all three groups had the same level of self-regulation ability at the outset of the study.

The mean scores of the control group, the summative group, and the formative group are, 80.12, 130.04, and 147.25, respectively (Table 8 ). At the first look, we can say that both experimental participants outflank the control participants since their mean scores are very higher than the mean score of the control group.

The results indicate significant differences between the self-regulation post-tests of the groups in favor of the experimental groups (Table 9 ) . Based on the inferential statistics, the performances of the three groups on the self-regulation post-test are different and the summative group and the formative group outflank the control group.

The outcomes in Table 10 indicate that both experimental groups have better performances than the control group on the self-regulation post-tests. Also, the findings show that the formative group performed better than the other two groups. The treatment had the most effect on the formative group.

The control group’s mean score is 90.33, the mean score of the summative group is 91.75, and the mean score of the formative group is 92.45 (Table 11 ). Accordingly, we can say that the three groups had an equal degree of motivation before conducting the treatment.

Table 12 presents the inferential statistics of all groups on the motivation pre-tests. One can see that Sig (.94) is larger than 0.50; consequently, no difference is observed among the groups in terms of motivation pre-tests. The inferential statistics show that the students of the three groups had the same amount of motivation before they had received the treatment.

As shown in the Table 13 , the mean scores of the summative and formative groups are 115.79 and 127.83, respectively, on the motivation post-tests and the mean of the control group is 92.87. It appears that the experimental participants outperform the control participants on the motivation post-tests as their mean scores are higher than the control group.

In Table 14 , the inferential statistics of all groups on the motivation post-tests are revealed. The Sig value (.00) is less than 0.50; therefore, the differences between the groups are significant. Indeed, the experimental groups outperformed the control group after the instruction and this betterment can be ascribed to the treatment.

The mean scores of the motivation post-tests are compared in Table 15 . Accordingly, there are noticeable differences between the post-tests of all groups. The formative participants had better performance than the other two groups. We can say that the formative assessment is more effective than the summative assessment in EFL classes.

As depicted in Table 16 , the amount of statistic T -value is 63.72, df =16, and Sig =0.00 which is less than 0.05. This implies that Iranian students held positive attitudes towards the effectiveness of summative and formative assessments on their language learning improvement.

Briefly, the results indicate that both experimental groups had better performances than the control group in their post-tests. The formative group had the best performance among the three groups of this study. Additionally, the results reveal that the participants of the present research had positive attitudes towards the effectiveness of both formative and summative assessments on their language learning development.

After analyzing the data, it was found that all three groups were at the same levels of test anxiety, motivation, and self-regulation skill at the outset of the research. But, the performances of the three groups were different at the end of the investigation. Both experimental groups outdid the control group on their post-tests and the formative group performed better among the three groups. Although both types of assessments (summative and formative) were effective on test the anxiety, motivation, and self-regulation skill of EFL learners, the formative assessment was the most effective one. The findings of the current research also indicated that both experimental groups presented positive attitudes toward the implementation of the summative and formative assessments in EFL classes.

The findings gained in this study are supported by Persaud Singh and Ewert ( 2021 ) who inspected the impacts of formative assessment on adult students’ language improvement. They indicated that there were meaningful differences between the formative participants and the control participants in terms of language achievement in favor of the formative participants. Additionally, our research findings are advocated by Alahmadi et al. ( 2019 ) who explored the effects of formative speaking assessments on EFL learners’ performances in speaking tests. They showed that the formative assessment assisted Saudi EFL learners to solve the problems they encountered in speaking tests.

In addition, our study findings are in accordance with Mahshanian et al. ( 2019 ) who confirmed that the amalgamation of summative and formative assessment can result in better achievement in English language learning. Also, our investigation lends support to the findings of Buyukkarci and Sahinkarakas ( 2021 ) who verified the positive effects of using formative assessment on learners’ language achievement. Additionally, the results of the current research are in agreement with Ounis ( 2017 ) who stated that formative assessment facilitated and supported students’ learning. Our study findings are supported by the sociocultural theory which focuses on the role of social interactions among the students and their teachers in the classroom. Based on this perspective, the learning process is mainly a social process and students’ cognitive functions are made based on their interactions with those around them.

Furthermore, our research results are in agreement with the results of Imen ( 2020 ) who discovered the impacts of formative assessments on EFL students’ writing abilities. His results indicated that using formative assessment develops the participants’ writing skills. Moreover, our research outcomes are supported by the impacts of formative assessments on learners’ academic attainment, opinions about lessons, and self-regulation skills in Ozan and Kıncal ( 2018 ) who performed an investigation on the influences of formative assessments on students’ attitudes toward lessons, academic achievement, and self-regulation skill. They revealed that the experimental class that received the treatment by formative assessment practices had better academic performances and more positive attitudes towards the classes than the control class.

Regarding the positive attitudes of the participants towards formative and summative assessment, our results are in line with Tekin ( 2010 ) who discovered that formative assessment practices meaningfully developed students’ attitudes about mathematics learning. That research indicated that the participants in the treatment group had positive attitudes about mathematics learning. In addition, King ( 2003 ) asserted that the formative assessments enhanced the learners’ attitudes about science classes. Also, Hwang and Chang ( 2011 ) revealed that the formative assessment highly boosted the attitudes and interest of students toward learning in local culture classes.

One explanation for the outperformance of the formative group over the other two groups can be the fact that they received much more input. They were provided with different kinds of feedback and took more exams during the semester. These exams and feedback can be the reasons for their successes in language achievement. This is in line with Krashen’s ( 1981 ) input theory stating that if students are exposed to more input, they can learn more.

The other possible explanations for our results are that formative assessments are not graded so they take the anxiety away from the assessees. They also detach the thinking that they must get everything right. Instead, they serve as a practice for students to get assistance along the way before the final tests. Teachers usually check for understanding if students are struggling during the lesson. Teachers address these issues early on instead of waiting until the end of the unit to assess. Teachers have to do less reteaching at the end because many of the problems with mastery are addressed before final tests. The mentioned advantages can be the reasons for our obtained findings.

In addition, monitoring the students’ learning via using the formative assessment can be the other justification for our results. In fact, monitoring the learning process can provide an opportunity for the teachers to give constructive feedback to their students to improve their language learning. When teachers continuously monitor students’ growth and modify instruction to ensure constant development, they find it easier and more predictable to progress towards meeting the standards on summative assessments. By comprehending precisely what their students know before and during the instruction, teachers have much more power to improve the students’ mastery of the subject matter than if they find out after a lesson or unit is complete.

It is important to point out that when instructors continually evaluate the development of their students and modify their curriculum to assure constant improvement, they find that it is simpler and more predictable to make progress toward fulfilling the requirements on summative assessments. If teachers wait until the end of a session or unit to find out how well their learners have mastered the material, they will have considerably less influence over how well their learners learn the material than if they find out how well their learners have mastered it earlier and during teaching. The value of formative assessment lies in the critical information about student comprehension that it provides throughout the process of learning, as well as the chance it gives educators to provide participants with quick and efficient, and action-oriented feedback, as well as the chance to alter their own behavior so that every respondent has the chance to learn and re-learn the material. Learners whose academic performance falls on the extreme ends of the normal curve, such as those who are struggling and those who excel academically, benefit the most from formative evaluation. These learners have learning requirements that are often one of a kind and highly specialized, and to meet those needs, the instructor needs updated data. In addition, making use of frequent formative evaluation as a means to remediate learning gaps brought up by COVID-19 guarantees that educators can promptly give remediation.

The other justification for our findings can be ascribed to the strength of formative assessments that lies in the formative information they provide about the students’ comprehension throughout the learning process and the opportunities they give to teachers to provide the pupils with action-oriented and timely feedback and to change their own behaviors so that each learner has an opportunity to learn and re-learn. More particularly, using formative assessment can assist the students to detect their own weaknesses and strengths and target areas that need more effort and work. All the positive points enumerated for the formative assessments can be the reasons and explanations for the results gained in the current research.

Moreover, the better performance of assessment groups may be due to numerous reasons. In the first place, consistently evaluating students’ progress helps maintain learning objectives at the forefront of one’s mind. This ensures that learners have a distinct goal to strive towards and that instructors have the opportunity to assist clear up misconceptions before learners get off track. Second, engaging in the process of formative assessment enables instructors to gather the information that reveals the requirements of their students. When instructors have a clear grasp of what it takes for their students to be successful, they are better able to design challenging educational environments that push every learner to their full potential. Thirdly, the primary role of formative assessment that will assist in enhancing academic achievement is to provide both learners and instructors with frequent feedback on the achievement that is being made toward their objectives. Learners can bridge the gap between their existing knowledge and their learning objectives through the use of formative assessment (Greensetin, 2010 ). The fourth benefit of doing the formative assessment is an increase in motivation. Formative assessment entails creating learning objectives and monitoring the progress towards those objectives. When learners have a clear idea of where they want to go, their performance dramatically improves. Fifthly, students must identify a purpose for the work that is assigned to them in the classroom. Connecting the learning objectives with real-world problems and situations draws students into the instructional activities and feeds their natural curiosity about the world. Sixthly, an in-depth examination of the data gathered via formative assessment provides the educator with the opportunity to investigate their own methods of teaching and identify those that are successful and those that are not. It is indeed possible that some of the strategies that work for one group of learners won’t work for another. Lastly, students become self-regulated when they are provided with the tools they need to set, track, and ultimately achieve their own learning objectives. Students may develop into self-reliant thinkers if they are exposed to models of high-quality work and given adequate time to reflect on and refine their own work.

The positive effects of formative and summative assessment on students’ motivation are supported by The Self Determination Theory (SDT) of Motivation which is a motivational theory that provides a way of understanding human motivation in any context (Ryan & Deci, 2000 ). SDT attempts to understand human motivation beyond the simple intrinsic/extrinsic model. It suggests that human motivation varies from fully intrinsic motivation, which is characterized by fully autonomous behavior and “for its own sake” to fully extrinsic motivation, which is characterized by behavior that is fully heteronomous and which is instrumentalized to some other end.

In this study, the self-regulatory skills of the students in the EGs where the formative assessment practices were applied did significantly differ from the ones in the CG where no formative assessment practices were applied. Thus, students’ self-regulation was shown to be improved as a result of formative assessment procedures. Similar findings were observed in the experimental research by Xiao and Yang ( 2019 ) that compared the self-regulation abilities of EG and CG learners in secondary school and discovered a substantial difference in favor of the former group. Research findings based on qualitative data reveal that learners engaged in a variety of cognitive techniques and self-regulatory learning practices. The participants acknowledged that they were an integral part of their own learning and that they accepted personal responsibility for their progress. Teachers reported that learners’ ability to self-regulate improved as a result of formative assessment, which fostered ongoing, meaningful, and learning-effort and performance-focused dialogue between teachers and learners. The students’ progress in the areas of self-regulation and metacognitive abilities, as well as their growth in accordance with educational standards, may be supported by a rise in their success in diagnostic examinations thanks to the use of formative assessment (DeLuca et al., 2015 ). In a study that he conducted in 2015, Woods examined the link between formative assessment and self-regulation. He highlighted that teachers who use formative assessment strategies need to comprehend the participants’ self-regulatory learning processes to make appropriate decisions for their classrooms. Furthermore, Woods ( 2015 ) recommended that educators make regular use of formative assessment to foster the growth of learners’ abilities to self-regulate and to boost the motivation levels of their learners. Wiliam ( 2014 ) also asserted that self-regulatory learning could be an important component of an effective formative assessment in relation to the techniques of explaining, sharing, and comprehending the learning goals and success criteria and students taking the responsibility for their own learning.

It is vital to note that learners who have developed self-regulation skills employ their cognitive abilities; work toward their learning objectives; seek out appropriate support from peers, adults, and authority figures; and, most significantly, accept personal accountability for their academic success. As a result, learners’ abilities to self-regulate have a direct effect on the type of formative assessment based on learning and the applications designed to eliminate learning deficiencies. Self-regulation is an ability that needs time and practice to acquire, but it is possible to do so with the right tools and a continuous strategy. Formative assessment techniques were shown to boost learners’ ability to self-regulate, although this effect was found to be small when the study findings were combined with those found in the literature. This finding may be attributed to the fact that, although formative assessment procedures were implemented for an academic year, they were limited to the context of the social research classroom, and students’ abilities to self-regulate may develop and evolve over time.

The findings of this research can increase the knowledge of the students about two types of assessment. This study can encourage students to want their teachers to assess their performances formatively during the semester. Also, the findings of this study can assist instructors to implement more formative-based assessments and feedback in their classes. This study can highlight the importance of frequent input, feedback, and exam for teachers. An exact analysis of formative assessment data permits the teachers to inspect their instructional practices in order to understand which are producing positive results and which are not. Some that are effective for one group of students may not be effective for another group. The implications of this research can help students try to compensate for their deficiencies by taking responsibility for their own learning instead of just attempting to get good grades. In this respect, formative assessments ensure that students can manage the negative variables such as a high level of examination and grading.

Using formative assessments helps teachers gather the information that reveals the students’ needs. Once teachers have an understanding of what students need to be successful, they can generate a suitable learning setting that will challenge each learner to grow. Providing students and teachers with regular feedback on progress towards their aims is the major function of the formative assessments that will help in increasing academic accomplishment. Formative assessments can help the students close the gap between their present knowledge and their learning objectives. Moreover, using formative assessment gives the students evidence of their present progress to actively monitor and modify their own learning. This also provides the students the ability to track their educational objectives. Also, via using formative assessment, the students have the ability to measure their learning at a metacognitive level. As the students are one of the main agents of the teaching-learning process, instructors must share the learning objectives with them. This sharing can develop the students’ learning in basic knowledge and higher order cognitive processes such as application and transfer (Fulmer, 2017 ). In fact, if learners know that they are expected to learn in that lesson, they will concentrate more on those areas. Formative assessments make the teaching more effective by guiding learners to achieve learning objectives, setting learning needs, modifying teaching accordingly, and increasing teachers’ awareness of efficient teaching methods. Lastly, our findings may aid material developers to implement more formative-based assessment activities in the EFL English books.

In conclusion, this study proved the positive impacts of applying formative assessments on Iranian EFL students’ academic motivation, attitude toward learning, test anxiety, and self-regulation skill. Therefore, teachers are strongly recommended to use formative assessment in their classes to help students improve their language learning. Using formative assessment allows teachers to modify instruction according to the results; consequently, making modifications and improvements can generate immediate benefits for their students’ learning.

One more conclusion is that using formative assessment gives the teacher the ability to provide continuous feedback to their students. This allows the students to be part of the learning environment and to improve self-assessment strategies that will help with the understanding of their own thinking processes. All in all, providing frequent feedback during the learning process is regarded as an efficient technique for motivating and encouraging students to learn a language more successfully. Indeed, by assessing students during the lesson, the teachers can aid them to improve their skills and examine if they are progressing or not. Thus, formative assessment is an essential part of teaching that should be used in EFL instructional contexts.

As we could not include many participants in our study, we recommend that future researchers include a large number of participants to increase the generalizability of their results. We worked on male EFL learners; the next studies are required to work on both genders. We could not gather qualitative data to enrich our results; the upcoming researchers are advised to collect both quantitative and qualitative data to develop the validity of their results. Next researchers are called to examine the effects of the summative and formative assessments on language skills and sub-skills. Also, next researchers are offered to inspect the effects of other types of assessments on language skills and subskills as well as on psychological variables involved in language learning.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

English as a foreign language

Analysis of variance

Preliminary English Test

Science Anxiety Scale

Self-Regulatory Strategies Scale

Attitude/Motivation Test Battery

Self Determination Theory

Experimental group

Control group

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Seyed M. Ismail is an assistant professor at Prince Sattam Bin Abdulaziz University, Saudi Arabia. His research interests are teaching and learning, testing, and educational strategies. He published many papers in different journals.

D. R. Rahul is an assistant professor School of Science and Humanities, Shiv Nadar University Chennai, Chennai, India. He has published several research papers in national and international language teaching journals.

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Ehsan Rezvani is an assistant professor in Applied Linguistics at Islamic Azad University, Isfahan (Khorasgan) Branch, Isfahan, Iran. He has published many research papers in national and international language teaching journals.

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Achievement Motivation

Updated 12 December 2023

Subject HR Management ,  Learning ,  Child Development

Downloads 56

Category Business ,  Education ,  Psychology

Topic Performance ,  Motivation

How Achievement Motivation is affected by Socioeconomic Background, Race, and Family Structure

Motivation is defined as the driving force behind an individual's actions, which can facilitate achievement of goals. People tend to take risk and perform dangerous activities to meet their needs and fulfill their interests. One expects negative and positive feedbacks, therefore, need to be motivated to ensure achievement of the objectives or self-satisfaction. Achievement motivation is the desire to perform better and acquire unique accomplishment, compete with the set standards of excellence, and involve with achievement goals that are long-term (Kavita " Malipatil, 2016). Achievement motivation constitutes the behaviors towards development and demonstration of higher capabilities by people. An individual is aware that he/she has the responsibility of a particular outcome and has to work hand to produce desired results. The goal is always to succeed and record good performance against the standards of excellence or in comparison to other competitors. People differ in strength and motive to achieve while challenges vary in the risk they pose as well as the opportunities they offer. The motivation for success in something is affected by personality and environmental factors. Achievement motivation is influenced by various factors such as social, economic status, race, as well as family structure.

Social, economic status and Achievement motivation

Social, economic status of an individual is the measure of work experience and the family's economic and social state about other people about income, occupation, and education. The household income is an important determiner of one's socioeconomic status since it determines several aspects such as quality of education and the career of an individual. For instance, in families with higher income, education is of great importance but in more impoverished areas food is of concern that is more significant. Kavita and Malipatil (2016) argue that social, economic status is essential in determining the behavior of an individual. The social conditions, which a person interacts with, provide a framework for the acquisition of values, practices, as well as procedures of some activities. The environment helps in developing unique personality traits that constitute the driving force to achieve some set goals. For instance, in sport, the social-economic background of players affects characteristics such as achievement motivation extensively. If one comes from a society that is renowned for sporting activities or produced great sports personalities, there is a higher possibility of such an individual having great interest in sports. Kavita and Malipatil (2016) found out that sportswomen from low socio-economic status possess high achievement motivation compared to those from high SES. The family can have a significant impact on members’ motivation by providing feelings of security, affection, as well as economic sufficiency.

Race and Achievement motivation

The race is another determiner of achievement motivation, and any discrimination has a negative impact on the individual. People from minority races face several challenges in life due to harmful stereotypes they suffer from their colleagues belonging to the majority races. Racial prejudice may occur in schools, communities, and among peers affecting their mental health outcomes (Wood " Graham, 2010). This, in turn, affects achievement of the motivation of various individuals in activities they undertake. The stress from racial discrimination can explain for the existence of persistent gaps in performance in various fields such as academics, athletics, and sports. This may be due to reduced achievement motivation by discriminated individuals who feel prejudiced. Individuals from the black minority race are likely to be less motivated in achieving specific goals if they feel that their white counterparts are exposed to better privileges. The perception that one may be treated differently or in an unfair way due to race leads to the stress of experiencing negative expectations about the ethnic group (Wood " Graham, 2010). Although some people may develop strategies to deal with the pain of racial discrimination, self-motivation and desire to achieve their goals may be affected negatively.

Family Structure and Achievement motivation

The family structure can be of significant influence to children's achievement motivation depending on the parenting style. Modern parenting styles can affect children achievement motivation in various fields including academic and co-curricular activities. Some parents are highly controlling while others are quite relaxed during parenting. For instance, some children are forced to go through music lessons and regimented academics in which children are shamed in case of underperformance. Achievement motivation in such families is meant to please parents as well as ensure satisfaction of cultural norms rather than benefit a child (Chakraborty, 2017). Some parents connect with their children very well by getting involved in their kids’ experiences and issues. However, being overprotective to children can make them hesitate to overcome challenges and less motivated. Whenever kids feel that their parents are always there, they can become less motivated to do something by themselves thus may not set their targets. Parents have a significant role in fostering independence and achievement motivation to their children. The family set up can be of considerable influence to growing children thus a right environment will be of more benefits (Chakraborty, 2017). Being open and discussing issues affecting family members is a right way of encouraging kids to venture out on their own and discover their strengths and weaknesses.

Implications

Motivation is the driving force in achieving targets as it provides a critical foundation for planning, organization, as well as decision-making in individuals. Achievement is a task-oriented behavior as individual performance is accessed against some set standards to determine the level of accomplishment. Achievement motivation combines two personality variables that include the tendency to approach success and to avoid failure (Wood " Graham, 2010). It allows people to steer towards targets and dominate challenging tasks that will enable them to get quality results. Achievement motivation makes it possible for people to pursue jobs that they feel that they are valuable in their lives. It is an essential aspect of schools, sports, and careers since it facilitates positive results by individuals. Individuals that fail to achieve their targets record poor performance as well as failure to enjoy their everyday life. Besides, some may experience stress and withdrawal, which can affect their emotional well-being.

Motivation achievement involves personal strive for particular goals and a profound driving force to engage in some tasks for personal accomplishment. Several factors affect motivation desire to achieve, which include socio-economic and social factors, family structure, and race. Each of them can have the different effect on an individual depending on the perception. For instance, a strict family upbringing may make a child more focused to achieve goals while others can rebel against parental control. Achievement motivation is associated with hard work in various fields such as education, sports, and careers since it can influence individuals' performance.

Chakraborty, J. (2017). A Study of Family Relation Structure Stress and Achievement Motivation of Higher Secondary Students.

Kavita, S. H., " Malipatil, R. P. (2016). Influence of Socio-Economic Status on Achievement Motivation of Sports Women. International Journal of Physical Education, Sports and Health 2016; 3(6): 440-442.

Wood, D., " Graham, S. (2010). Why Race Matters: Social Context and Achievement Motivation in African American Youth. In The Decade Ahead: Applications and Contexts of Motivation and Achievement (pp. 175-209). Emerald Group Publishing Limited.

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What motivates me? Take the Motivation Test

Understanding your underlying motivations can have a bigger impact on your life than providing a decent answer to a cliche interview question.

Motivations are highly individual so how exactly do you determine what it is that motivates you? Our motivation test analyze your existing behaviors so you can understand exactly what will set your motivation on fire.

41 Hacks to Get Seriously Motivated

Pouring over the latest research in human motivation we've compiled 41 ways for you to become seriously driven. During our research we discovered many old fashion ideas used to increase motivation end up doing the opposite. Finding motivation may be as much about implementing new patterns as it is about killing old ones you currently believe are helping. If you've found it difficult to maintain motivation or want to find new levels of drive read on.

• Find Purpose

Find a way to work on something you find meaningful. Motivation will constantly become a struggle if you find little meaning in applying effort while it will feel almost self perpetuating when your work has legitimate meaning to you. Make your work matter.

When you discover your mission, you will feel its demand. It will fill you with enthusiasm and a burning desire to get to work on it.

• Become a Master

People that feel a sense of improvement in skills tend to be more motivated . Chunk your tasks into small manageable segments and reward yourself at every stage with rewards that correspond to the size and level of achievement you've attained. Motivation is easier to come by when you get to make progress.

• Sprint, Rest, Sprint

Our minds are not designed to maintain focus for hours and hours upon end. Instead treat your work as a series of short sprints and learn how to rest in between.

• Completely Immerse Yourself - Flow

Find a way to make your tasks fun and exciting and give it your all. Become emotionally engaged and committed to perfection. Do this well enough and you'll find yourself in a state of 'flow'. During the state of flow people often lose the perception of time and motivation becomes completely effortless. Check out how to achieve the state of flow here .

• Relax when Motivation Subsides

Like all states motivation will vary depending upon our mood, health and many factors beyond our immediate control. Don't sweat it, your motivation will return and a rest may be the best way to come about it.

• Financial Rewards Don't Work

Behavioral research has demonstrated a seemingly counter intuitive idea. Extrinsic rewards such as money do not increase performance in tasks requiring creativity, in fact they tend to produce poorer performance. If the work you're attempting to find motivation for is a manual task then financial incentives can boost motivation and performance. Check out the Dan Pink video below to see how to motivate yourself for tasks requiring creativity.

• Be an Optimist

Your motivation to complete a task improves if you hold a more optimistic outlook for the results of your efforts. Take a look at our test to determine if you're optimistic and further research on the benefits of being optimistic. Yes, optimism can be learned.

Optimism is the faith that leads to achievement. Nothing can be done without hope and confidence.

• Be Realistic Too

Many modern positive psychology books advocate visualisng your life having attained your success. The theory is that your brain will go to work on pulling you toward this vision. What the research actually shows is the opposite. The flaw in the theory seems to be that these long term visions do little to impact more immediate levels of motivation. They also fail to prepare you for the associated challenges and pitfalls you'll encounter. Long term goals are great but they must come with the acceptance of overcoming challenges. Go back to tip 2 for the right way to approach your goals.

• Specific Goals beat 'Do your Best'

While the value of this tip has been a little overstated the research does back the claim that writing specific goals improves levels of motivation.

• Spend your Willpower Wisely

Many psychologist are beginning to think of willpower as an energy system . Each difficult or arduous task you complete makes a withdrawal from the pool of available willpower energy. It's known as Ego Depletion . Aggressive dieting, detrimental relationships, breaking a habit and anything which you perceive as difficult deplete the levels of willpower energy we have available. If you're finding it difficult to muster the motivation for a task can you find willpower energy from other parts of your life which may be depleting it?

• Is Fear Killing Motivation?

In order to be motivated to do something you need to believe that your efforts will lead to your goal. This often involves a risk of failure and loss of something you might already have. Is your fear reasonable? Is the effort likely to lead to reward and what can you do to improve your chances?

I can accept failure, but I can't accept not trying.

• Create a To Don't List

You found motivation and started out brilliantly but somehow ended up spending too much time on Facebook once again. The day is lost and your sense of achievement and accomplishment is gone. Now you're not feeling quite so motivated. This is a common scenario and a perfect reason to create a "To Don't List". What has sidetracked you in the last month? What has it kept you from achieving. Write out your list and stick it to your monitor.

• Signs Multiple Motivation

Researchers were able to get more people to take the stairs simply by printing out signs encouraging them to do so . Once you've established the most effective methods for motivating yourself place visual cues where you most need them.

• Have a Backup Plan

Disaster, challenges and setbacks are all inevitable and a part of everyone's lives and potential motivation killers. Research has shown our ability to respond to these situations greatly improves if we set out a plan for responding to these events. Maintain your motivation by creating a plan for all scenarios.

I am prepared for the worst, but hope for the best

• Use the Energy Hack

Point 10 talked about the science of Willpower as energy. How do you replenish your available levels of energy? Well just spending a few moments away from the task at hand is not enough. Research has shown your energy levels are restored when you spend time on something you find genuinely interesting. It doesn't need to be easy, relaxing or related to anything in particular, it just needs to be intensely interesting to you. Work for 20 minutes and then take 5 on something you find interesting and watch your energy levels rebound.

• Create a Rivalry

Competition increases motivation when we believe we have a decent chance of winning. Research has shown students taking the SAT's in room of 10 people will outperform students taking the test in a group of 100 . Competition doesn't work for everyone and tends to be more effective in motivating men . Pro Tip: Testosterone levels of athelets increase when the competitive rival is despized.

• Scrap Motivation and Use Habits

Many of our conscious and unconscious behaviours are driven by habit. If you can find a way to accomplish a task by implementing a new habbit you'll require less motivation and are more likely to make longer term changes. Checkout Charles Duhigg's book on using habits to change your life and his brilliant infographic on changing habits .

• Celebrate New Year's Everyday

Research has shown that our level of motivation increases around big annual events . Why is this? When we look forward to the future and envision an improved version of ourselves our levels of motivation increase. Don't wait until new years to set goals and look toward the future.

• Understand your Values and Personality

Research by Dr Steven Reiss conducted on the motivational forces of over 60,000 individuals has shown there isn't a one size fits all approach to finding motivation. Your values and personality will play a big role in finding effective motivators. This is one reason we encourage our test and a little probing into your personality firsthand.

• Supercharge your Why's

Perhaps your levels of motivation are suffering because you lack compelling reasons why something must occur. Forget for a moment about your levels of motivation and focus instead on what it would mean for you if 'it' did happen. List as many compelling reasons as possible. Now focus on what it means to you if 'it' doesn't happen. Both of these lists should be long and compelling. If they're not big lists perhaps it's not your levels of motivation that are suffering but instead it's the level of motivation your goals provide.

He who has a why can endure any how

• Positive Self talk Works - But Choose Carefully

Research has shown that tasks requiring higher levels of technique and precision, self talk which focuses on technique and precision boosts performance . For these kinds of tasks focus on statements like "Chin down arms up" if you're boxing. If your work requires simple applications of effort more general statements are effective, think "This problem is not bigger than me"

• Make it Easy

Researchers presented two groups of students with an exercise program. One group had the program printed in a clear and easy to read font. The second groups program was printed in a difficult to read cursive font. People from the first group were far more likely to engage in exercise and described it as requiring less effort. How can you simplify the task at hand? Can you create a simple easy to read plan of the required steps?

• Take Control - Be your Own Boss

You're far more likely to sustain motivation if you're working under your own direction. Research has demonstrated those given direction do not maintain motivation for as long as those working under their own control. If you have no choice and do not agree with the direction of your work, speak with your manager. Find a way to work towards a goal you both believe is important.

• Get the Motivation App

We know that if you're participating in a group that hold similar motivational values and goals your chances of maintaining motivation improve. Free online apps like 'Lift' allow you to commit to improvement within a group of people sharing the same goal.

• Eliminate Doubt

Research had one group of students write out the phrase "Will I" and another group write the phrase "I Will" The task was presented as an exercise in handwriting skill. Following this the research gave both groups a set of anagrams to complete. The group writing "I Will" performed significantly better .

• Don't Share Your Goal

Research has shown that sharing your intention to do something can actually decrease your motivation to act . Psychologist speculate that sharing our goals gives us a sense of achievement which can reduce our motivation to act. Let your actions be your recognition, not your goals.

Tell the world what you intend to do, but first show it

• Be Impartial and Leave Ego Behind

Research is revealing the ego stroking positive psychology movement may not be particularly helpful. New evidence has indicated a view self compassion is a better ally to improving motivation and performance but why? Psychologist believe self compassion, or evaluating your pitfalls without criticising your ego produces better performance than blindly proclaiming your own virtues. Pro Tip: Separate your work from your sense of self and honestly evaluate your performance.

• Let Failiure Make you Stronger

Not so long ago willpower was believed to be something you were born with, a trait. We now know that willpower along with many other determinants of motivation and success are skills we can learn . When you do encounter setbacks don't allow your inner voice to tell you "I don't have what it takes" or "I'm destined to fail" Instead remind yourself that willpower and motivation are skills which require practice and planning. Re-evaluate your plan and continue practicing.

• Get Better Progressively and Avoid Burnout

As with exercise, taking on too much too soon will only lead to burn out. Willpower as we've pointed out is a muscle which improves with exercise. Aim to progressively improve your capacity and take rest seriously. You're more likely to enjoy the process.

A bigger stick

If the motivation test shows high behavioral inhibition you're motivated by avoiding pain and there are a number of strategies you can employ to improve your motivation.

Realize that if you don't work towards your goal and get yourself into gear you'll never achieve your goals and be trapped within your current circumstances. Nasty? Yep you bet but this works for you remember.

• Deadlines Work

Set a reasonable date for completion of your task and don't let yourself fail. Without the deadline you don't have as much to avoid.

• Live the Alternative

Take a minute out and consider the alternative. Imagine living your life without achieving the goal you're trying to achieve. Close your eyes and imagine every little detail of the alternative from how you would breathe to how you would walk, feel and think. Now open your eyes and seize the opportunity.

• The Right Kind of Criticism Helps

"You suck" is neither helpful or motivating. But research shows that when you're particularly advanced at a task negative feedback is both motivating and constructive . What is the right kind of negative feedback? "You dropped your elbows in the 5th round" provides technical feedback you can use to improve your game. Negative feedback is useful when it helps you to elevate your game and isn't simply a personal attack.

The physiology of motivation

Our motivation is affected not only by our patterns of thought but also the underlying physical chemistry of our brain. Within the brain we know motivation is controlled within the pre-frontal cortex and the striatum. Our levels of dopamine and histamine affect levels of alertness, motivation and many other processes. So in order to be highly motivated we need a healthy brain with healthy levels of both of these neurotransmitters.

• Sleep Efficiently

Research shows great sleep improves our levels of motivation . Exactly what qualifies as enough sleep will depend upon your individual physiology but aiming for 8 hrs of efficient sleep is a great start. Efficient sleep means when you're lying down you're in a deep sleep. If you wake many times or spend a lot of time lying down awake you may be getting 8 hrs but it won't be efficient.

• Get enough Vitamin D

Among the myriad of problems associated with Vitamin D deficiency is a feeling of lethargy and lack of motivation. Vitamin D has been used to treat depression because of the positive effects it can have on dopamine levels. You can either aim for 30mins of sun a day or purchase Vitamin D supplements.

• Address Depression if it exists

More severe forms of depression affect several neurotransmitters including dopamine. Extremely low levels of motivation may be psychomotor retardation, a symptom of depression. Take a look our test for depression for deeper look.

• Don't eat too much or too little

A major calorie deficit (eating too little) for an extended period of time is great for weight loss but will lead to feelings of lethargy and shift your bodies primary motivation to one of finding food. Too much food and your health will suffer which will also impact energy levels. Eat a high carbohydrate, high fibre diet for stable blood sugar levels and the sustained alertness that follow.

• Exercise Aerobically

Aerobic exercise outperforms anaerobic when it comes to neuropsychological performance. What does this mean? Going for a 30min run will do more for your levels of motivation than lifting heavy weights.

• Practice Mindfulness Meditation

Meditation changes the density and thickness of connections in our prefrontal cortex which as we mentioned is the part of the brain responsible for motivation. It also improves our awareness of our emotional state which can become a great ally when procrastination arises. We also know that regular meditation improves alertness and concentration. Checkout this awesome infographic on meditation .

• Evaluate your Friendships

Once you've identified values likely to motivate you it's important to consider how your friendships may impact your levels of motivation. Research has shown that maintaining friendships with values aligned to yours is going to help while those which conflict with your values are going to hurt.

• Music Motivates

Many marathons no longer permit to use of music because of the unfair advantage to performance it offers. The research shows that music boosts performance and effort without us even knowing so.

Great Reading on Motivation

• The Power of Habit
• How I went from being a lazy student to a success

The puzzle of motivation

60 Inspiring Examples: How To Write Accomplishment Statements

By Status.net Editorial Team on November 22, 2023 — 17 minutes to read

• Crafting Your Accomplishment Statements Part 1
• Types of Accomplishment Statements Part 2
• Examples of Quantitative Accomplishment Statements Part 3
• Examples of Qualitative Accomplishment Statements Part 4
• Examples of Action Verbs to Describe Your Achievements Part 5
• Common Mistakes to Avoid Part 6
• Editing and Refining Your Achievement Statements Part 7

When you’re jazzing up your resume or preparing for an interview, crafting strong accomplishment statements can set you apart. Think of these statements as snapshots that capture how you’ve excelled in your roles. They’re your professional highlights reel where action verbs are your star players, setting the scene with energy and precision.

Your accomplishment statements should feel as though they are bringing a dose of enthusiasm to your narrative, not just listing duties. When drafting, consider how each sentence provides a window into the problems you’ve solved and the goals you’ve kicked. Give enough detail to spark curiosity and make recruiters want to learn more about what you bring to the table.

Part 1 Crafting Your Accomplishment Statements

Creating strong accomplishment statements on your resume can set you apart from other candidates. They not only show what you’ve done but also how well you’ve done it.

Starting With Action Verbs

Start your statements with powerful action verbs to capture attention and make your accomplishments stand out. Verbs like ‘executed’, ‘transformed’, ‘implemented’, ‘spearheaded’, and ‘orchestrated’ show you’re action-oriented. For example, instead of saying “Was in charge of,” you might say, “Managed a team of 10 to…”.

Highlighting the Impact

Quantify your achievements to provide a clear picture of your impact. Use numbers, percentages, and financial figures where possible. A statement like “Increased sales by 20% over a six-month period by implementing a new strategic marketing plan” clearly demonstrates your effectiveness.

Adding the Wow Factor

Use qualitative terms to give context and show the significance of your accomplishments. You might say, “Revitalized a stagnant brand by introducing a fresh social media strategy, resulting in a 50% increase in online engagement.” This shows not only what you did, but also the positive effect it had.

Part 2 Types of Accomplishment Statements

Crafting accomplishment statements effectively showcases your achievements in a way that’s clear and impressive. They typically come in two varieties: quantitative and qualitative.

Quantitative Accomplishment Statements

Quantitative statements rely on numbers and data to demonstrate your impact. Examples of these might include, “Increased sales by 20% within one fiscal quarter” or “Reduced customer call times by 30 seconds, improving the customer experience.” These particular phrases employ numbers to give a solid, measurable snapshot of your achievements.

Qualitative Accomplishment Statements

Qualitative statements, on the other hand, emphasize the quality of your impact, often in areas where numerical data isn’t the focus. For example, “Improved team communication by implementing weekly sync meetings” or “Enhanced customer satisfaction through personalized follow-up emails.” These statements spotlight the positive changes you brought about through your actions and decisions without relying strictly on metrics.

Part 3 Examples of Quantitative Accomplishment Statements

Quantifying your achievements means adding numbers to provide a clear and measurable impact of your work. This approach makes your contributions tangible and shows the value you’ve added.

• Start by reviewing your job duties and identify any areas where you’ve made a measurable difference. Look for changes in revenue, time saved, increase in customer satisfaction scores, or any other metric that can be expressed in numbers. If you are struggling to recall specific figures, try estimating conservatively or use percentages to indicate growth or improvement.
• For example, if you’re in sales, you could write, “Exceeded monthly sales targets by 20% for five consecutive months, resulting in a $50K increase in revenue.” This statement not only shows that you met your goals but surpassed them significantly.
• If you’ve streamlined a process, describe how much time you saved. A statement such as “Implemented a new inventory system, reducing stock-checking time by 30%,” makes it clear that your actions had direct, time-saving outcomes.
• Use action verbs in the past tense to emphasize your role in the achievements. Words like ‘achieved’, ‘expanded’, ‘developed’, ‘reduced’, and ‘negotiated’ pack a punch and give your statements power.
• Don’t underestimate smaller numbers. Even improving customer satisfaction by 5% can be important in a competitive market. Any positive change you’ve driven is worth mentioning, and quantifying these changes provides a clearer picture of your capabilities and results.
• 1. Increased departmental sales by 15%, resulting in a $100K revenue boost over six months.
• 2. Streamlined project delivery process, reducing turnaround time by 25%.
• 3. Managed a team of 10, increasing overall productivity by 35%.
• 4. Cut operational costs by 10% through strategic vendor negotiations.
• 5. Improved customer satisfaction ratings by 8% through enhanced service protocols.
• 6. Led a marketing campaign that generated a 50% increase in leads.
• 7. Automated report generation, saving 20 hours of manual work per week.
• 8. Boosted social media engagement by 40% with targeted content strategies.
• 9. Developed a new employee training program, reducing onboarding time by 30%.
• 10. Oversaw a budget of $500K, ensuring all projects stayed under budget by at least 5%.
• 11. Implemented a CRM system, increasing customer retention by 12%.
• 12. Directed a team that delivered a critical software update 3 weeks ahead of schedule.
• 13. Increased production efficiency by 20% by optimizing assembly line processes.
• 14. Expanded the company’s market share by 5% within one fiscal year.
• 15. Reduced employee turnover by 15% through improved HR policies and staff engagement.
• 16. Coordinated an event with 300+ attendees, resulting in a 25% increase in brand awareness.
• 17. Secured 5 high-value client contracts, each worth over $50K.
• 18. Consolidated two company divisions, saving $30K annually in administrative costs.
• 19. Achieved a record-breaking $1M in sales during the first quarter.
• 20. Enhanced website traffic by 60% via SEO and content marketing initiatives.
• 21. Decreased defect rates by 7% through meticulous quality control measures.
• 22. Surpassed fundraising targets by 150%, raising over $300K for a non-profit initiative.
• 23. Facilitated a partnership that led to a 20% expansion of service offerings.
• 24. Delivered 10+ major presentations to stakeholders, improving project buy-in by 30%.
• 25. Negotiated a critical contract, resulting in a 10% discount on supply costs.
• 26. Pioneered a digital transformation that improved data accessibility by 70%.
• 27. Mentored 5 junior employees, all of whom were promoted within a year.
• 28. Conducted market research that informed a successful product pivot, increasing sales by 35%.
• 29. Revamped the company’s social media strategy, leading to a 100% increase in follower engagement.
• 30. Orchestrated a logistics overhaul that reduced shipping times by 15%.
• 31. Authored a white paper that attracted 2,000+ downloads, establishing thought leadership in the industry.
• 32. Implemented energy-saving initiatives that cut utility expenses by $5K annually.
• 33. Spearheaded a customer feedback system, enhancing product features and boosting satisfaction by 10%.
• 34. Managed a portfolio of 50+ client accounts, maintaining a 98% satisfaction rate.
• 35. Co-authored three successful grant applications, totaling $150K in funding.
• 36. Optimized inventory management, resulting in a 5% reduction in waste.
• 37. Led a cross-functional team that successfully launched a new product line, contributing to a 20% increase in annual revenue.
• 38. Designed a training module that decreased employee onboarding time from 2 weeks to 3 days.
• 39. Coordinated with international teams, delivering projects 20% faster than previous benchmarks.
• 40. Developed a comprehensive risk management strategy, reducing incidents by 40%.
• 41. Launched an affiliate marketing program that generated an additional $25K in monthly sales.
• 42. Implemented a customer loyalty program that increased repeat business by 15%.
• 43. Conducted a competitive analysis that led to a strategic pivot, capturing an additional 10% of the market share.
• 44. Reduced software development cycle time by 25% through agile methodologies.
• 45. Increased average order value by 18% through targeted upselling techniques.
• 46. Successfully managed and closed deals with three Fortune 500 companies.
• 47. Reduced annual IT expenses by 10% by migrating to cloud-based solutions.
• 48. Enhanced online conversion rates by 30% with a redesigned user interface.
• 49. Negotiated a major contract that resulted in a recurring annual saving of $50K.
• 50. Implemented a quality assurance program that decreased customer complaints by 20%.
• 51. Accelerated product time-to-market by 10% through efficient project management.
• 52. Facilitated a merger that expanded the company’s workforce by 25% without sacrificing productivity.
• 53. Developed and patented a new technology that increased product efficiency by 15%.
• 54. Cultivated a business partnership that led to a joint venture, increasing revenue by $1M.
• 55. Designed and executed a direct mail campaign with a 5% response rate
• 56. Orchestrated a supply chain realignment that saved $40K in logistics costs annually.
• 57. Championed a customer service initiative that reduced call-handling times by 20%.
• 58. Led a digital advertising campaign that drove a 300% ROI within the first month.
• 59. Increased membership retention by 25% through personalized engagement strategies.
• 60. Directed a cost-reduction initiative that saved the company $200K in the first year.

Part 4 Examples of Qualitative Accomplishment Statements

Writing impactful accomplishment statements that aren’t centered around numerical data can be highly effective in showcasing your skills and experience. When you lack quantifiable results or when confidentiality concerns prevent sharing specific metrics, you can focus on qualitative achievements that speak to your abilities.

• Start with strong action verbs that convey your direct contribution. For example, verbs like ‘launched’, ‘improved’, ‘developed’, ‘expanded’, or ‘transformed’ demonstrate your active role in making things happen.
• You might say, “Developed a comprehensive onboarding program that improved team integration and productivity.” Here, the focus is on the creation and positive outcome of your action, emphasizing the value of your contribution.
• Describe your accomplishments through the lens of challenges faced and the solutions you provided. For example, “Resolved a longstanding customer service bottleneck, which heightened client satisfaction.” This showcases problem-solving skills and the impact on customer experience, both highly valuable to employers.
• Highlight your leadership and collaborative efforts with phrases that show your role within a team or project. An example might be, “Coordinated a cross-departmental project that harmonized communication and workflows.” This underlines your teamwork and organizational skills.
• Consider including advancements in personal skills or professional development. For instance, “Mastered advanced design software to enhance content quality and visual appeal,” which suggests dedication to self-improvement and keeping up with industry tools.
• Remember to tailor these statements to the job you’re applying for, aligning your achievements with the skills and attributes the employer is seeking. This personalized approach can often resonate more than raw numbers alone.
• 1. Launched an innovative marketing campaign that significantly elevated brand visibility in a saturated market.
• 2. Improved the company’s internal communication strategy, fostering a culture of transparency and collaboration.
• 3. Developed a state-of-the-art inventory tracking system that streamlined warehouse operations.
• 4. Expanded the customer base through strategic networking and partnerships, leading to market growth.
• 5. Transformed the user experience of the corporate website, enhancing customer engagement and satisfaction.
• 6. Orchestrated a successful merger, integrating teams and systems seamlessly.
• 7. Revitalized a stagnant product line, reinvigorating sales and customer interest.
• 8. Pioneered a sustainability initiative that positioned the company as an environmental leader in the industry.
• 9. Engineered a software solution that became the standard for improving operational efficiency.
• 10. Forged strong relationships with key industry influencers, boosting the company’s reputation and authority.
• 11. Negotiated critical contracts that provided long-term stability and growth opportunities.
• 12. Cultivated a dynamic team culture that attracted top talent and reduced turnover.
• 13. Directed a comprehensive rebranding effort that refreshed the company’s image and messaging.
• 14. Championed diversity and inclusion policies that enriched the workplace environment.
• 15. Masterminded a crisis management plan that protected the company’s interests during challenging times.
• 16. Facilitated a workshop that enhanced team creativity and problem-solving skills.
• 17. Spearheaded a digital transformation that kept the company ahead of technological trends.
• 18. Authored thought leadership articles that established the company as an expert in its field.
• 19. Revamped the onboarding process, creating a welcoming and efficient experience for new hires.
• 20. Orchestrated a company-wide training program that upskilled employees and boosted productivity.
• 21. Mediated and resolved complex disputes, maintaining harmony and cooperation within the team.
• 22. Initiated a quality assurance protocol that upheld the company’s high standards for product excellence.
• 23. Designed an award-winning product packaging that captured the attention of consumers.
• 24. Led a cross-functional initiative that broke down silos and improved interdepartmental collaboration.
• 25. Implemented a customer feedback loop that informed key product enhancements.
• 26. Developed a risk management framework that safeguarded the company against potential threats.
• 27. Coordinated a successful trade show exhibition that generated a buzz in the industry.
• 28. Enhanced the corporate social responsibility program, earning accolades from the community.
• 29. Piloted a mobile work initiative that increased employee satisfaction and work-life balance.
• 30. Championed a company-wide initiative that promoted work-life balance, leading to a marked decrease in reported employee
• burnout and a significant enhancement in overall job satisfaction.
• 31. Launched a mentorship program that empowered employees and fostered leadership development.
• 32. Improved project reporting mechanisms, resulting in more informed decision-making processes.
• 33. Developed a custom software tool that became essential in daily operations.
• 34. Expanded the company’s social media presence, significantly increasing online engagement.
• 35. Transformed underperforming teams into high achievers through targeted coaching and development.
• 36. Orchestrated a volunteer program that enhanced the company’s community involvement and presence.
• 37. Revitalized client relationships through proactive outreach and personalized service strategies.
• 38. Pioneered an internal idea-sharing platform that spurred innovation and process improvements.
• 39. Engineered a change management strategy that minimized resistance and maximized adoption.
• 40. Forged strategic alliances that opened new channels for business development and revenue streams.
• 41. Cultivated a culture of continuous improvement, leading to enhanced operational effectiveness.
• 42. Negotiated with suppliers to secure more favorable terms without compromising on quality.
• 43. Initiated a comprehensive competitor analysis that guided the company’s strategic planning.
• 44. Championed a user-centered design philosophy that led to more intuitive and effective products.
• 45. Directed the successful turnaround of an underperforming business unit.
• 46. Implemented a robust protocol that protected sensitive company data.
• 47. Coordinated a company retreat that boosted morale and team cohesion.
• 48. Authored a series of industry whitepapers that solidified the company’s thought leadership.
• 49. Mediated high-stakes negotiations that resulted in beneficial partnerships.
• 50. Developed and led a training module on emotional intelligence, enhancing team empathy and communication.
• 51. Championed a wellness program that improved overall employee health and reduced absenteeism.
• 52. Orchestrated the decommissioning of outdated systems, ensuring a smooth transition to modern technology.
• 53. Enhanced the talent acquisition process, attracting higher-caliber candidates.
• 54. Led a task force to address critical workflow bottlenecks, resulting in more efficient operations.
• 55. Piloted a flexible work arrangement program, leading to increased employee satisfaction.
• 56. Coordinated a successful brand collaboration that expanded market reach and influence.
• 57. Implemented a client onboarding system that streamlined the acquisition process.
• 58. Spearheaded an initiative to revamp the company newsletter, significantly increasing readership.
• 59. Directed a cross-cultural communication training that enhanced global team interactions.
• 60. Facilitated the adoption of a new project management methodology, leading to more predictable project outcomes.

Part 5 Examples of Action Verbs to Describe Your Achievements

Choosing the right action verb for your accomplishment statements can give your resume or performance review the punch it needs to stand out. Use these dynamic verbs to clearly articulate your successes and make your contributions shine.

• Start with words like ‘orchestrated’ or ‘spearheaded’ when you want to demonstrate leadership and initiative. These words convey that you were at the helm of a project, directing it to success. If you improved a process or made something more efficient, consider ‘streamlined’ or ‘optimized’. These verbs suggest improvement without taking up too much space.
• Suppose you saved the company money or increased revenue. In that case, words like ‘generated’, ‘accelerated’, or ‘enhanced’ can show the direct impact of your actions. For teamwork, ‘collaborated’, ‘united’, or ‘fostered’ emphasize your ability to work effectively with others and contribute to a joint effort.
• When showcasing creativity, use terms like ‘conceived’ or ‘envisioned’. These indicate that you brought new ideas to life. And if precision or expertise was key to your role, ‘crafted’, ‘engineered’, or ‘calibrated’ can depict your skills in a field or intricate work.
• Compile your own list of powerful verbs tailored to the skills and accomplishments you want to highlight. Make sure each verb fits the action you’re describing and that it presents your experience confidently and accurately. With a well-chosen verb, your accomplishments will grab attention and clearly communicate your value.

Examples of action verbs that can help make your achievement statements more impactful:

• – Orchestrated
• – Streamlined
• – Optimized
• – Generated
• – Accelerated
• – Enhanced
• – Collaborated
• – United
• – Fostered
• – Conceived
• – Crafted
• – Engineered
• – Calibrated
• – Pioneered
• – Transformed
• – Revitalized
• – Negotiated
• – Directed
• – Implemented
• – Facilitated
• – Cultivated
• – Innovated
• – Revamped
• – Modernized
• – Advocated
• – Analyzed
• – Customized
• – Drove
• – Expanded
• – Forged
• – Governed
• – Integrated
• – Leveraged
• – Mediated
• – Navigated
• – Overhauled
• – Piloted
• – Quantified
• – Reconciled
• – Shaped
• – Tailored
• – Unified
• – Validated
• – Amplified
• – Bolstered
• – Conceptualized
• – Deployed
• – Elevated

These verbs can be strategically used to describe your professional experiences and accomplishments with a strong sense of action and purpose.

Part 6 Common Mistakes to Avoid

• When crafting accomplishment statements, one of the pitfalls you might fall into is using vague language. Your statements should be specific and clear to provide a concrete understanding of your achievements. Avoid generic phrases like “handled tasks” or “worked with clients.” Instead, say exactly what you did and the outcome, like “increased sales by 20% through direct client engagement.”
• Listing duties instead of accomplishments is another frequent error. Rather than just saying what your role was, focus on what you accomplished in that role. For example, don’t just say “responsible for sales team,” tell others how you improved the team’s performance.
• Resist the temptation to inflate your achievements. Honesty is key as it maintains your credibility. If you improved productivity, provide realistic figures to back it up. Inflated numbers or exaggerated claims can damage your reputation if scrutinized.
• Avoid a monotonous list of tasks. Mix in some qualitative accomplishments to show your skills in a broader context. These provide insights into not just what you did, but how you approached tasks, dealt with challenges, and contributed to the team or company culture.
• Neglecting the use of strong action verbs can weaken your statements. Start your accomplishments with verbs like ‘orchestrated,’ ‘innovated,’ or ‘transformed’ to grab attention and immediately inform about the action you took.
• Lastly, make sure your accomplishment statements are not too long or complex. You want your reader to grasp your successes quickly. Dense paragraphs or overly technical jargon can detract from the impact of your achievements. Keep it concise and straightforward.

Part 7 Editing and Refining Your Achievement Statements

After drafting your accomplishment statements, review each one to ensure they are clear, concise, and impactful. Focus on active verbs and precise language to make your accomplishments stand out. Ask yourself, does the statement convey the impact of your work?

Quantitative results often speak for themselves but check that the context is also there. A 20% increase in sales is impressive, but noting that this was a key part of a successful product launch adds depth. Keep the numbers simple, and make sure they stand out—people are drawn to concrete evidence of success.

Qualitative statements can be trickier. Strive for vividness by using strong action verbs and sensory language where appropriate. Instead of “Managed a team,” personalize and punch it up: “Steered a dynamic team towards surpassing annual goals.”

Solicit feedback from peers or mentors. Sometimes, you’re too close to your own experience to see unclear points. Fresh eyes can spot areas where more specificity is needed or where jargon slips in.

Lastly, trim the fluff. Eliminate unnecessary words and focus on the ‘what’ and the ‘why’. This distillation process will leave you with powerful statements that clearly demonstrate your value. Keep refining until each statement reads well and has a distinct purpose.

Frequently Asked Questions

How can i craft an effective accomplishment statement for my resume.

When writing accomplishment statements, start with a strong action verb to capture attention. Follow with a description of the task you completed and conclude with the positive outcome or impact. Likewise, quantifying accomplishments helps to provide a clear understanding of your capabilities.

What are some powerful action verbs to enhance accomplishment statements?

Use dynamic verbs like “achieved,” “expanded,” “optimized,” and “streamlined.” These words can effectively convey your contributions and exhibit your active role in achieving success. Action verbs also add energy and clarity to your statements, showing your dynamism in various roles.

Can you give me examples of accomplishment statements with quantifiable results?

Certainly, for instance: “Increased sales by 20% over a 6-month period through strategic business development initiatives,” or “Cut customer support response time by 30% by implementing a more efficient ticketing system.”

Could you provide examples of accomplishment statements that highlight qualitative achievements?

Here’s an example: “Improved team morale and productivity through the introduction of monthly team-building activities.” Another could be “Enhanced the company’s brand image by redesigning the customer service protocol to be more user-friendly.”

What’s the best structure to use when writing a professional accomplishment statement?

Your accomplishment statement should have three parts: a strong action verb, the task or project you were responsible for, and the positive result or impact that task had. Ensuring these elements are present gives a comprehensive view of what you did and the value you brought to the company.

How should one present their skills and accomplishments in a resume to make a strong impact?

Highlight your skills and accomplishments in a resume by tying them to specific results and using metrics whenever possible. Present your achievements in a way that matches the job description, aligning your experience with the prospective employer’s needs and showing that you have a proven track record of success.

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