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The Relative Importance of Intelligence and Motivation as Predictors of School Achievement: A meta-analysis
Abstract
This meta-analysis summarizes 74 studies (N = 80,145) that simultaneously examined the predictive power of intelligence and motivation for school achievement. First, we found average correlations between intelligence (r = 0.44) and motivation (r = 0.27) with school achievement and between intelligence and motivation (r = 0.17). Moderator analyses showed that the correlation between motivation and school achievement was higher for expectancies than for values. No moderator effects were found for grade level, school form or gender. Second, in a path model, 24% of variance in school achievement was explained overall. From this overall explained variance in school achievement, 66.6% was uniquely explained by intelligence and 16.6% uniquely by motivation, whereas the two predictors commonly explained 16.6%. Thus, the results show that both intelligence and motivation contribute substantial, unique shares to the prediction of school achievement as well as an additional share of commonly explained variance.
... Similarly, academic motivation, or the internal factor that drives an individual to approach a certain academic goal (Kriegbaum et al., 2018;Pintrich, 2003), is often portrayed as a large construct comprehensive of various motivational factors that predict academic achievement (Hattie, 2008). Within a social-cognitive approach to motivation (Bandura, 2001), several well-established constructs associated with academic achievement can be identified. ...
... Among them there are academic self-efficacy (Bandura et al., 1997), which refers to the belief in one's ability to successfully complete academic tasks; growth mindset (Dweck, 1999), which is the belief that one's intelligence is malleable and not fixed; and learning goals (mastery goals), indicating students' desire to acquire and enhance their knowledge rather than solely focusing on performance outcomes (Dweck & Leggett, 1988). Various meta-analyses have confirmed the significance of these factors for students' academic achievement (Costa & Faria, 2018;Richardson et al., 2012;Robbins et al., 2004), and numerous individual studies have also underscored the distinct roles of each of these three motivational factors in predicting mathematics performance (Blackwell et al., 2007;Kriegbaum et al., 2015Kriegbaum et al., , 2018Liu, 2021). It should be noted, however, that there is an ongoing debate in the scientific literature, especially regarding the role of growth mindset. ...
... � Arithmetic performance, self-regulated learning strategies, motivation and emotions: We expect self-regulated learning strategies, academic motivation, and positive achievement emotions to positively relate to arithmetic performance (Burnette et al., 2013;Forsblom et al., 2022;Kriegbaum et al., 2018;Lavrijsen et al., 2022;Ma, 1999;Richardson et al., 2012). On the contrary, negative achievement emotions should have a negative relation with arithmetic performance. ...
... Die Motivation von Schüler*innen ist eine zentrale Variable für ihren Lernerfolg (Linnenbrink & Pintrich, 2002). Sie erklärt etwa in gleichem Maße die schulische Leistung wie Intelligenz (Gagné & St Père, 2001;Kriegbaum et al., 2018). Motivation beschreibt einen vielschichtigen, kognitiven Prozess, der im Vergleich zu Intelligenz zeitlich und situativ veränderbar ist (Heckhausen & Heckhausen, 2018). ...
... On a theoretical level, motivation (cognitive antecedent) affects academic achievement (behavioral outcome) in multiple ways (Kriegbaum et al., 2018;Lewin, 1936;. That is, different motivational variables (e.g., self-efficacy, selfdetermined motivation, achievement goals), as well as other learning-relevant aspects (e.g., quality of teacher instructions), explain a student9s degree of academic achievement. ...
Motivation is crucial for student learning, yet teachers’ judgments of student motivation often differ from students’ self-assessments. This dissertation investigated the mechanisms behind this discrepancy and explores ways to align these perspectives. In Study 1, students judged their motivation with an emphasis on achievement goals, whereas teachers prioritized achievement information. In Study 2, however, making achievement goal information directly available led teachers to rely on it more strongly. Nonetheless, when they had to memorize information, they reverted to using achievement information again. In Study 3, individual feedback was intended to help teachers improve their usage, but no significant change was observed. Overall, the findings suggest that low agreement stems from differential information use, possibly influenced by a performance-oriented school policy. This could encourage biased mental heuristics when judging motivation in the inherently complex everyday school environment. Formative assessment could help to reduce such biases.
... Learning motivation and academic engagement are widely recognised as critical determinants of students' academic success (Kriegbaum, Becker, and Spinath 2018;Putwain et al. 2019). In the field of language acquisition, extensive research has demonstrated their significant impact on language proficiency Lau 2019). ...
... According to Social Cognitive Theory (Bandura 1986), human actions are inherently goal-oriented. When students perceive a learning activity as valuable and believe in their ability to succeed, they are more likely to engage in these activities with both greater quantity and quality, leading to improved academic achievement (Kriegbaum, Becker, and Spinath 2018;Putwain et al. 2019;Schwinger and Stiensmeier-Pelster 2012;Wong et al. 2024). In the domain of language learning, the positive impact of learning motivation and engagement on students' language proficiency has been substantiated by numerous empirical studies in both L1 (Gu and Lau 2023;Lau 2019) and L2 contexts Tsang and Dewaele 2024). ...
... Moreover, several studies have identi ed that students' interest in mathematics declines across the secondary school years (e.g., across Grades 5 to 9; Frenzel et al., 2010). [1] This decline is highly problematic given that students' interest in school subjects (e.g., mathematics) is positively associated with their academic achievement (Köller et al., 2001;Kriegbaum et al., 2018;Schiefele et al., 1992). Because citizens need mathematics to successfully navigate through today's society, as many everyday tasks require people to solve complex problems, it is critical to promote students' interest in mathematics. ...
... Interest is an essential construct that shapes people's lives by affecting their leisure activities or determining their career paths after high school graduation . In educational contexts, when students nd a topic or activity interesting, they show more focused attention and increased cognitive functioning, which may lead to a deeper engagement and, nally, to enhanced learning outcomes and a more positive attitude toward the subject matter Hidi, 2001;Jansen et al., 2016;Köller et al., 2001;Kriegbaum et al., 2018;Mitchell, 1993;Murayama, 2022;Rotgans & Schmidt, 2017b;Trautwein et al., 2006). In a meta-analysis, Schiefele et al. (1992) demonstrated that students' interest in mathematics was positively associated with their mathematics achievement (r = .32, ...
Previous research has shown that students’ interest typically declines across secondary school, likely resulting from a mismatch between their needs and the school environment. Technology-enhanced adaptive teaching may allow teachers to better tailor their instruction to students’ needs, including students’ interests; thus, this approach may be promising in this regard. The objective of this study was to gain insight into the associations between equipping students and their teachers with tablet computers (1:1 technology), student-perceived adaptive teaching, and students' situational interest. We used questionnaire data (i.e., from two measurement points: t 0 = baseline; t 1 = 4 months later) from the longitudinal project tabletBW meets science from 2,601 students (Grade 7, Gymnasium, Germany) attending 28 schools. Fourteen schools were randomly chosen to be given 1:1 technology (i.e., tablet computers for teachers and students; intervention condition). The other 14 randomly chosen schools were not given such equipment (control condition). We assessed how students' situational interest in mathematics was associated with the use of tablet computers (intervention vs. control) and student-perceived adaptive teaching. Results from multilevel models showed that the 1:1 technology had a statistically significant effect on students' situational interest, partly mediated by student-perceived adaptive teaching. Moreover, knowing that students' interest in math declines in adolescence, our results indicate that equipping classrooms with technology might offer a promising way to implement more adaptive lessons that have the potential to provide the appropriate degree of challenge to students and thus spark their interest in mathematics.
... In an academic context this may relate to a person's interest and enthusiasm to complete a task. A wealth of evidence suggests that motivation is associated to the academic achievement of school children (Gorard et al., 2012;Henderlong et al., 2009;Kriegbaum et al., 2018;Linnenbrink-Garcia et al., 2018;Schunk et al., 2008 andSteinmayr et al., 2018). ...
... Intelligence is often defined as the ability to learn from experience, adapt to new situations, understand complex ideas, and employ various forms of reasoning to overcome obstacles (Neisser et al., 1996). The assertion that general intelligence is a predictor of academic performance is well-supported by existing literature as was summarized by meta-analyses (Kriegbaum et al., 2018;Lozano-Blasco et al., 2022;Roth et al., 2015). Focusing on success in the domains of STEM revealed that various cognitive abilities, including numerical, spatial, and verbal intelligence predicted educational success in STEM studies. ...
Background
The current study aimed to investigate the associations between cognitive abilities, grit, and academic achievement in high school STEM studies. The study utilized a natural sample of excelling STEM students (N = 814) who underwent a selection process to join elite undergraduate STEM programs. Through this selection process, the students reported their high school grades in Math, Physics, and Computer science, as well as their Psychometric Entrance Test (PET) scores, which are equivalent to the SAT. They also completed a Grit questionnaire and took various cognitive ability tests.
Results
Our study highlights the significant role of grit in STEM achievements, particularly for students with moderate cognitive abilities. We found that while cognitive abilities were strong predictors of academic STEM success, grit weakly contributed to predicting achievements in STEM studies beyond cognitive abilities alone. The study's main finding revealed that grit moderates the association between cognitive abilities and academic STEM grades, with higher levels of grit diminishing the impact of cognitive abilities on STEM success. Specifically, students with high grit could leverage their determination and passion to bridge cognitive gaps, effectively reducing performance disparities.
Conclusions
The findings underscored the multifaceted nature of cognitive skills and non-cognitive factors like grit in contributing to STEM success. The study highlights the importance of fostering grit, particularly among students with moderate cognitive abilities. Higher grit can especially benefit these students in achieving higher STEM grades. According to Social Cognitive Career Theory (SCCT), higher achievements could promote one’s self-efficacy and encourage students to pursue STEM careers after high school. This underscores the importance of integrating both cognitive and non-cognitive factors in educational and career guidance programs.
... One key predictor of academic achievement is motivation explaining 16.6% of the variance in school achievement and incrementally predicting school achievement above and beyond intelligence (Kriegbaum et al., 2018). Academic motivation can be defined as "the process whereby goal-directed academic activity is instigated and sustained" (Schunk et al., 2014, p. 4). ...
There is considerable variability in young students’ development of academic achievement. Differences in the tendency to be motivated by rewarding stimuli through the behavioral activation system or to avoid aversive stimuli through the behavioral inhibition system may affect trajectories of academic performance (AP). Second-order growth mixture modeling was used to explore latent classes of trajectories of AP among elementary school students (N = 2,147) from fourth through seventh grade. Students’ approach and avoidance sensitivity were added as predictors and assessed using multinomial regression. AP was assessed using teacher-rated academic indicators on Norwegian, Mathematics, English, and Social Science. Avoidance sensitivity was measured using Carver and White’s (1994) Behavioral Inhibition System scale, and approach sensitivity was measured using the Behavioral Activation System subscales Drive and Reward Responsiveness. Three latent classes of academic trajectories emerged: one high and increasing (26%), one consistently moderate (59%), and one low and decreasing (15%). The risk of having a low and decreasing trajectory was increased by high Behavioral Inhibition System and Drive sensitivity. The results confirmed previous research associating high avoidance sensitivity with low AP but contradicted findings associating high approach sensitivity with high AP. Drive may motivate students to achieve competence but may become detrimental to academic achievement if interests diverge from normative demands in the educational context. Students with high Drive may need support in self-regulation and in recognizing the value of using their Drive to acquire academic competence.
... A significant positive correlation between motivation and educational outcomes has been found in a meta-analysis conducted by Kriegbaum, Becker & Spinath (2018). However, it is important to define what motivation is to understand how motivational states can be regulated. ...
p dir="ltr"> Since little is known about the incorporation of educational neuroscience into foreign language teaching, so many English as a Foreign Language (EFL) teachers heavily rely on the most used teaching methods they learn through Initial Teacher Training programmes (ITT), such as TEFL, CertTESOL, and CELTA. CELTA, which stands for Certificate in English Language Teaching to Adults, is a benchmark of excellence in the field due to its high demand from employers (3/4 English language teaching jobs require a CELTA), its standardised format and practical teaching experience. Even though the CELTA course is widely considered the gold standard for EFL, it fails to equip novice teachers with the neuroscientific evidence to help them improve students’ outcomes by explicitly teaching meta-skills: metacognition — “learning how to learn” and meta-motivation — “learning how to motivate oneself”. Metacognition and meta-motivation allow learners to evaluate and support their learning, and in turn, encourage autonomy and change the idea of learning as an event purely happening within the four walls of the classroom. This research focused on the overview of the CELTA syllabus through the lens of neuroscience, examination of evidence as to why adding a topic in neuroscience to a CELTA certification course can bring about positive change, a design of the new topic to be potentially added to a CELTA syllabus, as well as an empirical study design to measure its effectiveness. It is hypothesised that adding a topic in meta-skills to the most in-demand course for EFL teachers, will not only improve teaching practice on the course and promote lifelong learning, but also become an accessible, evidence-based, teacher-friendly neuroscience resource. It is assumed that a topic in educational neuroscience will become a black swan of teacher training, — an unprecedented event that can change the whole course of teacher training by shifting the focus from the “know-what” to the “know-how” and the “know-why” of learning, and therefore, have a significant impact on how teachers see learning. A possible positive influence on other certification courses and “dehyping” of neuroscience is also expected, which should lead to more awareness among EFL teachers and minimise the risks of falling into a trap of snake oil salesmen promoting “brain friendly” language learning teacher training courses for EFL teachers. </p
... Many factors are essential for success in school performance, such as cognitive factors like intelligence or working memory capacity. In terms of school success, often measured as test performance or school grade and termed achievement, it can be assumed that there is a prediction of intelligence on school achievement (Kriegbaum et al., 2018) -but this is only moderately pronounced. Spinath et al. (2006) showed that general intelligence and motivation are linked to school performance. ...
... In this study, we focus on intrinsic motivation for math. Various studies have shown that math intrinsic motivation positively predicts academic achievement in math (Kriegbaum et al., 2018;Stevens et al., 2006). Since intrinsic motivation does not depend on expectations of success, it could be key to encouraging math learning for groups of students who lag behind on math achievement. ...
Despite increased investment in rural education in recent years, the academic achievement of ethnic minority students in rural China continues to lag behind their Han Chinese peers. Few studies have used up-to-date data to measure the size of this achievement gap, and none have examined whether differential math attitudes and math anxiety play a role in perpetuating it. Using data from a survey of 16,747 students in 235 rural primary schools, we find a significant disparity in math performance between ethnic minority and Han students, with minority students scoring 0.25 standard deviations lower than their Han peers. Multivariate analysis reveals that differences in math affinity and math anxiety were significantly associated with math achievement among ethnic minority and Han students. Decomposition analysis further reveals that up to 37% of the achievement gap can be explained by variations in student, parent, and teacher characteristics. The difference in household asset was the largest explained contributor to the Han-minority achievement gap, followed by math affinity and math anxiety. This study underscores the importance of addressing students’ math affinity and math anxiety in narrowing rural achievement gaps and promoting equitable educational outcomes in rural China and abroad.
... Meanwhile, the motivation of students in the high and medium mathematical understanding groups is influenced by students' emotions and aspirations to succeed in learning. The different relationship patterns between motivation and mathematical understanding of these different achievement groups directly compare variations in these groups [25] as a meta-analysis study conducted by Kriegbaum et al. [65] showed that there is a positive correlation between motivation and students' academic achievement in school. ...
Technology-based learning media is strongly suspected of influencing students’ emotional reactions and motivation to learn mathematics. However, students’ emotional reactions to mathematics learning still receive less attention from teachers. This study aims to investigate the differences in emotional reactions and learning motivation between high, medium, and low levels of students’ mathematical comprehension and the role of digital comic media in mathematics learning. This study involved 100 high school student respondents. Data collection is done through observation, surveys, and tests. The findings of this study indicate significant differences in emotional reactions and learning motivation between high, medium, and low levels of students’ mathematical comprehension in mathematics learning assisted by digital comic media. Emotional reactions predict students’ mathematical comprehension abilities in the high and medium groups in mathematics learning assisted by digital comics. However, specifically learning motivation is the strongest predictor of low group students’ mathematical comprehension. The role of digital comic media in mathematics learning is to build positive emotional reactions, focus attention, visualize abstract concepts in mathematics into concrete concepts, and become good cognitive control for students when learning.
... Does student motivation predict academic achievement and/or does academic achievement predict motivation? Disentangling the relations between motivation and achievement has been a core concern among researchers for a long time (Kriegbaum et al., 2018;Morgan & Fuchs, 2007;Mouratidis et al., 2021;Seaton et al., 2014;Skaalvik & Valås, 1999). Whereas there is no doubt about the predictive power of autonomous motivation on academic achievement-this is performing activities for their own sake, with volition and choice, because of the inherent value or enjoyment the activity brings- (Cerasoli et al., 2014;Hattie, 2009;Roth, 2019;Šakan et al., 2023;Taylor et al., 2014) studies have long suggested the possible existence of bidirectional relations between motivational constructs and student achievement ( Jang et al., 2024). ...
Background
While it's clear that autonomous motivation significantly boosts academic success, there are conflicting findings regarding the opposite relation. Besides, the reciprocal relations among controlled motivation and achievement present mixed results. Adequately distinguishing between variations among individuals and within individuals results key to acknowledge such relations.
Aim
This longitudinal study examines the reciprocal relations between controlled and autonomous forms of motivation and academic achievement using the RI‐CLPM methodology.
Sample
Participants were 1042 high school students (M = 16 years, 52% male adolescents) from 16 different high schools in urban and rural areas.
Methods
A random intercept cross‐lagged panel model (RI‐CLPM) was tested to estimate whether students' autonomous and controlled motivation predicted achievement and/or vice versa. Independent models were estimated for the two types of motivation.
Results
Overall, the RI‐CLPM results indicated a unidirectional relationship between autonomous motivation and achievement. As for controlled motivation, the results of RI‐CLPM models showed no reciprocal relationship between this type of motivation and achievement.
Conclusions
These results underline the importance of taking within‐ and between‐person processes into account when analysing reciprocal relations and provide crucial insights for enhancing student motivation and achievement in diverse educational contexts.
... Children inherit both the environment and their genes from their parents. Research indicates that intelligence is one of the most powerful predictors of educational and occupational success (e.g., Boman, 2023;Colom & Flores-Mendoza, 2007;Kriegbaum et al., 2018;Kuncel & Hezlett, 2007;Marks, 2020Marks, , 2022Roth et al., 2015;Sackett et al., 2009;Strenze, 2007). Its predictive validity does not substantially decrease after controlling for SES. ...
... Согласно предыдущим выводам коллег, психометрический интеллект был и остается наиболее сильным и универсальным индикатором академического успеха [1]. Более того, осознанная саморегуляция рассматривается как универсальный ресурс, способствующий успеху в течение всего образовательного процесса [7; 20], в то время как мотивация сопровождается умеренным, но значительным влиянием на успеваемость [21]. Школьная вовлеченность как внешний индикатор мотивации также имеет существенную связь с академическими успехами: чем выше уровень вовлеченности, тем выше результаты [18; 22]. ...
p>The research described in the article is devoted to the study of the relationship between the ideas of boys and girls about their future and the results they received on the unified state exam (USE). A two-stage study was conducted, during which the meaningful elements of predicting the future of the participants were first identified, and then these data were compared with the educational achievements of the respondents. The study sample consisted of 150 people aged 18 to 28 years. At the first stage, the I.S. Cohn methodology "I am in five years" was used, at the second stage, the respondents were presented with the results of the first stage and asked questions about their achievements. The study showed that boys and girls who received high results on the Unified State Exam more often used the words "I know" and "I will do" in their ideas about the future. A connection was found between the grades obtained on the Unified State Exam and the assessment of satisfaction with one's achievements. Boys and girls who passed the exam with high scores rate the achievement of their plans lower than those who passed the exam with a lower score. The lack of achievements with high scores obtained on the Unified State Exam is associated by respondents with changed circumstances or lack of time, and with good results – with strict adherence to plans. The results obtained can be useful in practical work with modern boys and girls when discussing plans for the future with them.</p
... In his decade-spanning work, Hattie (2008) showed that intelligence strongly affects school achievement. Several studies found substantial evidence for positive associations between intelligence and academic achievement ; for a meta-analysis, see Kriegbaum et al., 2018). Moreover, research indicates that intelligence benefits learning particularly in areas in which learners possess limited prior knowledge such as early literacy (Beckmann & Goode, 2010;Beier & Ackerman, 2005;Dinsmore et al., 2014;James et al., 2019;Li et al., 2012;Schneider & Preckel, 2017). ...
Family background factors like socioeconomic status (SES) and migration background, along with child characteristics such as gender and intelligence, significantly influence early childhood competencies. Children from families with low SES and/or migration background often show weaker literacy outcomes than their peers. Game-based learning via apps can support children's competency development, but its effects may depend on children's app usage and how it interacts with child and family characteristics. We examined the effects of specifically developed literacy apps with N = 500 preschoolers (M Age = 60.96 months). The intervention was successful: Children who used our literacy apps obtained greater literacy competencies compared to a control group, even after accounting for family and child characteristics. Longer app usage time was associated with literacy gains, independent of SES and migration background, with a U-shaped relation, but only among girls. Consequently, game-based learning via apps can be successful; however, individual differences should be considered.
... When students achieve satisfactory learning outcomes, it shows that they have successfully mastered the material and can apply it in various situations (Ofem et al., 2024). Good learning outcomes also motivate for students to continue learning and improve their abilities (Kriegbaum et al., 2018). Thus, high learning motivation and satisfactory learning outcomes are important components in creating an effective learning environment and positively influence students' overall development (McInerney, 2019). ...
The quality of learning requires innovation in teaching methods to improve student motivation, activity and learning outcomes. This pseudo-experimental research aims to determine the differences in motivation, activity, and learning outcomes of students taught using the Discovery Learning learning model assisted by student books (DL 1) and videos (DL 2). This study involved all students of class X at SMAN 8 Makassar and randomly selected class X.3 and X.7 as samples. Data were collected using a motivation questionnaire, observation sheet, and learning outcome test. The data collected were analyzed using descriptive statistics in the form of averages and inferential in the Manova Test. The results of this study show that there is a significant difference in the effect of the two treatments on student motivation, activity, and learning outcomes. Where students who were taught using a video-assisted discovery learning model were better than student books, the findings in this study imply that increasing the motivation, activity, and learning outcomes of students in high school should be given more attention through the application of appropriate learning models and media
... On a theoretical level, motivation (cognitive antecedent) affects academic achievement (behavioral outcome) in multiple ways (Kriegbaum et al., 2018;Lewin, 1936;Urhahne & Wijnia, 2023). That is, different motivational variables (e.g., self-efficacy, self-determined motivation, achievement goals), as well as other learning-relevant aspects (e.g., quality of teacher instructions), explain a student's degree of academic achievement. ...
Background. Accurately judging student motivation enables individualized and student-centered instruction. However, teachers in school tend to judge student motivation inaccurately. Low availability of motivation-related cues, like mastery-approach goals and work-avoidance goals, may explain neglecting these cues in judging motivation. Instead, gender and academic achievement might be overly utilized because they are easily available.
Aim. To test teachers’ utilization of highly and equally available cues when judging student motivation.
Methods. In the first vignette experiment, pre-service and in-service teachers (N = 205) judged eight fictitious students’ motivation sequentially. Teachers received either achievement goal cues (EG1) or additionally gender and academic achievement cues (EG2), creating an information-adequate environment. In Experiment 2, newly recruited pre-service and in-service teachers (N = 213) evaluated the same vignettes in the same groups, but vignettes were presented simultaneously, and cues had to be memorized, resulting in an information-rich environment. Teachers then formed judgments based solely on their memory without further access to the vignettes.
Results. When teachers judged student motivation sequentially, they strongly used mastery-approach goals and work-avoidance goals—regardless of whether other cues were available. In memory-based judgments, teachers primarily used gender and academic achievement.
Conclusions. Results demonstrate that in information-rich environments where cues have to be memorized, teachers tend to overlook motivation-relevant cues. Instead, they focus more on cues that do not inherently indicate motivation. These findings suggest that teachers could benefit from assessment environments, like formative assessment, that allow for the direct processing of available cues to better judge student motivation.
... However, statistically we cannot rule out a crosssectional self-enhancement model where trait-like academic self-concept has a unidirectional effect on trait-like academic achievement, rather than the other way round, or a model where both trait-like academic achievement and trait-like academic self-concept are affected, that is, confounded, by some third variable. The confounding variable could be, for example, cognitive ability, which has an association both with academic self-concept and achievement (Deary et al., 2007;Kriegbaum et al., 2018;Roth et al., 2015). Both the cross-sectional self-enhancement model and a ''full confounding'' model would exhibit close fit if applied to simulated data similarly as the present model with a cross-sectional unidirectional effect of achievement on self-concept (see Figure 2). ...
Plain Language Summary
The so called reciprocal effects model of academic self-concept and achievement might be wrong
In a recent aggregation of findings from several studies, a so called meta-analysis, researchers claimed to have found evidence that academic self-concept (that is, self-perceived academic competence) had an increasing effect on future academic achievement and that academic achievement, likewise, had an increasing effect on future academic self-concept. However, the used method of statistical analysis is known to often deliver defective results. In the present study, we analyzed the same data and found that the data can be claimed to show both an increasing and a decreasing effect of academic self-concept on future academic achievement. Due to these incongruent results, we believe that the claims in the previous meta-analysis lack solid support and can be challenged. There may still exist a correlation between academic self-concept and achievement, but correlations do not prove causal effects. We also carried out simulations, and these showed that results as in the challenged meta-analysis can be observed even without any true increasing effects between academic self-concept and achievement. In the present article, we also present something we call the extended skill development model (ESDM).
... Across the two studies, our findings thus suggest that growth mindset instructors foster the stated positive and reduce the stated negative antecedents and indicators of high academic achievement and well-being in students more strongly than fixed mindset instructors do. Whereas motivation, particularly success expectancies (e.g., Kriegbaum et al., 2018) and help-seeking when difficulties arise (e.g., Fong et al., 2023), are known to be positively related to academic achievement, the opposite has been found for performance-avoidance goals (e.g., Wirthwein et al., 2013). High levels of positive emotions and low levels of negative emotions or stress (as found in the growth mindset condition) furthermore indicate high affective wellbeing. ...
Experimental evidence of effects of instructors’ growth or fixed mindsets has so far been provided only by studies on U.S. university students. Research outside the US and on primary and secondary school students has relied on correlational data. In two preregistered vignette experiments with secondary school and university students in Germany (N = 214 in total), we therefore tested for effects of fictitious instructors’ growth and fixed mindsets. Both studies revealed detrimental effects of fictitious instructors’ fixed mindsets. In Study 1, the fixed mindset teacher elicited lower anticipated positive emotions, stronger anticipated negative emotions, stronger anticipated performance-avoidance goals, and less anticipated help-seeking in fifth-to-seventh graders compared with the growth mindset teacher. In Study 2, the fixed mindset professor elicited lower anticipated positive emotions, stronger anticipated negative emotions, higher anticipated stress, less anticipated help-seeking, lower anticipated success expectancies, and less anticipated motivation in university students than the growth mindset professor did. Moreover, larger effects were found for female than male university students. These findings provide a more fine-grained perspective on the risks of being taught by a fixed mindset teacher or professor and support the idea that growth mindset instructors are an important part of a learning environment that helps every student flourish.
... This conceptualization aligns with the way that intelligence is understood across the various literatures we are discussing. For example, commonly-used individual difference measures such as IQ scores are intended to predict goal attainment in a variety of domains [16], [17], [18]. Similarly, collective intelligence metrics are used to predict group goal attainment across different kinds of tasks [19]. ...
A core part of human intelligence is the ability to work flexibly with others to achieve both individual and collective goals. The incorporation of artificial agents into human spaces is making increasing demands on artificial intelligence (AI) to demonstrate and facilitate this ability. However, this kind of flexibility is not well understood because existing approaches to intelligence typically focus either on the individual or the collective level of analysis. At the individual level, intelligence is seen as an individual-difference trait that exists independently of the social environment. At the collective level intelligence is conceptualized as a property of groups, but not in a way that can be used to understand how groups can make group members smarter or how group members acting as individuals might make the group itself more intelligent. In the present paper we argue that by focusing either on individual or collective intelligence without considering their interaction, existing conceptualizations of intelligence limit the potential of people and machines. To address this impasse, we identify and explore a new kind of intelligence - socially-minded intelligence - that can be applied to both individuals (in a social context) and collectives (of individual minds). From a socially-minded intelligence perspective, the potential intelligence of individuals is unlocked in groups, while the potential intelligence of groups is maximized by the flexible, context-sensitive commitment of individual group members. We propose ways in which socially-minded intelligence might be measured and cultivated within people, as well as how it might be modelled in AI systems. Finally, we discuss ways in which socially-minded intelligence might be used to improve human-AI teaming.
... In addition, given the extensive evidence of the relationship between motivation and academic achievement, researchers have examined the 5E model's effects on motivation (Kriegbaum et al., 2018). Within the situated expectancy value theory (SEVT) framework, efficacy has a strong relationship to performance whereas subjective task values have a strong relationship to course taking, task choices and other behaviors. ...
We conducted a comprehensive, systematic review and meta-analysis on the effects of the BSCS 5E Instructional Model—and its related variants—on science, math, and motivation outcomes. The 5E Instructional Model is a framework for delivering STEM instruction that is based on constructivist learning theory; it has been used throughout the U.S. and other countries, particularly in Turkey. Despite its wide usage, no comprehensive systematic review and meta-analysis on the effects of 5E and related models has yet been conducted. Our search and screening procedures yielded 61 randomized controlled trial studies, estimating 156 effect sizes; 70% of studies met WWC standards with or without reservations. We found that the 5E instructional model resulted in improved science outcomes (g=0.82, 95% CI [0.67, 0.97]), but a large amount of heterogeneity requires some caution (t=0.56). We explored numerous explanations for the effect heterogeneity and provided practical recommendations
... Cognitive ability is the strongest predictor of academic success (Roth et al. 2015). This consists of abilities related to thinking, memory, and information processing of learning materials, which are generally unrelated or minimally related to SRL, motivation, or life satisfaction (Köller et al. 2019;Kriegbaum, Becker, and Spinath 2018). ...
Literacy skills and academic achievement were examined in this study. An individual's capacity to learn and apply new skills relies heavily on their ability to read and write well. In this study, a meta-analysis approach is used to calculate the correlation with the fixed-effect model, which is quantitative. The first step in formulating research questions is to identify relevant research and then look for research that doesn't publish the r-value. There are 29 articles in the sample. This study's findings on the relationship between literacy skills and student academic achievement are free from publication bias because the fixed-effect funnel plot model shows a variety of sample sizes with the asymmetric distribution. After seeing the forest plot before and after trimming and filling it, it was clear that the results of the summary effect were evident. So, the fixed-effect model of the relationship between students' reading skills and how well they do in school is very likely to be true.
... In terms of practical implications, one should first note that all coefficients, especially for student achievement, were small. This is not surprising considering the importance of individual learner prerequisites (e.g., cognitive abilities, prior knowledge) for students' academic development (Kriegbaum et al., 2018). Hence, our study points towards the relevance of teacher and parent support as additional factors that can make small, but potentially meaningful contributions to adolescents' academic development over time. ...
Teachers and parents are two important socializers for students. During adolescence, relationships with different social interaction partners undergo significant changes. However, empirical evidence regarding potential shifts in the importance of parents’ and teachers’ support for multiple dimensions of adolescents’ academic development over time is still lacking. Additionally, effects of teacher and parent support may differ depending on student background characteristics (gender, migration background, and socioeconomic status), and better understanding these issues is vital for theory building and for supporting students with diverse backgrounds to thrive academically. The present study therefore analyzed data from a longitudinal study with 3,470 adolescents from Germany who participated in yearly assessments from fifth to eighth grade. Results from longitudinal structural equation modelling revealed that parent and teacher support predicted adaptive changes in adolescents’ academic identification with school, school satisfaction, and truancy, whereas only parent support had a positive association with students’ self-concept of academic aptitude and achievement on standardized tests. These associations remained invariant over time and when we used parent reports instead of student reports on support. Moreover, the findings did not differ depending on students’ gender, migration background, or socioeconomic status. We discuss implications of these results for theory and research on adolescent development, and for practice.
... A substantial amount of literature indicates that general cognitive ability and motivation are two of the primary determinants of academic success (e.g., [62][63][64][65][66][67]). Furthermore, there is extensive research evidence that motivation and related constructs (e.g., achievement goals) have incremental validity beyond cognitive ability in predicting academic achievement (e.g., [67][68][69][70][71][72][73][74][75]). ...
Background
Despite expectancy theory’s widespread appeal and influence as a framework for motivation in organizational and educational settings, studies that have examined the theory’s validity for performance-based outcomes, particularly with academic performance as the criterion, have been characterized by inconsistent results. Given numerous methodological concerns associated with past studies (e.g., prevalence of between-person rather than within-person design), we examined the predictive validity of expectancy theory for academic performance using methods that were consistent with the theory’s original conceptualization. Additionally, we assessed the validity of the theory for students’ study effort.
Methods
The final sample included 123 undergraduate students who reported their final grades in four courses. Study effort and other variables were measured with self-report surveys. Because course grades were nested within each person, multilevel modeling was used to test study hypotheses.
Results
Both the valence model and the force model predicted a student’s current study effort, but contrary to expectations, neither model predicted a student’s final course grades. In contrast, both valence for academic success and the simplified force model (based only on valence and expectancy) predicted current study effort, final course grades, and explained incremental variance beyond cognitive ability. Furthermore, the predictive validity of this force model was relatively stable across the 11 weeks of the study.
Conclusions
Based on methods congruent with expectancy theory’s original framework, we find that the force model does not predict academic performance. An alternative version of the model, however, predicts course grades and has incremental validity over cognitive ability. Our results have several significant theoretical and practical implications.
... Similar to EFs, intelligence is a multifaceted construct hypothesized to differentiate across development (Tucker-Drob, 2009), with its neural substrate localized in a parieto-frontal brain network (Jung & Haier, 2007). Moreover, intelligence predicts important developmental outcome variables such as school achievement (Kriegbaum et al., 2018). ...
... Similar findings to the study of Kriegbaum and Spinath (2018) claim that motivated students are more likely to set challenging goals, have higher self-efficacy, and exhibit adaptive learning strategies, all contributing to academic success. Moreover, according to research conducted by Sotos-Martínez et al. (2023), motivation directly impacts students' achievement by influencing their engagement, effort, and persistence in various academic tasks. ...
This study aimed to determine the relationship and predictive power of academic self-concept and motivation to tertiary students' Mathematics achievement. This descriptive correlational research was conducted with 347 college students in selected tertiary schools in Davao de Oro. Mean scores, Pearson's Correlation Coefficient, and linear regression analysis were utilized to analyze the data. The study's result revealed that the students' academic self-concept is moderate, and their learning motivation is high. The study also reported a very satisfactory level of performance in Mathematics. Further, academic self-concept and motivation significantly predict students' mathematics achievement in Mathematics. These findings suggest that academic self-concept and motivation are vital factors in enhancing students' achievement in Mathematics. This study recommended integrating academic self-concept and motivation to amplify students' achievement in Mathematics, promoting a comprehensive approach to learning success.
... Standardised Mean Differences (SMDs) were calculated using Cohen's d. To obtain estimates that were as specific as possible, we adjusted for covariates that may affect reading acquisition, such as sex (Torppa et al., 2020) and general intelligence (Kriegbaum et al., 2018). Additionally, performance in another major area of learning, that is mathematics (Harlaar et al., 2012), was controlled, due to its well-known substantial covariance with reading ability both in the general population and in learning disorders (e.g., De Smedt, 2022). ...
Children with dyslexia (CwD) often report poor psychological well‐being. We examined (i) whether anxiety, self‐concept and reading motivation in CwD differed from those of typically developing children (TDC; case–control design, Study 1a) and (ii) whether these differences mirrored the linear relationships that these variables present with reading ability in the TDC group (dimensional approach, Study 1b). In Study 1a, 34 CwD were compared with 191 TDC in grades 4–8 on anxiety, self‐concept, reading motivation and reading strategy using self‐reports (controlling for sex, intelligence and math ability scores). In Study 1b, the differences that emerged in Study 1a were compared with the results obtained from a simulation procedure that generated dyslexia observations under the assumptions of a dimensional hypothesis. The CwD group presented small‐to‐moderate difficulties, which partially mirrored the predictions in the TDC group. However, violations of predictions based on the population without dyslexia were found for reading self‐concept, social anxiety and reading competitiveness. In sum, children's diagnoses affect their self‐perception as readers and social anxiety in a way that cannot be inferred from linear relationships. CwD need support to preserve an adequate image of themselves as readers and cope with social anxiety.
... Third, published systematic literature reviews have already shown that individual characteristics can explain differences in students learning (see, for example, Hattie, 2023or Jansen et al., 2022 for overviews of systematic literature reviews with meta-analysis between students' individual differences and learning or motivation). Examples of individual characteristics moderating the relation between achievement and motivation within systematic literature reviews with metaanalysis are students' achievement level (Kriegbaum et al., 2018); school level (Koenka et al., 2021); level of prior knowledge/level of education moderating effects of simulation-based learning on the development of complex skills and competencies (Chernikova et al., 2020). Further examples of students' individual differences moderating the effectiveness of interventions within a systematic literature review with meta-analysis are students' gender (Collins et al., 2019) and culture (Wong et al., 2021). ...
Through this editorial, we will provide guidance to readers and potential authors of systematic literature reviews with or without meta-analysis that aim to submit this type of research to Learning and Individual Differences. We also aim at providing guidance on a more general level beyond this specific journal and to point out relevant considerations to authors. In this, we provide some supporting documentation and guidance to authors in the field of learning and individual differences, pointing them to the most important guidelines to conduct systematic literature reviews, irrespective of the journal in which they seek publication.
... Accordingly, needsupportive teaching explained less variance in student achievement than in student motivation. Arguably, achievement is somewhat less malleable by teachers than is student motivation as achievement depends more strongly on student characteristics such as cognitive ability (Kriegbaum et al., 2018;Lavrijsen, Vansteenkiste, et al., 2022;Roth et al., 2015), leaving less room for teaching practices to predict students' academic performance. Indeed, Roorda et al.'s (2017) relatively recent meta-analysis reported achievement to generally be less dependent on teaching quality than students' engagement. ...
... Standardised Mean Differences (SMDs) were calculated using Cohen's d. To obtain estimates that were as specific as possible, we adjusted for covariates that may affect reading acquisition, such as sex (Torppa et al., 2020) and general intelligence (Kriegbaum et al., 2018). Additionally, performance in another major area of learning, that is mathematics (Harlaar et al., 2012), was controlled, due to its well-known substantial covariance with reading ability both in the general population and in learning disorders (e.g., De Smedt, 2022). ...
Background: Children with dyslexia often report poor psychological well-being. We examined i) whether anxiety, self-concept, and reading motivation in children with dyslexia differed from those of controls (case-control design, Study 1a), and ii) whether these differences mirrored the linear relationships that these variables present with reading ability in children without dyslexia (dimensional approach, Study 1b).Methods: In Study 1a, 34 “Children with Dyslexia” (CwD) were compared with 191 “Typically Developing Children” (TDC) in grades 4–8 on anxiety, self-concept, reading motivation, and reading strategy using self-reports (controlling for sex, intelligence, and math ability scores). In Study 1b, the differences that emerged in Study 1a were compared with the results obtained from a simulation procedure that generated dyslexia observations under the assumptions of a dimensional hypothesis.Results: The CwD group presented small-to-moderate difficulties, which partially mirrored the predictions in the TDC group. However, violations of predictions based on the population without dyslexia were found for reading self-concept, social anxiety, and reading competitiveness.Conclusions: Children’s diagnoses affect their self-perception as readers and social anxiety in a way that cannot be inferred from linear relationships. Children with dyslexia need support to preserve an adequate image of themselves as readers and to cope with social anxiety.
Aim . To determine cognitive and non-cognitive indicators of readiness for school, which are predictors of academic success at the stage of primary general education.
Methodology. The results of the study of psychological readiness for learning and indicators of academic performance in primary school are compared. Factor analysis is used to determine the structure of school readiness, the contribution of cognitive and non-cognitive factors to school success. Sample composition: primary school students (N = 222; 6–7 years old), primary school teachers (N = 9). Diagnostic methods: "Progressive matrices" by J. Raven (series "A"), "Visual-motor gestalt test" by L. Bender, "Exclusion of subjects", "Establishing the sequence of events", "Retelling the text", "Assessment of school motivation of primary school students" by N. G. Luskanova, "Methodology for studying socio-psychological adaptation to school" by
M. Alexandrovskaya.
Results. The indicators of the child's mental development that have the greatest impact on academic performance are determined: the level of development of nonverbal and conceptual thinking, the formation of visual-spatial perception and graphomotor skills, activity, arbitrariness of behavior, the ability to self-regulation in intellectual activity. It is established that in relation to the forecast of academic performance, the teacher's assessment of children's readiness for learning is no less accurate than the data of a screening psychodiagnostic examination. Cognitive and metacognitive factors of school readiness reveal close links with academic performance. Non-cognitive factors, presumably, affect the process of socialization, the emotional well-being of the child at school. Of particular importance for school success are such systemic personality characteristics as activity and arbitrariness.
Research implications . The identification of school-relevant indicators of readiness for learning complements the idea of general patterns in predicting academic success at different stages of education. A comprehensive analysis of various aspects of readiness for learning using multidimensional methods of mathematical statistics allowed us to determine the system of cognitive qualities and personal characteristics of a child necessary for primary school education, to assess the contribution of cognitive, metacognitive and non-cognitive factors of readiness for learning to school success.
Students’ self-efficacy in language learning is not a static attribute but rather a dynamic construct. However, studies have seldom explored how students’ self-efficacy beliefs change over time, whether there are heterogeneities in the pattern of change among students, and what factors are associated with these patterns of change. This study aimed to (1) investigate the changes in English self-efficacy over time; (2) delve into the distinct trajectories of English self-efficacy changes; and (3) examine the relationships between trajectories of English self-efficacy changes and their predictors. A total of 452 students in secondary schools participated in the study. We combined the variable-centered (latent growth curve modeling) and person-centered (growth mixture modeling) approaches in analyzing the three-wave data over a semester. The results of the latent growth curve modeling showed students’ self-efficacy remained stable over the study period in general. Using the growth mixture modeling approach, four trajectories of self-efficacy changes were identified, involving “low decreasing”, “average stable”, “high decreasing” and “high increasing” trends. Higher prior academic achievement and exposure to mastery experience, vicarious experience, and social persuasion predicted the membership of increasing trajectories. Theoretical and practical implications are discussed.
La motivación en el aula es parte crucial para el aprendizaje de los alumnos y en el mundo actual donde la autorregulación de los aprendizajes juega un papel preponderante lograr que la apropiación de los aprendizajes se disfrute es indispensable. Debido a lo anterior el presente estudio cuantitativo e instrumental tiene el interés de contribuir a la medición de dicho constructo, teniendo como objetivos 1) diseñar una escala tipo Likert, con evidencia de validez de contenido, que examine la motivación para el aprendizaje y las actividades escolares en estudiantes universitarios, 2) analizar su validez de constructo y 3) examinar su confiabilidad. Para alcanzar los objetivos se diseñó la Escala de Motivación para el Aprendizaje y Actividades Escolares (EMAAE), la cual se aplicó a una muestra de estudiantes universitarios. Los resultados arrojaron una estructura factorial de cuatro factores: motivación interna por el gusto de aprender, motivación externa por control parental, motivación interna por el gusto por la tarea y motivación externa por busca de reconocimiento, aportando evidencia de validez; respecto a la confiabilidad los valores mostraron índices de consistencia interna adecuados en su mayoría.
The big-fish–little-pond effect (BFLPE) is a well-supported contextual effect that hypothesizes that school-average achievement is negatively related to academic self-concept, even though the relation between individual achievement and self-concept tends to be positive. However, there are some uncertainties about possible moderators of the BFLPE. The bright-student hypothesis assumes that the negative relation between school-average achievement and student self-concept is less strong for higher achieving students. This hypothesis has been tested mainly with measures of individual achievement, but there have been few or no attempts to investigate if the BFLPE varies by individual cognitive ability. The objective of the present study was to provide clarity on the issue by using a measure of cognitive ability, operationalized as students’ verbal, spatial, and inductive abilities, to study the moderating effect of cognitive ability across levels. Multilevel structural equation modeling was used to test the BFLPE in the mathematics and language domains using Swedish representative ninth-grade data (N = 24,771). Support for the BFLPE was found in the mathematics domain (b = −0.32, p < .001) and the language domain (b = −0.23, p < .001). A statistically significant cross-level interaction effect was found between individual cognitive ability and school-average achievement in the mathematics domain (b = 0.22, p < .001) but not in the language domain (b = 0.07, p = .051). This indicated that the negative relation between school-average mathematics achievement and mathematics self-concept was less strong for students with higher cognitive abilities, thus supporting the bright-student hypothesis.
Despite efforts to implement innovative approaches such as flipped learning leveraging computer technology, the challenge of student failure persists. Understanding the factors that contribute to student success in flipped engineering courses remains a critical issue. This study addresses this issue by investigating the impact of student readiness, engagement, and gamified online formative quizzes on the academic achievement of low-achieving students. Logistic regression analysis was conducted on data from 122 university students who failed the pretest. The results reveal that flipped learning readiness, self-reported engagement, and digital footprints significantly influence success. Surprisingly, gamification and certain dimensions of the Flipped Learning Readiness Scale do not have a significant impact. Of note, success decreases with more time spent on quizzes and higher levels of motivation to learn, while success increases with more quiz attempts, indicating the value of seeking feedback. To our knowledge, such a relationship between digital footprints and success has not been reported in flipped engineering classrooms, making our study a novel contribution to the literature. Our findings have practical implications for the use of computers in flipped course design and offer insights into the theory of the testing effect. They highlight the importance of providing special support for overmotivated, underperforming students. They also inform the pedagogical aspects of incorporating digital footprints and formative assessment in flipped learning environments where quiz duration is limited to mitigate potential drawbacks.
Despite ongoing discussions regarding the relevance of Latin in modern education, this language still holds a prominent role in European secondary school curricula. While studying Latin is commonly believed to yield cognitive and linguistic benefits, this argument primarily relies on dated research that often uses methodologies that do not allow to make strong claims justifying the widespread use in education. It also remains unclear to which extent the benefits associated with Latin studies are due to Latin students’ superior pre-existing abilities (preselectivity), or to cognitive transfer effects elicited by studying the language. To delve further into the presence and nature of a potential cognitive advantage of Latin, we gathered data from N = 1,731 secondary school students across three grades. We explored whether a ‘Latin advantage’ exists, and if so, for which subjects, when this advantage arises and how it evolves throughout secondary education. We found that first-year Latin students exhibited higher intelligence scores, superior native language competencies and higher meta-linguistic awareness compared to non-Latin peers, which is in line with the preselectivity account. This performance difference was larger in the second year, but smaller in the last year of secondary education, thereby challenging the notion of cognitive transfer effects attributed to Latin studies. Only one variable, vocabulary, demonstrated a trend in line with cognitive transfer benefits. Longitudinal work is needed to further investigate whether Latin studies result in persisting benefits or whether the ‘Latin advantage’ is merely a reflection of preselection biases.
p>The problem of studying the factors influencing students’ academic achievement does not lose its relevance in modern psychological and pedagogical science. Such interest arises due to current development of ideas about education as a way of developing human capital, increasing well-being and quality of life of people in modern society. The academic achievement of schoolchildren is largely determined by non-cognitive factors, including personality characteristics, motivational indicators and the development of self-regulation. The present work aims to analyze the relationships between non-cognitive predictors of academic achievement of middle and high school students using the network modeling method. Primary data was obtained using the following methods: V.I. Morosanova’s “The Self-Regulation Profile of Learning Activity Questionnaire (SRPLAQ)”, “Academic Motivation Scale - School (AMS-S)”, “Attitude towards learning in middle and high school”, “Big Five Questionnaire — Children version, BFQ-C”. The average score in Russian language and mathematics was used as an indicator of academic achievement. The sample consisted of 307 secondary school students (37.1% boys, age: 10-18 years). The statistical analysis included calculation of descriptive statistics for 28 indicators, and analyses of partial correlation networks, describing the relationships between regulatory and personality variables, as well as the academic achievement of students in grades 5-6, 7-9 and 10-11. The results revealed significant relationships between variables regardless of the period of education, and differences in the structure of partial correlation networks in grades 5-6, 7-8 and 9-11. It was found that the nature of the relationships between non-cognitive predictors and academic achievement varies depending on the period of study. The result showed that the achievement of students in grades 5-6 is significantly and directly correlated to the indicator of openness to new experience, while in grades 7-9 a direct correlation is also found with the general level of attitude towards learning, and in grades 10-11 - with cognitive motivation, neuroticism and conscious self-regulation. The results confirm the known relationships, and also reveal new ones that were not previously discovered in existing research: for example, a negative relationship between academic performance and cognitive motivation. The article concludes with directions for further research of moderator-mediator interactions between non-cognitive variables in their impact on students’ academic achievement.</p
This study evaluated differential item functioning (DIF) in achievement motivation items before and after using anchoring vignettes as a statistical tool to account for group differences in response styles across gender and ethnicity. We applied the nonparametric scoring of the vignettes to motivation items from the 2015 Programme for International Student Assessment (PISA) and examined changes to DIF characteristics between the raw self-report item scores and the vignette-adjusted item scores. Overall, applying the anchoring vignettes changed DIF classification, magnitude, direction, and form for some items. Group-specific response patterns by gender and by ethnicity group were also seen. Our findings contribute to the research literature on observed response styles in PISA motivation items, DIF in PISA items, and changes to DIF characteristics after adjusting self-report item scores with anchoring vignettes.
Information and Communication Technology (ICT) helps people learn is becoming more and more common in the teaching process. This lets learners keep learning by using their mobile devices to access their learning tools. On the other hand, language teachers, who are often both users and creators of teaching and learning activities, do not always know how to use and apply the steps on designing the lesson by infiltrating technology. The purpose of this study is to develop the efficacy of game-based learning multimedia in enhancing student-learning outcomes in the classroom with regard to English grammar. The research development of multimedia game-based learning using the Raiser and Demsey procedure. The trial of product development had passed multiple processes, including: the review from a media expert, which included software changes and visual communication; the review from a content expert, which included material and instructional design; the responses of students to the product's usability and attractiveness; and the review from a content expert. The implication of this study is that the language learning design with the ICT approach is able to fulfil the needs and skills of students. Gamification can enhance the learning process because it can engage and motivate students with games.
This study examines reciprocal effects between self-concept and achievement by considering a long time span covering grades 5 through 9. Extending previous research on the reciprocal effects model (REM), this study tests (1) the assumption of developmental equilibrium as time-invariant cross-lagged paths from self-concept to achievement and from achievement to self-concept, (2) the generalizability of reciprocal relations when using school grades and standardized achievement test scores as achievement indicators, and (3) the invariance of findings across secondary school achievement tracks. Math self-concept, school grades in math, and math achievement test scores were measured once each school year with a representative sample of 3,425 German students. Students’ gender, IQ, and socioeconomic status (SES) were controlled in all analyses. The findings supported the assumption of developmental equilibrium for reciprocal effects between self-concept and achievement across time. The pattern of results was found to be invariant across students attending different achievement tracks and could be replicated when using school grades and achievement test scores in separate and in combined models. The findings of this study thus underscore the generalizability and robustness of the REM.
Individuals differ in their timing of sleep (bed times, rise times) and in their preference for morning or evening hours. Previous work focused on the relationship between academic achievement and these variables in secondary school students. The main aim of the study is to investigate the relationship between chronotype and academic achievement in 10-year-old children (n = 1125) attending 4th grade of primary school. They filled a cognitive test (Culture Fair Intelligence Test, CFT 20-R) and questions about rise times and bed times, academic achievement, conscientiousness and motivation. We used the "scales for the assessment of learning and performance motivation" (SELLMO; Skalen zur Erfassung der Lern- und Leistungsmotivation for motivation), the short version of the Five-Factor Personality Inventory Children (FFPI-C) to measure conscientiousness, and the Composite Scale of Morningness (CSM) to assess morningness-eveningness. Mean CSM score was 37.84 ± 6.66, midpoint of sleep was 1:36 ± 00:25 and average sleep duration (time in bed) was 10:15 ± 0:48. Morningness orientation was positively related to intelligence, conscientiousness and learning objectives. Eveningness orientation was related to avoidance performance objectives and work avoidance. Early midpoint of sleep, conscientiousness and intelligence were associated with better grades. The multivariate model showed that intelligence was the strongest predictor of good grades. Conscientiousness, motivation, younger age and an earlier midpoint of sleep were positively related to good grades. This is the first study in primary school pupils, and it shows that the relationship between evening orientation and academic achievement is already prevalent at this age even when controlling for important predictors of achievement.
This exploratory review compares academic self-concept and self-efficacy research. From the conceptual perspective, self-concept emerges as a more complex construct incorporating both cognitive and affective responses toward the self and is heavily influenced by social comparison. Self-efficacy, in contrast, concerns primarily cognitive judgments of one's capabilities based on mastery criteria. Despite these differences, the 2 constructs demonstrate similar internal structures that are multifaceted and hierarchical. From the methodological perspective, self-efficacy research demonstrates more consistent operational definitions, more context-specific assessment of both the construct and outcomes, and more frequent implementation of experimental, as opposed to correlational, designs. In the past, self-concept research has used more general indexes of both self-concept and achievement and depends mostly on correlational rather than on experimental data. These differences, although not necessarily inherent in construct definitions, contribute to self-efficacy's superior predictive and explanatory utility in past research.
Achievement behavior is defined as behavior directed at developing or demonstrating high rather than low ability. Ability can be conceived either with reference to the individual's own past performance or knowledge, a context in which gains in mastery indicate competence, or as capacity relative to that of others, a context in which a gain in mastery alone does not indicate high ability. To demonstrate high capacity, one must achieve more with equal effort or use less effort than do others for an equal performance. The conditions under which these different conceptions of ability function as individuals' goals and the nature of subjective experience in each case are specified. Different predictions of task choice and performance are derived and tested for each case using data from previously published studies. The effects of task and ego involvement, task choice, and self-perceptions are discussed. (125 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Research conclusions in the social sciences are increasingly based on meta-analysis, making questions of the accuracy of meta-analysis critical to the integrity of the base of cumulative knowledge. Both fixed effects (FE) and random effects (RE) meta-analysis models have been used widely in published meta-analyses. This article shows that FE models typically manifest a substantial Type I bias in significance tests for mean effect sizes and for moderator variables (interactions), while RE models do not. Likewise, FE models, but not RE models, yield confidence intervals for mean effect sizes that are narrower than their nominal width, thereby overstating the degree of precision in meta-analysis findings. This article demonstrates analytically that these biases in FE procedures are large enough to create serious distortions in conclusions about cumulative knowledge in the research literature. We therefore recommend that RE methods routinely be employed in meta-analysis in preference to FE methods.
This study investigated how affective factors like attitude and motivation contribute to science achievement in PISA 2006 using linear structural modeling. The data set of PISA 2006 collected from 4942 fifteen-year-old Turkish students (2290 females, 2652 males) was used for the statistical analyses. A total of 42 selected items on a four point Likert-type scale were initially subjected to Exploratory Factor Analysis (EFA) resulting in seven factors with total variance of 64.82%. Confirmatory Factor Analysis (CFA) was later performed for cross-validation of factor structures of PISA 2006 data. Furthermore, Structural Equation Modeling (SEM) was also utilized to test the proposed model representing the relationship among affective factors and Turkish students' science achievement scores in PISA 2006. The results indicated that the hypothesized model fits data well. The results also revealed that, in general, affective factors contributed significantly either positively or negatively to 15 year-old students' science achievement. In addition, affective factors were observed to be predictors of the science achievement based on PISA 2006 Turkish data set, but they are not good predictors due to their low magnitude. In light of the findings, implications are presented for further studies.
Rosenthan's (1979) concept of fail-safeN has thus far been applied to probability levels exclusively. This note introduces a fail-safeN for effect size.
This article investigates gender differences in 181 gifted and 181 average-ability sixth graders in achievement, academic self-concept, interest, and motivation in mathematics. Giftedness was conceptualized as nonverbal reasoning ability and defined by a rank of at least 95% on a nonverbal reasoning subscale of the German Cognitive Abilities Test. Mathematical achievement was measured by teacher-assigned grades and a standardized mathematics test. Self-concept, interest, and motivation were assessed by questionnaire. In both ability groups, boys earned significantly higher test scores but there were no gender differences in grades. Girls scored lower on measures of academic self-concept, interest, and motivation. Gender differences were larger in gifted than in average-ability students. Ability group differences for self-concept and interest were only found for boys in favor of the gifted. Results support the assumption that gender differences in self-concept, interest, and motivation in mathematics are more prevalent in gifted than in average-ability students.
This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; M(age) = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies.
This study investigates the effects of class-average ability (intelligence) and class type (gifted vs. regular) on Math academic self-concept. The sample comprised 722 fifth-grade students (376 female) in a setting of full-time ability grouping at the top track of the German secondary high school system. Students came from 34 different classes at five schools; nine of these classes were part of a gifted track (n = 179). Academic self-concept and school grades were assessed by a self-report questionnaire, intelligence by a standardized test. Higher class-average ability led to lower academic self-concepts after controlling for the positive influence of individual ability (contrast effect). Class type had a counterbalancing positive effect on self-concept (assimilation effect). For students in gifted classes, both effects were of comparable size. Thus, no evidence for a big-fish-little-pond effect (stronger contrast than assimilation effect) was found. Effects of individual and group level ability were partially mediated by school grades. Implications for educational practice of highly able students are discussed.
An adjusted rank correlation test is proposed as a technique for identifying publication bias in a meta-analysis, and its operating characteristics are evaluated via simulations. The test statistic is a direct statistical analogue of the popular "funnel-graph." The number of component studies in the meta-analysis, the nature of the selection mechanism, the range of variances of the effect size estimates, and the true underlying effect size are all observed to be influential in determining the power of the test. The test is fairly powerful for large meta-analyses with 75 component studies, but has only moderate power for meta-analyses with 25 component studies. However, in many of the configurations in which there is low power, there is also relatively little bias in the summary effect size estimate. Nonetheless, the test must be interpreted with caution in small meta-analyses. In particular, bias cannot be ruled out if the test is not significant. The proposed technique has potential utility as an exploratory tool for meta-analysts, as a formal procedure to complement the funnel-graph.
- U Neisser
- G Boodoo
- T J J Bouchard
- A W Boykin
- N Brody
- S J Ceci
Neisser, U., Boodoo, G., Bouchard, T. J. J., Boykin, A. W., Brody, N., Ceci, S. J., et al.
(1996). Intelligence: Knowns and unknowns. American Psychologist, 51, 77-101.