Seeing the Connection: A Systematic Review of Meta-Analyses on the Link Between Teacher-Student Relationships and Student Outcomes

Scientific Conference (2023, August 25)

Theoretical background School climate is a key construct with great potential to impact student outcomes. The construct is multidimensional and includes, for instance, academic, community, safety, and ... [more ▼]

Theoretical background School climate is a key construct with great potential to impact student outcomes. The construct is multidimensional and includes, for instance, academic, community, safety, and institutional environment aspects (Wang & Degol, 2016). While the dimensions may vary, researchers widely agree that teacher-student relationships play a vital role in establishing a positive school climate (Wang et al., 2020). Their role can be explained by Bronfenbrenner's (1979) bioecological theory identifying the driver of human development as the interaction with the persons in our closest (proximal) environment. Thus, in a school setting, emotional warmth and closeness or conflict and dependence in teacher-student relationships should also be associated with positive/negative student outcomes. Several meta-analyses uncovered significant associations between teacher-student relationships and school engagement, good peer relationships, executive functioning, well-being, and reductions in aggressive or disruptive behaviors (Endedijk et al., 2021; Nurmi, 2012; Roorda et al., 2011; Vandenbroucke et al., 2018). However, these meta-analyses differed in their methods and substantive findings. Moreover, the extant literature is ambiguous about which moderators (e.g., age) influence these relationships. Furthermore, the reporting and quality of meta-analyses in this field vary considerably, which can compromise the reliability and validity of their findings. Aims Given these research gaps, we systematically searched and reviewed the meta-analytic literature (Cooper & Koenka, 2012) to provide an overview of correlations between teacher-student relationships and student outcomes. In doing so, we examined three research questions: 1. To what extent are academic, behavioral, socio-emotional, motivational, and cognitive student outcomes associated with teacher-student relationships in the meta-analytic literature? 2. Which moderators influence these associations? 3. What is the methodological quality of the included meta-analyses? Methodology After preregistration, a systematic literature search was conducted. During several screening rounds, we identified 24 appropriate meta-analyses that included approximately meta-analytic 130 effect sizes for over one million students. From these meta-analyses, we extracted effect sizes on the association between teacher-student relationships and academic, behavioral, socio-emotional, motivational, and general cognitive student characteristics. We summarized the results for research questions 1 and 2 and developed a narrative overview. For research question 3, we assessed the quality of the meta-analyses using the AMSTAR-2 scale (adapted to correlational studies in psychology and education research; Shea et al., 2017). Findings and their significance Looking at the teacher-student relationship aspect of school climate, a variety of outcome variables were analyzed. The strongest associations were shown for negative teacher-student relationships with student behavior problems (r = .35 bis .57; Nurmi, 2012). Positive teacher-student relationships showed the strongest association with school involvement (r = .26 bis .34; Roorda et al., 2011), prosocial, externalizing, and internalizing behaviors (r = .25; Endedijk et al., 2021), and learning motivation combined with student involvement (r = .23; Wang et al., 2020). Age and grade level were the most frequently examined moderators, with partially contradicting findings. Gender differences, on the other hand, were found less frequently. At the same time, an informant effect was frequently examined, that is, whether and in what ways teachers, student peers, or the students themselves rated the teacher-student relationship. For research question 3, we discuss differences in reporting and the quality range of meta-analyses. With this preregistered systematic review of meta-analyses, we summarize the research landscape on correlates of the teacher-student relationship aspect of school climate. Following our findings and the bioecological theory, teachers should be made aware of the impact of teacher-student relationships and how they could contribute to a positive school climate via relationship building. Some interventions to improve these important relationships have already been meta-analytically studied with promising results (Kincade et al., 2020). Next, we need experiments to causally confirm positive teacher-student relationships as an effective strategy for improving academic, behavioral, socio-emotional, motivational, and cognitive student outcomes and school climate at large. Finally, future research should structure the broad range of conceptualizations of teacher-student relationships and review the variety of theories to explain their impact on student outcomes. References Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Harvard university press. Cooper, H., & Koenka, A. C. (2012). The overview of reviews: Unique challenges and opportunities when research syntheses are the principal elements of new integrative scholarship. American Psychologist, 67(6), 446–462. https://doi.org/10.1037/a0027119 Endedijk, H. M., Breeman, L. D., van Lissa, C. J., Hendrickx, M. M. H. G., den Boer, L., & Mainhard, T. (2021). The Teacher’s Invisible Hand: A Meta-Analysis of the Relevance of Teacher–Student Relationship Quality for Peer Relationships and the Contribution of Student Behavior. Review of Educational Research, 003465432110514. https://doi.org/10.3102/00346543211051428 Kincade, L., Cook, C., & Goerdt, A. (2020). Meta-Analysis and Common Practice Elements of Universal Approaches to Improving Student-Teacher Relationships. Review of Educational Research, 90(5), 710–748. https://doi.org/10.3102/0034654320946836 Nurmi, J.-E. (2012). Students’ characteristics and teacher–child relationships in instruction: A meta-analysis. Educational Research Review, 7(3), 177–197. https://doi.org/10.1016/j.edurev.2012.03.001 Roorda, D. L., Koomen, H. M. Y., Spilt, J. L., & Oort, F. J. (2011). The Influence of Affective Teacher–Student Relationships on Students’ School Engagement and Achievement: A Meta-Analytic Approach. Review of Educational Research, 81(4), 493–529. https://doi.org/10.3102/0034654311421793 Shea, B. J., Reeves, B. C., Wells, G., Thuku, M., Hamel, C., Moran, J., Moher, D., Tugwell, P., Welch, V., Kristjansson, E., & Henry, D. A. (2017). AMSTAR 2: A critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ, j4008. https://doi.org/10.1136/bmj.j4008 Vandenbroucke, L., Spilt, J., Verschueren, K., Piccinin, C., & Baeyens, D. (2018). The Classroom as a Developmental Context for Cognitive Development: A Meta-Analysis on the Importance of Teacher–Student Interactions for Children’s Executive Functions. Review of Educational Research, 88(1), 125–164. https://doi.org/10.3102/0034654317743200 Wang, M.-T., & Degol, J. L. (2016). School Climate: A Review of the Construct, Measurement, and Impact on Student Outcomes. Educational Psychology Review, 28(2), 315–352. https://doi.org/10.1007/s10648-015-9319-1 Wang, M.-T., L. Degol, J., Amemiya, J., Parr, A., & Guo, J. (2020). Classroom climate and children’s academic and psychological wellbeing: A systematic review and meta-analysis. Developmental Review, 57, 100912. https://doi.org/10.1016/j.dr.2020.100912 [less ▲]

Lehrer-Schüler-Beziehungen und ihre Korrelate: Ein systematisches Review von Meta-Analysen

Scientific Conference (2023, March 01)

THEORETISCHER HINTERGRUND Gute Beziehungen zur eigenen Lehrerin können sich positiv auf den Erfolg eines Schülers auswirken. Dieser Effekt kann mit Bowlby’s (1982) Bindungstheorie erklärt werden und wird ... [more ▼]

THEORETISCHER HINTERGRUND Gute Beziehungen zur eigenen Lehrerin können sich positiv auf den Erfolg eines Schülers auswirken. Dieser Effekt kann mit Bowlby’s (1982) Bindungstheorie erklärt werden und wird empirisch immer wieder gestützt (z.B. Hamre & Pianta, 2001). Positive Lehrer-Schüler-Beziehungen zeichnen sich durch emotionale Wärme und Nähe aus; negative Aspekte durch Konflikt und Abhängigkeit. So stehen positive Lehrer-Schüler-Beziehungen nicht nur mit akademischen Leistungen in Verbindung, sondern auch mit einer Vielzahl anderer, wünschenswerter Schülerentwicklungen. Zahlreiche Meta-Analysen deuten auf signifikante Zusammenhänge zwischen Lehrer-Schüler-Beziehungen und schulischem Engagement, guten Beziehungen zu Gleichaltrigen, exekutiven Funktionen, allgemeinem Wohlbefinden und der Verringerung aggressiver oder störender Verhaltensweisen hin (Endedijk et al., 2021; Nurmi, 2012; Roorda et al., 2017; Vandenbroucke et al., 2018). Diese Befunde sind jedoch weit verstreut in der Literatur, sodass Forschungslücken unentdeckt bleiben. Auch unterscheiden sich bisherige Überblicksarbeiten in ihren Methoden und den gefundenen Zusammenhängen zwischen Lehrer-Schüler-Beziehungen und Ergebnisvariablen von Schüler*innen. Darüber hinaus ist die Literatur uneindeutig, welche Moderatoren (z.B. Alter oder Geschlecht) diese Beziehungen beeinflussen. Gleichzeitig variiert die Qualität der Meta-Analysen in diesem Feld merklich, was die Interpretation ihrer Ergebnisse erschweren kann. FRAGESTELLUNG Angesichts dieser Forschungslücken haben wir die meta-analytische Literatur systematisch durchsucht und zusammengefasst (Cooper & Koenka, 2012), um einen Überblick über Korrelate von Lehrer-Schüler-Beziehungen zu schaffen. Hierbei untersuchten wir drei Forschungsfragen 1. Inwieweit hängen akademische, verhaltensbezogene, sozio-emotionale, motivationale und kognitive Schülereigenschaften mit Lehrer-Schüler-Beziehungen in der meta-analytischen Literatur zusammen? 2. Welche Moderatoren beeinflussen diese Zusammenhänge? 3. Welche methodische Qualität haben die einbezogenen Meta-Analysen? METHODE Um diese Forschungsfragen zu beantworten, analysierten wir 24 Meta-Analysen, die rund 130 Effektstärken für über eine Million Schüler*innen umfassten. Nach der Präregistrierung erfolgte eine systematische Literatursuche. Während mehrerer Runden der Überprüfung mithilfe unserer Ein- und Ausschlusskriterien identifizierten wir 24 passende Meta-Analysen. Aus diesen Meta-Analysen extrahierten wir die Effektstärken zum Zusammenhang von Lehrer-Schüler-Beziehungen und akademische, verhaltensbezogene, sozio-emotionale, motivationale und allgemeine kognitive Schülereigenschaften. Für die Forschungsfragen 1 und 2 haben wir die Ergebnisse zusammengefasst und einen narrativen Überblick erarbeitet. Für Forschungsfrage 3 bewerteten wir die Qualität der Meta-Analysen mit Hilfe der AMSTAR-2 Skala (angepasst an korrelative Studien in der Psychologie und Bildungsforschung; Shea et al., 2017). ERGEBNISSE UND IHRE BEDEUTUNG Mit Blick auf die Lehrer-Schüler-Beziehungen werden unterschiedliche Ergebnisvariablen analysiert (Forschungsfrage 1). Die stärksten Zusammenhänge zeigten sich für Konflikt und Abhängigkeit in der Lehrer-Schüler-Beziehung mit Verhaltensproblemen der Schüler*innen (r = .35 bis .57; Nurmi, 2012). Positive Lehrer-Schüler-Beziehungen zeigte die stärkste Verbindung mit der Beteiligung in der Schule (r = .26 bis .34; Roorda et al., 2011), prosozialem, externalisierendem und internalisierendem Verhalten (r = .25; Endedijk et al., 2021) sowie mit Lernmotivation in Kombination mit Beteiligung der Schüler*innen (r = .23; Wang et al., 2020). Alter oder Klassenstufe waren die am häufigsten untersuchten Moderatoren mit teilweise gegenläufigen Befunden (Forschungsfrage 2). Geschlechterunterschiede wurden dagegen seltener festgestellt. Gleichzeitig wurde der Effekt der Informationsquelle häufig untersucht, d.h., ob und auf welche Weise Lehrkräfte, Gleichaltrige oder die Schüler*innen selbst die Lehrer-Schüler-Beziehung bewerteten. Für Forschunsgfrage 3 diskutieren wir die Qualitätsunterschiede der Meta-Analysen. Mit dem systematischen Review von Meta-Analysen fassen wir die Forschungslandschaft zu Korrelaten von Lehrer-Schüler-Beziehungen zusammen und zeigen, in welchem Zusammenhang diese mit Lehrer-Schüler-Beziehungen stehen. Unseren Ergebnissen folgend sollten Lehrkräfte für die Wirkung von Lehrer-Schüler-Beziehungen und deren Zusammenhängen sensibilisiert werden. Einige Interventionen zur Verbesserung von dieser wichtigen Beziehungen wurden bereits meta-analytisch mit vielversprechende Ergebnissen untersucht (Kincade et al., 2020). Ein nächster Schritt ist nun die experimentelle Überprüfung der gefundenen Korrelate, um positive Lehrer-Schüler-Beziehungen als wirksame Strategie zur Verbesserung von akademischen, verhaltensbezogenen, sozio-emotionalen, motivationalen und kognitiven Schülereigenschaften kausal zu bestätigen. LITERATUR Bowlby, J. (1982). Attachment and loss: Vol. 1. Attachment. (2nd ed., Vol. 1). Basic Books. Cooper, H., & Koenka, A. C. (2012). The overview of reviews: Unique challenges and opportunities when research syntheses are the principal elements of new integrative scholarship. American Psychologist, 67(6), 446–462. https://doi.org/10.1037/a0027119 Decristan, J., Kunter, M., & Fauth, B. (2022). Die Bedeutung individueller Merkmale und konstruktiver Unterstützung der Lehrkraft für die soziale Integration von Schülerinnen und Schülern im Mathematikunterricht der Sekundarstufe. Zeitschrift für Pädagogische Psychologie, 36(1–2), 85–100. https://doi.org/10.1024/1010-0652/a000329 Endedijk, H. M., Breeman, L. D., van Lissa, C. J., Hendrickx, M. M. H. G., den Boer, L., & Mainhard, T. (2021). The Teacher’s Invisible Hand: A Meta-Analysis of the Relevance of Teacher–Student Relationship Quality for Peer Relationships and the Contribution of Student Behavior. Review of Educational Research, 003465432110514. https://doi.org/10.3102/00346543211051428 Givens Rolland, R. (2012). Synthesizing the Evidence on Classroom Goal Structures in Middle and Secondary Schools: A Meta-Analysis and Narrative Review. Review of Educational Research, 82(4), 396–435. https://doi.org/10.3102/0034654312464909 Hamre, B. K., & Pianta, R. C. (2001). Early Teacher-Child Relationships and the Trajectory of Children’s School Outcomes through Eighth Grade. Child Development, 72(2), 625–638. https://doi.org/10.1111/1467-8624.00301 Kincade, L., Cook, C., & Goerdt, A. (2020). Meta-Analysis and Common Practice Elements of Universal Approaches to Improving Student-Teacher Relationships. Review of Educational Research, 90(5), 710–748. https://doi.org/10.3102/0034654320946836 Korpershoek, H., Harms, T., de Boer, H., van Kuijk, M., & Doolaard, S. (2016). A Meta-Analysis of the Effects of Classroom Management Strategies and Classroom Management Programs on Students’ Academic, Behavioral, Emotional, and Motivational Outcomes. Review of Educational Research, 86(3), 643–680. https://doi.org/10.3102/0034654315626799 Lei, H., Cui, Y., & Chiu, M. M. (2016). Affective Teacher—Student Relationships and Students’ Externalizing Behavior Problems: A Meta-Analysis. Frontiers in Psychology, 7. https://doi.org/10.3389/fpsyg.2016.01311 Nurmi, J.-E. (2012). Students’ characteristics and teacher–child relationships in instruction: A meta-analysis. Educational Research Review, 7(3), 177–197. https://doi.org/10.1016/j.edurev.2012.03.001 Roorda, D. L., Jak, S., Zee, M., Oort, F. J., & Koomen, H. M. Y. (2017). Affective Teacher–Student Relationships and Students’ Engagement and Achievement: A Meta-Analytic Update and Test of the Mediating Role of Engagement. School Psychology Review, 46(3), 239–261. https://doi.org/10.17105/SPR-2017-0035.V46-3 Roorda, D. L., Koomen, H. M. Y., Spilt, J. L., & Oort, F. J. (2011). The Influence of Affective Teacher–Student Relationships on Students’ School Engagement and Achievement: A Meta-Analytic Approach. Review of Educational Research, 81(4), 493–529. https://doi.org/10.3102/0034654311421793 Shea, B. J., Reeves, B. C., Wells, G., Thuku, M., Hamel, C., Moran, J., Moher, D., Tugwell, P., Welch, V., Kristjansson, E., & Henry, D. A. (2017). AMSTAR 2: A critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ, j4008. https://doi.org/10.1136/bmj.j4008 Vandenbroucke, L., Spilt, J., Verschueren, K., Piccinin, C., & Baeyens, D. (2018). The Classroom as a Developmental Context for Cognitive Development: A Meta-Analysis on the Importance of Teacher–Student Interactions for Children’s Executive Functions. Review of Educational Research, 88(1), 125–164. https://doi.org/10.3102/0034654317743200 Wang, M.-T., L. Degol, J., Amemiya, J., Parr, A., & Guo, J. (2020). Classroom climate and children’s academic and psychological wellbeing: A systematic review and meta-analysis. Developmental Review, 57, 100912. https://doi.org/10.1016/j.dr.2020.100912 [less ▲]

Teacher-Student-Relationships and Student Outcomes in Heterogeneous Educational Settings: A Systematic Review of Meta-Analyses

Scientific Conference (2022, November 09)

Especially in diverse educational settings, positive relationships between students and their teachers can foster students’ learning and help alleviate systematic inequalities. Characterized by emotional ... [more ▼]

Especially in diverse educational settings, positive relationships between students and their teachers can foster students’ learning and help alleviate systematic inequalities. Characterized by emotional warmth or closeness, positive teacher-student relationships (TSR) can improve several student outcomes. For instance, existing meta-analyses suggest significant links between TSR and students’ peer relations, school engagement, academic achievement, emotions, executive functions, general well-being, and reductions in aggressive or disruptive behaviors. However, the evidence on these links is scattered, and a comprehensive overview of the associations with TSR integrating academic, behavioral, socio-emotional, motivational, and general cognitive outcomes is lacking. Furthermore, researchers have been unequivocal about possible moderators, such as how these relationships vary with student age or gender. In light of these research gaps, we systematically reviewed the meta-analytic literature and examined (a) the extent to which academic, behavioral, socio-emotional, motivational, and general cognitive student outcomes are related to TSR in the meta-analytic literature; (b) which moderators influence this association; and (c) the methodological quality of the included meta-analyses. We included meta-analyses with preschool or K-12 samples in our dataset which reported some measure of the relation between TSR and student outcomes. With this dataset, we systematically mapped the evidence on (a) the TSR-outcome relationship; (b) the moderators; and (c) the methodological quality of the meta-analyses. We will present our core findings and discuss future research with this second-order, meta-analytic dataset and the impact of positive TSR in diverse and heterogeneous settings. [less ▲]

The Associations Between Teacher-Student-Relationships and Student Outcomes: A Systematic Review of Meta-Analyses (ReMA-TSR)

Report (2022)

The relationships between students and their teachers can impact students’ learning and development. Characterized by emotional warmth or closeness, positive teacher-student-relationships (TSR) can ... [more ▼]

The relationships between students and their teachers can impact students’ learning and development. Characterized by emotional warmth or closeness, positive teacher-student-relationships (TSR) can improve a variety of student outcomes. Existing meta-analyses suggest strong links between TSR and students’ peer relations, school engagement, academic achievement, emotions, executive functions, general well-being, and reductions in aggressive or disruptive behaviors. However, this evidence base is scattered, and a comprehensive overview of the TSR-outcome associations integrating academic, behavioral, socio-emotional, and general cognitive outcomes is lacking. Further, researchers have been unequivocal about possible moderators, such as how these relationships change with student age as their relationship to family, peers, and teachers change. Considering these research gaps, we aim to systematically review the meta-analytic literature and examine the following two research questions: Research Question 1: To what extent do existing meta-analyses provide evidence supporting significant relations between TSR and children’s academic, behavioral, socioemotional, motivational, and general cognitive outcomes? (Overall relationship) Research Question 2: To what extent do these relationships vary by the characteristics of the meta-analyses, such as student samples, measurement characteristics, and the quality of the meta-analyses? To address these research questions, we conduct a systematic review of existing meta-analyses, integrating the findings of eligible studies. We will include quantitative meta-analyses with preschool or K-12 samples who have no diagnosed disorder or disability. [less ▲]

Uncovering everyday dynamics in students’ perceptions of instructional quality with experience sampling

in Learning and Instruction (2022), 81

Why we need systematic reviews and meta-analyses in the testing and assessment literature

in European Journal of Psychological Assessment (2022)

Meta-Analytic Structural Equation Models of Executive Functions and Math Intelligence in Preschool Children

Scientific Conference (2021, September)

BACKGROUND: Response inhibition, attention shifting, and working memory updating are the three core executive functions (EFs; Miyake et al., 2000) underlying other cognitive skills that are relevant for ... [more ▼]

BACKGROUND: Response inhibition, attention shifting, and working memory updating are the three core executive functions (EFs; Miyake et al., 2000) underlying other cognitive skills that are relevant for learning and everyday life. For example, they have shown to be differentially related to the mathematical component of intelligence (i.e., math intelligence) in school students and adults. While researchers suppose these three EFs to become more differentiated from early childhood to adulthood, neither the link of these constructs nor their structure has been conclusively established in preschool children yet. Primary studies on path models connecting EFs and math intelligence diverge in the exact relation of EFs and math intelligence. It remains unclear whether inhibition, shifting, and updating exhibit distinct but correlated constructs with respect to their relation to math intelligence. OBJECTIVES: With our meta-analysis, we aimed to (a) synthesize the relation between the three EFs and math intelligence in preschool children; and (b) compare plausible models of the effects of EFs on math intelligence. METHODS/RESULTS: Synthesizing data from 47 studies (363 effect sizes, 30,481 participants) from the last two decades via novel multilevel and multivariate meta-analytic models (Pustejovsky & Tipton, 2020), we found the three core EFs to be significantly related to math intelligence: Inhibition ("r" ̅ = .30, 95 % CI [.25, .35]), shifting ("r" ̅ = .32, 95 % CI [.25, .38]), and updating ("r" ̅ = .36, 95 % CI [.31, .40]). Looking at the three core EFs as one construct, the correlation was "r" ̅ = .34, 95 % CI [.31, .37]. Utilizing correlation-based, meta-analytic structural equation modeling (Jak & Cheung, 2020), our results exhibited significant relations of all EFs to math intelligence. These relations did not differ between the three core EFs. DISCUSSION: Our findings corroborate the positive link between EFs and math intelligence in preschool children and are similar to other age groups. From the model testing, we learned that representing EFs by a latent variable, thus capturing the covariance among the three core EFs, explained substantially more variation in math intelligence than representing them as distinct constructs. [less ▲]

Measuring Executive Functions and their Relation to Math Intelligence in Preschool Children: A Meta-Analysis

Scientific Conference (2021, July)

Introduction: Executive functions (inhibition, attention shifting, updating) are linked to math intelligence in school students and adults. This link is particularly important because performance in ... [more ▼]

Introduction: Executive functions (inhibition, attention shifting, updating) are linked to math intelligence in school students and adults. This link is particularly important because performance in school mathematics is predictive of various competencies later in life. While some researchers argue that tests of executive functions and math intelligence measure the same underlying construct, others argue that they measure distinct but correlated constructs. Also, evidence on the differentiation of cognitive skills over time exists. Clarifying the relation between executive functions and math intelligence is, however, challenging, especially because preschoolers cannot fill in commonly used questionnaires that require them to read. As a consequence, researchers have to resort to behavioral, verbal, apparatus-, or computer-based assessments of executive functions. Objectives/Methodology: With this meta-analysis of 29 studies containing 268 effect sizes, we examined the link between executive functions and math intelligence for a total sample of 25,510 preschool children. Specifically, we synthesized the corresponding correlations and sought to clarify which executive function assessments were used for preschool children and how the assessment characteristics may moderate the correlation between executive functions and mathematical skills. Results: Utilizing three-level random-effects meta-analysis, we found a moderate correlation between executive functions and mathematical skills in preschool children, r = 0.35. The type of assessment (behavioral, verbal, apparatus-, or computer-based assessments) did not moderate this relation. Differentiating between the three executive functions revealed average correlations of r = 0.30 between math and inhibition, r = 0.38 between math and attention shifting, and r = 0.36 between math and updating. These analyses will be supplemented by further moderator analyses. Conclusions: Our findings support the significant link between executive functions and mathematical skills in preschoolers—yet, the average correlations do not suggest that both measures are identical. Results will be discussed against the background of deployed assessments and testing environments. [less ▲]

Students’ lesson-to-lesson perceptions of the three basic dimensions of instructional quality

Scientific Conference (2021)

Measuring Executive Functions and their Relations to Mathematical Skills in Preschool Children: A Meta-Analysis

Scientific Conference (2020, July)

Introduction: Executive functions (inhibition, attention shifting, working memory) are linked to mathematical skills in school students and adults. This link is particularly important because performance ... [more ▼]

Introduction: Executive functions (inhibition, attention shifting, working memory) are linked to mathematical skills in school students and adults. This link is particularly important because performance in school mathematics is predictive of various competencies later in life. While some researchers argue that tests of executive functions and mathematical skills measure the same underlying construct, others argue that they measure distinct but correlated constructs. Also, evidence on the differentiation of cognitive skills over time exists. Clarifying the relation between executive functions and mathematical skills is, however, challenging, especially because preschoolers cannot fill in commonly used questionnaires that require them to read. As a consequence, researchers have to resort to behavioral, verbal, apparatus-, or computer-based assessments of executive functions. Objectives/Methodology: With this meta-analysis of 26 studies containing 238 effect sizes, we examined the link between executive functions and early mathematical skills for a total sample of 24,256 preschool children. Specifically, we synthesized the corresponding correlations and sought to clarify which executive function assessments were used for preschool children and how the assessment characteristics may moderate the correlation between executive functions and mathematical skills. Results: Utilizing three-level random-effects meta-analysis, we found a moderate correlation between executive functions and mathematical skills in preschool children, r = 0.35. The type of assessment (behavioral, verbal, apparatus-, or computer-based assessments) did not moderate this relation. Differentiating between the three executive functions revealed average correlations of r = 0.31 between math and inhibition, r = 0.38 between math and attention shifting, and r = 0.36 between math and updating. These analyses will be supplemented by further moderator analyses. Conclusions: Our findings support the significant link between executive functions and mathematical skills in preschoolers—yet, the average correlations do not suggest that both measures are identical. Results will be discussed against the background of deployed assessments and testing environments. [less ▲]