Pub Date : 2026-01-28DOI: 10.1007/s10648-025-10106-3
Gabriel Velez, Larry Zhiming Xu, Jacklynn Fitzgerald
{"title":"From AI as a Relational Breaker to a Relational Broker: Comment on Bauer et al. (2025)","authors":"Gabriel Velez, Larry Zhiming Xu, Jacklynn Fitzgerald","doi":"10.1007/s10648-025-10106-3","DOIUrl":"https://doi.org/10.1007/s10648-025-10106-3","url":null,"abstract":"","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":"43 1","pages":""},"PeriodicalIF":10.1,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-27DOI: 10.1007/s10648-025-10098-0
Zhuotao Lu, Hao Lei, Ming Ming Chiu, Weijie Mao, Shuai Wang
{"title":"Meta-analyses of Peer Assessment and Affective Outcomes: Motivation, Self-efficacy, and Anxiety","authors":"Zhuotao Lu, Hao Lei, Ming Ming Chiu, Weijie Mao, Shuai Wang","doi":"10.1007/s10648-025-10098-0","DOIUrl":"https://doi.org/10.1007/s10648-025-10098-0","url":null,"abstract":"","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":"8 1","pages":""},"PeriodicalIF":10.1,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146056091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-26DOI: 10.1007/s10648-025-10103-6
Michael W. Asher, Paulo F. Carvalho
{"title":"Conditions for Effective Learning Without Upfront Instruction: How Practice with Feedback Supports Memory, Generalization, Motivation, and Metacognition","authors":"Michael W. Asher, Paulo F. Carvalho","doi":"10.1007/s10648-025-10103-6","DOIUrl":"https://doi.org/10.1007/s10648-025-10103-6","url":null,"abstract":"","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":"29 1","pages":""},"PeriodicalIF":10.1,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146048512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1007/s10648-026-10119-6
Tina Seufert
Research on self-regulated learning (SRL) is undergoing a methodological and conceptual transformation from static, retrospective measures toward dynamic, multimodal, and temporally sensitive analyses. This discussion paper synthesizes and extends the contributions of a Topical Collection devoted to multimodal approaches in SRL research. It examines how diverse studies conceptualize and operationalize SRL as a complex interplay of cognitive, metacognitive, affective, and motivational (CAMM) processes. The Self-regulated learning, Multimodal data, and Analysis Grid (SMA Grid) serves as a shared framework for classifying and integrating different modalities and analytical designs. Across the reviewed contributions, a general shift from unimodal toward integrated multimodal approaches is evident, though motivational and affective dimensions remain underrepresented. The paper argues for expanding existing frameworks—particularly SMA and CAMM—toward explanatory models that account for social, contextual, and resource-based factors shaping regulatory processes. It also highlights persistent challenges in aligning data richness with theoretical depth, especially regarding temporal modeling and causal inference. A central concern is the translation of multimodal diagnostics into actionable pedagogical support, an area still underdeveloped despite the rise of AI-based analytics. Building on concepts such as cognitive load theory and resource-based perspectives, the paper proposes that SRL should be understood as a function of the dynamic balance between learners’ resources, task demands, and instructional context. Ultimately, it calls for a more integrated, theory-driven, and practice-oriented research agenda that connects analysis with support, and measurement with meaningful educational intervention.
{"title":"Transforming Self-regulated Learning – Multimodal Insights and Future Directions","authors":"Tina Seufert","doi":"10.1007/s10648-026-10119-6","DOIUrl":"https://doi.org/10.1007/s10648-026-10119-6","url":null,"abstract":"Research on self-regulated learning (SRL) is undergoing a methodological and conceptual transformation from static, retrospective measures toward dynamic, multimodal, and temporally sensitive analyses. This discussion paper synthesizes and extends the contributions of a Topical Collection devoted to multimodal approaches in SRL research. It examines how diverse studies conceptualize and operationalize SRL as a complex interplay of cognitive, metacognitive, affective, and motivational (CAMM) processes. The Self-regulated learning, Multimodal data, and Analysis Grid (SMA Grid) serves as a shared framework for classifying and integrating different modalities and analytical designs. Across the reviewed contributions, a general shift from unimodal toward integrated multimodal approaches is evident, though motivational and affective dimensions remain underrepresented. The paper argues for expanding existing frameworks—particularly SMA and CAMM—toward explanatory models that account for social, contextual, and resource-based factors shaping regulatory processes. It also highlights persistent challenges in aligning data richness with theoretical depth, especially regarding temporal modeling and causal inference. A central concern is the translation of multimodal diagnostics into actionable pedagogical support, an area still underdeveloped despite the rise of AI-based analytics. Building on concepts such as cognitive load theory and resource-based perspectives, the paper proposes that SRL should be understood as a function of the dynamic balance between learners’ resources, task demands, and instructional context. Ultimately, it calls for a more integrated, theory-driven, and practice-oriented research agenda that connects analysis with support, and measurement with meaningful educational intervention.","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":"44 1","pages":""},"PeriodicalIF":10.1,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146048514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1007/s10648-025-10093-5
Allison Master, Khushboo S. Patel, Katherine Weltzien, Shaila Sharmin
{"title":"“I Felt Like I Completely Belonged in That Class”: Gender and the Development of Sense of Belonging in K-12 STEM Education","authors":"Allison Master, Khushboo S. Patel, Katherine Weltzien, Shaila Sharmin","doi":"10.1007/s10648-025-10093-5","DOIUrl":"https://doi.org/10.1007/s10648-025-10093-5","url":null,"abstract":"","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":"7 1","pages":""},"PeriodicalIF":10.1,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146048515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-19DOI: 10.1007/s10648-025-10100-9
Zohreh Fathi, Pedram Zarei, Carlton J. Fong, Arnob K. Saha, Sanzida Sharmeen
Faculty-student relationships (FSRs) are broadly recognized as meaningful predictors of students’ success in higher education as evidenced by various theoretical models. Strong FSRs meet basic psychological needs (autonomy, competence, relatedness), provide emotional support, support identity development, and help students engage with their campus community. Although prior syntheses have focused on teacher-student relationships in K–12 (primary and secondary) settings, less is known about the importance of FSRs in higher education. This meta-analysis integrated 128 effect sizes drawn from 36 studies to explore the associations between FSRs and several measures of academic outcomes: students’ achievement (grade point average [GPA] and grades) and persistence. Results showed a significant overall positive correlation between FSRs and students’ academic outcomes ( r = .18), with the strongest correlation for persistence ( r = .33). Moreover, effects based on FSR measures including a dimension of care had higher correlations with students’ GPA. These results highlight the important role of supportive and responsive FSRs in fostering achievement and persistence. We discuss implications for educational practice (such as professional development for faculty members) and future research (such as a more expansive set of outcomes or mediators).
{"title":"The Caring Professor: A Meta-Analysis of Associations between Faculty-Student Relationships and Postsecondary Student Success","authors":"Zohreh Fathi, Pedram Zarei, Carlton J. Fong, Arnob K. Saha, Sanzida Sharmeen","doi":"10.1007/s10648-025-10100-9","DOIUrl":"https://doi.org/10.1007/s10648-025-10100-9","url":null,"abstract":"Faculty-student relationships (FSRs) are broadly recognized as meaningful predictors of students’ success in higher education as evidenced by various theoretical models. Strong FSRs meet basic psychological needs (autonomy, competence, relatedness), provide emotional support, support identity development, and help students engage with their campus community. Although prior syntheses have focused on teacher-student relationships in K–12 (primary and secondary) settings, less is known about the importance of FSRs in higher education. This meta-analysis integrated 128 effect sizes drawn from 36 studies to explore the associations between FSRs and several measures of academic outcomes: students’ achievement (grade point average [GPA] and grades) and persistence. Results showed a significant overall positive correlation between FSRs and students’ academic outcomes ( <jats:italic>r</jats:italic> = .18), with the strongest correlation for persistence ( <jats:italic>r</jats:italic> = .33). Moreover, effects based on FSR measures including a dimension of care had higher correlations with students’ GPA. These results highlight the important role of supportive and responsive FSRs in fostering achievement and persistence. We discuss implications for educational practice (such as professional development for faculty members) and future research (such as a more expansive set of outcomes or mediators).","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":"30 1","pages":""},"PeriodicalIF":10.1,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146005579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-16DOI: 10.1007/s10648-025-10105-4
Katrin Schuessler, Jenna Koenen, Elke Sumfleth, Marvin Rost
Systematic analyses of repeated measures of cognitive load during realistic, complex learning tasks are still lacking. Previous findings are based on simulations and the use of a set of multiple short problem-solving tasks. For the present study, lower secondary level pupils ( N = 360) worked on three worked examples on the topic of acids in their chemistry lessons. Cognitive load (invested mental effort and perceived task difficulty), interest, and self-assessed understanding were measured at seven points during the completion of each example. The study examines differences between repeated measures of cognitive load and interest and the relationship between the variables. The results show that the values of the repeated measures differ significantly and are poorly represented by the mean value across the measurement points. In addition, the pairwise relationship between the variables (invested effort, perceived task difficulty, interest, and self-assessed understanding) is not constant at different measurement points. Further analyses also show that different intervention conditions during the learning phase and prior knowledge are additional influencing factors.
{"title":"Variations in Repeated Measures of Cognitive Load and Interest During Complex Learning Tasks","authors":"Katrin Schuessler, Jenna Koenen, Elke Sumfleth, Marvin Rost","doi":"10.1007/s10648-025-10105-4","DOIUrl":"https://doi.org/10.1007/s10648-025-10105-4","url":null,"abstract":"Systematic analyses of repeated measures of cognitive load during realistic, complex learning tasks are still lacking. Previous findings are based on simulations and the use of a set of multiple short problem-solving tasks. For the present study, lower secondary level pupils ( <jats:italic>N</jats:italic> = 360) worked on three worked examples on the topic of acids in their chemistry lessons. Cognitive load (invested mental effort and perceived task difficulty), interest, and self-assessed understanding were measured at seven points during the completion of each example. The study examines differences between repeated measures of cognitive load and interest and the relationship between the variables. The results show that the values of the repeated measures differ significantly and are poorly represented by the mean value across the measurement points. In addition, the pairwise relationship between the variables (invested effort, perceived task difficulty, interest, and self-assessed understanding) is not constant at different measurement points. Further analyses also show that different intervention conditions during the learning phase and prior knowledge are additional influencing factors.","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":"99 1","pages":""},"PeriodicalIF":10.1,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146005580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This special issue examines advances in the measurement and support of self-regulated learning (SRL), emphasizing the integration of multimodal data and artificial intelligence (AI) in educational contexts. SRL is a goal-directed process in which learners plan, monitor, and control their learning, influenced by the interplay of cognition, affect, metacognition, and motivation (CAMM). Traditional methods in educational psychology, such as self-reports and interviews, often fall short of capturing the dynamic and recursive nature of SRL. Recent research employs multimodal data and process-oriented approaches to better understand the complex interactions among CAMM processes. The self-regulated learning, multimodal data, and analysis grid (SMA) is used as a framework for mapping and analyzing these processes across diverse data streams. The special issue includes three review papers and two empirical studies that illustrate the benefits and challenges of integrating multiple data sources and analytical techniques, while emphasizing the need for reliable and valid measures to enable personalized support for SRL. Collectively, the studies provide a multidisciplinary perspective on the current state and future directions of SRL research, advocating for innovative, theory-driven approaches that leverage existing technological capabilities to empower agentic learners in digital environments.
{"title":"Self-Regulated Learning, Multimodal Data, and Analysis Grid: Where Are We Now and Where Are We Going?","authors":"Joni Lämsä, Susanne de Mooij, Martine Baars, Inge Molenaar, Sanna Järvelä","doi":"10.1007/s10648-025-10113-4","DOIUrl":"https://doi.org/10.1007/s10648-025-10113-4","url":null,"abstract":"This special issue examines advances in the measurement and support of self-regulated learning (SRL), emphasizing the integration of multimodal data and artificial intelligence (AI) in educational contexts. SRL is a goal-directed process in which learners plan, monitor, and control their learning, influenced by the interplay of cognition, affect, metacognition, and motivation (CAMM). Traditional methods in educational psychology, such as self-reports and interviews, often fall short of capturing the dynamic and recursive nature of SRL. Recent research employs multimodal data and process-oriented approaches to better understand the complex interactions among CAMM processes. The self-regulated learning, multimodal data, and analysis grid (SMA) is used as a framework for mapping and analyzing these processes across diverse data streams. The special issue includes three review papers and two empirical studies that illustrate the benefits and challenges of integrating multiple data sources and analytical techniques, while emphasizing the need for reliable and valid measures to enable personalized support for SRL. Collectively, the studies provide a multidisciplinary perspective on the current state and future directions of SRL research, advocating for innovative, theory-driven approaches that leverage existing technological capabilities to empower agentic learners in digital environments.","PeriodicalId":48344,"journal":{"name":"Educational Psychology Review","volume":"214 1","pages":""},"PeriodicalIF":10.1,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145961809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：