Journal of Educational Psychology, Vol 117(2), Feb 2025, 153-175; doi:10.1037/edu0000916

This study examined the impact of a widely used content-rich literacy curriculum on kindergarteners’ vocabulary, listening comprehension, and content knowledge. In combined findings from two randomized controlled trials (RCTs), the second being a replication of the first, 47 schools in large urban U.S. districts were randomly assigned to implement Core Knowledge Language Arts: Knowledge Strand (CKLA: Knowledge) or to a waitlist control condition. CKLA: Knowledge focuses instruction on language comprehension through interactive read alouds that systematically build content knowledge. Teachers received two days of professional development workshops, along with light-touch support from facilitators during implementation. Participants included 1,194 kindergarten students, who were administered individual pre- and posttest measures of proximal and standardized vocabulary, listening comprehension, and content knowledge (i.e., science, social studies). After approximately one semester of curricular implementation, CKLA: Knowledge demonstrated positive and significant impacts on proximal vocabulary and science and social studies knowledge. Significant interactions were found for vocabulary and content knowledge, such that children who began the year with relatively higher receptive vocabulary scores derived a greater benefit of learning the words and content knowledge taught in the curriculum. The present work is unique in that it tested the effects of a content-rich literacy curriculum that integrated literacy and content-area instruction and replicated the effects across two RCTs. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(2), Feb 2025, 176-205; doi:10.1037/edu0000890

Undergraduates enrolled in large, active learning courses must self-regulate their learning (self-regulated learning [SRL]) by appraising tasks, making plans, setting goals, and enacting and monitoring strategies. SRL researchers have relied on self-report and learner-mediated methods during academic tasks studied in laboratories and now collect digital event data when learners engage with technology-based tools in classrooms. Inferring SRL processes from digital events and testing their validity is challenging. We aligned digital and verbal SRL event data to validate digital events as traces of SRL and used them to predict achievement in lab and course settings. In Study 1, we sampled a learning task from a biology course into a laboratory setting. Enrolled students (N = 48) completed the lesson using digital resources (e.g., online textbook, course site) while thinking aloud weeks before it was taught in class. Analyses confirmed that 10 digital events reliably co-occurred ≥ 70% of the time with verbalized task definition and strategy use macroprocesses. Some digital events co-occurred with multiple verbalized SRL macroprocesses. Variance in occurrence of validated digital events was limited in lab sessions, and they explained statistically nonsignificant variance in learners’ performance on lesson quizzes. In Study 2, lesson-specific digital event data from learners (N = 307) enrolled in the course (but not in Study 1) predicted performance on lesson-specific exam items, final exams, and course grades. Validated digital events also predicted final exam and course grades in the next semester (N = 432). Digital events can be validated to reflect SRL processes and scaled to explain achievement in naturalistic undergraduate education settings. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(2), Feb 2025, 206-227; doi:10.1037/edu0000909

Interleaving (intermixing exemplars from different categories) is more effective in promoting inductive learning than blocking (massing exemplars from a given category together). Yet learners typically prefer blocking over interleaving during self-regulated inductive learning, highlighting the need to develop effective interventions to overcome this metacognitive illusion and promote learners’ practical use of the interleaving strategy. Drawing on a sample of university students, three experiments examined the effects of an instructional intervention on (a) correction of metacognitive fallacies regarding the superiority of blocking over interleaving for inductive learning, (b) adoption of the interleaving strategy during self-regulated learning when learners are allowed to make study choices exemplar-by-exemplar, (c) classification performance, and (d) transfer of category learning across diverse domains. Experiments 1 and 2 showed that instructions about the benefits of interleaving over blocking improved metacognitive awareness of the efficacy of interleaving and enhanced self-usage of the interleaving strategy during learning of new categories. However, this intervention had negligible influence on interleaving distance and did not improve classification performance. Experiment 3 found that informing learners about the benefits of extensive interleaving, as compared to minimal interleaving or no interleaving, successfully increased interleaving distance and boosted classification performance, and the intervention effects transferred to learning categories in a different domain. These findings support the practical use of the instructional intervention in promoting self-usage of the interleaving strategy and highlight the important role of enlarging interleaving distance in facilitating inductive learning. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(2), Feb 2025, 228-245; doi:10.1037/edu0000914

Emerging evidence has demonstrated the close association between relational reasoning (RR) and mathematical performance. While mathematics is a discipline with multiple representations, prior investigations on the RR–mathematics relation mainly relied on nonverbal tests of RR. The role of RR in linguistic contexts to mathematics achievement was rarely explored. With a newly developed verbal test of RR for children, the present study attempted to examine the contribution of nonverbal and verbal RR to mathematics achievement. Sixth graders in Hong Kong (n = 235) were assessed on their nonverbal and verbal RR, numerical operations, and mathematical problem solving. The novel verbal test of RR showed satisfactory psychometric properties. A structural equation model was subsequently estimated. With the effect of cognitive abilities and literacy skills (working memory, spatial skills, and reading comprehension) accounted for, results indicated that while nonverbal RR was significantly associated with both mathematics achievement outcomes, verbal RR significantly predicted numerical operations but not mathematical problem solving. The above findings provided preliminary evidence of the contribution of verbal RR to mathematics achievement. Implications and future directions will be discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(2), Feb 2025, 246-256; doi:10.1037/edu0000912

The knowledge of various types of numbers, such as integers and fractions, has been shown to be crucial for students’ success in mathematics. However, the significance of negative number knowledge has not been explored enough. This study aims to investigate the role of negative number knowledge in mathematics achievement. A group of seventh graders (n = 192) in Hong Kong were assessed on their understanding of positive and negative integers, mathematics achievement, fluid intelligence, working memory, and inhibition. Using hierarchical linear models, the study found that negative number understanding significantly predicted mathematics achievement, even after controlling for school, general cognitive skills, and positive number understanding. The findings confirm the importance of negative number understanding in early adolescents’ mathematics learning. Educators should pay more attention to this aspect of numerical magnitude. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(2), Feb 2025, 257-272; doi:10.1037/edu0000919

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. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(2), Feb 2025, 273-291; doi:10.1037/edu0000894

Recent research has increasingly discussed the importance of temporal comparisons (comparisons with previous achievements) for the formation of students’ academic self-concepts, in addition to social comparisons (comparisons with others’ achievements) and dimensional comparisons (comparisons with achievements in other subjects). However, empirical findings on temporal comparison effects are inconsistent. In this paper, we contribute to this debate by arguing that temporal comparison effects were overestimated in previous studies testing the 2I/E model—a model that has often been used to investigate the joint effects of social, dimensional, and temporal comparisons in recent years—due to an inappropriate specification of social and dimensional comparison effects. Moreover, we examine the potential impact of comparison periods on the strength of temporal comparison effects. Specifically, we developed an extension of the 2I/E model in which we calculated students’ achievement levels (used to specify social and dimensional comparison effects) by weighting rather than averaging students’ grades from earlier school years. Subsequently, we tested this 2I/E model extension, together with two alternative models, in a sample of 1,006 tenth-graders from Germany by examining social, dimensional, and temporal comparison effects, relating to periods from 0.5 to 2.0 years, on students’ math and German self-concepts. Overall, we found evidence for our assumption that temporal comparisons were overestimated in previous 2I/E model studies. Nevertheless, we still found significant temporal comparison effects in our 2I/E model extension. The periods for which the temporal comparison effects became significant differed between math and German. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(2), Feb 2025, 292-307; doi:10.1037/edu0000922

Self-control has emerged as a research focus, particularly among adolescents, as they frequently struggle with self-control when studying. We examined the longitudinal relationship between achievement motivation (i.e., attainment value and mastery-approach goal) and self-control at the within-person level after controlling for trait-like interpersonal variance. We used 3-year longitudinal data sets from two panels of the 2010 Korean Children and Youth Panel Survey for the multigroup random intercept cross-lagged panel model. The final analysis included self-reported responses to academic self-control, attainment value, and mastery-approach goal for 3 years from 2,152 early adolescents (11–13 years old) and 2,163 middle adolescents (14–16 years old). Our multigroup random intercept cross-lagged panel models with two different adolescent cohorts revealed strong associations between achievement motivation and self-control at the between-person level, regardless of the adolescent cohort. At the within-person level, early and middle adolescents exhibited distinct longitudinal associations between these two variables. Early adolescents’ self-control demonstrated noticeable stability and correlations with mastery-approach goal pursuit. By contrast, middle adolescents’ self-control exhibited a fluctuating state, which was predicted by attainment value. Practically, this implies that for early adolescents, self-control may function as a trait that can determine and guide adaptive mastery-approach goal pursuit implicitly and habitually. For middle adolescents, however, self-control may no longer function as a trait; instead, it can fluctuate and be affected by their identity-related attainment value perceived within a given academic context. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(2), Feb 2025, 308-335; doi:10.1037/edu0000846

The “remembered success effect” (Finn, 2010) refers to the finding that challenging academic tasks that start or end with extra opportunities for success are preferred to challenging tasks that do not include these opportunities. Work on remembered success has primarily been done with adults. We assessed (in a preregistered study) whether the remembered success effect could be detected in two school-aged groups of students (281 third-graders and 289 sixth-graders). We examined the effect in terms of students’ future activity choices and task evaluations, as well as their expectancies for success, task values, and perceived costs, key motivational constructs from expectancy-value theory. More specifically, we tested whether students would prefer an “extended” difficult math task that began or ended with a set of moderately difficult problems (i.e., that included experiences of relative success) over a shorter task that contained the same number of difficult problems, but none of the moderate problems. Results showed that students in both grades preferred the extended task. In addition, students’ expectancies and subjective task value were higher, and perceived costs lower, in the “extended” condition than in the short condition. Results were generally stronger for the older students. Adding experiences of remembered success to challenging math tasks could turn out to be a straightforward, cost-effective way to increase the likelihood that students will choose to engage in and persist at such tasks, even as early as Grade 3. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(1), Jan 2025, 1-11; doi:10.1037/edu0000933

Research in educational psychology involves empirical investigation into the learning process with an aim to refine psychological theories of learning and their application to real-world settings where they can be used to benefit learners. Emergent methodological processes involved in learning analytics include the study of event-based data produced by individuals in learning environments where they use technology. Paradigms for substantive-methodological synergy can be used to align the strengths of educational psychology and learning analytics research. The Journal of Educational Psychology invites such collaborations. This issue illustrates the advancements to educational theory and practice that can be attained when learning analytics practices are aligned to reflect the assumptions within psychological theories of learning and learning analytics methods including feature engineering and multimodal modeling are leveraged. Exemplars demonstrate learning analytics’ potential contribution to the refinement and application of theories of learning and motivation. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(1), Jan 2025, 12-37; doi:10.1037/edu0000906

Educators, families, and students continue to debate whether homework promotes academic achievement. A resolution to this debate has proven elusive, given the often-mixed findings of the relationship between homework behavior, typically measured with often-unreliable student self-reports and achievement. We argue better estimates of these relationships require (a) changes to what data are collected to measure homework behavior and (b) more theory-informed ways to model those data. Thus, in this article, we pursued what Marsh and Hau (2007) called substantive-methodological synergy. We grounded our substantive investigation in Trautwein et al.’s (2006) Homework Model, wherein student characteristics and motivation predict homework behaviors (i.e., homework effort, homework time), which in turn predict achievement. To better understand students’ homework behavior, we used digital tools that produced trace data that could be understood and modeled via theory-informed learning analytics. We collected homework behavior data and subsequent achievements from 507 German academic-track school students who used an intelligent tutoring system to learn English as a foreign language. Our initial analyses showed that theory-aligned digital trace data captured unique information beyond self-report data. Then, we found homework effort, as conceptualized in the Homework Model and captured via theory-informed learning analytics, predicted academic performance, whereas homework time did not. Overall, behavioral trace measures of homework effort were more predictive than self-reports. These findings help to clarify the mixed findings in the homework literature and illustrate the benefits of substantive-methodological synergy between theory and learning analytic methods. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(1), Jan 2025, 38-62; doi:10.1037/edu0000903

Remote learning settings require students to self-regulate their behavioral, affective, and cognitive processes, including preventing mind wandering. Such engagement in task-unrelated thoughts has a negative impact on learning outcomes and can occur with or without students’ awareness of it. However, research on the meta-awareness of mind wandering in education remains limited, predominantly relying on self-report measures that capture discrete information at specific time points. Therefore, there is a need to investigate and measure temporal dynamics in the meta-awareness of mind wandering continuously over time. This study examined the temporal patterns of 15 mind-wandering and meta-awareness probes in a sample of university students (N = 87) while they watched a video lecture. We found that the majority (60%) of mind wandering occurred with meta-awareness. Cluster analysis identified five distinct thought sequence clusters. Thought patterns dominated by unaware mind wandering were negatively associated with fact- and inference-based learning, whereas persistent aware mind-wandering patterns were linked to reduced deep-level understanding. Initial exploration into predictive modeling, based on eye gaze features, revealed that the models could distinguish between aware and unaware mind-wandering instances above the chance level (macro F1 = 0.387). Model explainability methods were employed to investigate the intricate relationship between gaze and mind wandering. It revealed the importance of eye vergence and saccade velocity in distinguishing mind-wandering types. The findings contribute to understanding mind-wandering meta-awareness dynamics and highlight the capacity of continuous assessment methods to capture and address mind wandering in remote learning environments. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(1), Jan 2025, 63-87; doi:10.1037/edu0000902

This study leverages natural language processing (NLP) to deepen our understanding of how students integrate their ideas about genetic inheritance while engaging in an adaptive dialog. In Study 1, informed by knowledge integration (KI) pedagogy, we used responses from 1,485 students to test one NLP model to detect the ideas students express when explaining why siblings look similar but not identical and another NLP model to holistically score their response for KI. In Study 2, we used the tested NLP models from Study 1 to design an adaptive dialog that responds to students’ detected ideas. We assessed the impact of the dialog on students’ level of KI. We embedded the dialog in a web-based unit and implemented it in five middle and high schools with 11 teachers and 610 students. Students’ KI scores significantly improved across the unit, and from their initial to revised responses in the dialogs. Consistent with KI, students significantly added differing new accurate ideas. They generally linked their vague ideas to new ideas rather than dropping vague ideas. Two patterns emerged: Students who achieve partial KI form links between new accurate and initial vague ideas; Students who progress to integrated KI distinguish between initial vague and accurate ideas plus new accurate ideas to form varied links. These results clarify that students follow multiple paths to combine their ideas and construct coherent responses while studying a unit featuring adaptive dialogs. They point to designs for adaptive guidance to build on students’ ideas and promote integrated understanding. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(1), Jan 2025, 88-105; doi:10.1037/edu0000901

The process of setting goals and creating plans is crucial for self-regulated learning (SRL), yet students often struggle to construct efficient plans and establish goals. Adaptive learning environments hold promise for assisting students with such processes through adaptive scaffolding. Through the examination of data collected from 144 middle school students, we present a data-driven analysis of students’ explicit planning activities in Crystal Island, a narrative game-based learning environment. In this game, students are provided with a planning support tool that aids them in externalizing their science-related goals and plans before putting them into action. We extracted features from their planning tool use and connected them to several SRL processes and problem-solving outcomes. We found that students who engaged with the planning support tool were more likely to successfully complete the learning scenario. To investigate the potential for adaptive support with this tool, we also constructed a student plan recognition framework aimed at predicting students’ goals and planned action sequences. This framework uses student gameplay sequences as input and student interactions with the planning tool as labels for both prediction tasks. We evaluated these tasks using six machine learning models and found that all approaches improved on the majority baseline classification performance. We then investigated additional machine-learning architectures and a technique for detecting when students enact all steps in their plans as methods for improving the framework. We demonstrated performance improvement with these enhancements. Overall, results demonstrated that the planning support tool can help students engage in SRL activities and drive adaptive support in real time. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(1), Jan 2025, 106-133; doi:10.1037/edu0000905

Embodied collaborative learning, intertwining verbal and physical behaviors, is an intricate learning process demanding a multifaceted approach for comprehensive understanding. Prior studies in this field have often neglected the temporal dynamics and the interplay between verbal and bodily behaviors in collaborative learning settings. This study bridges this gap by employing an integrative approach combining social constructivism, situated cognition, and embodied cognition theories through multimodal learning analytics (MMLA) to dissect the temporal dynamics of embodied collaborative learning in a simulated clinical setting. The study operationalized the linguistic, contextual, and bodily elements of each theoretical perspective, focusing on analyzing the verbal communication, spatial behavior, and physiological responses of 56 students across 14 sessions. These multimodal data were analyzed using correlation analysis and epistemic network analysis. The results illustrated the interconnected nature of students’ verbal communication and spatial behaviors during collaborative learning and demonstrated that an MMLA approach could effectively capture the temporal dynamics of these behaviors across different learning phases. The study also identified significant differences in the behaviors of efficient and inefficient teams and between satisfied and dissatisfied students, primarily linked to spatial behaviors. These insights underline the utility of MMLA in providing a nuanced understanding of collaborative learning behavior from an integrated theoretical perspective, with implications for learning design and the development of reflection and in-the-moment analytics. This study sets the stage for further exploration of the multifaceted dynamics of collaborative learning, underscoring the value of a multimodal approach to learning analytics and educational research. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Journal of Educational Psychology, Vol 117(1), Jan 2025, 134-151; doi:10.1037/edu0000904

We present and test communicative influence as a novel measure of team dynamics that integrates theories of team cognition with collaborative problem solving (CPS) assessment frameworks. We define influence as the degree to which a teammate’s behavior dynamically predicts patterns in their team’s future CPS state, quantified as the average mutual information (AMI) between the two signals. We evaluated this novel metric in the laboratory with college students (Study 1), in middle school classrooms (Study 2), and in semistructured interviews with teachers (Study 3). In the laboratory study, influence was related to experimental assignment of students’ role (i.e., those assigned control over a shared interface had more influence than those who verbally contributed to the solution) and predicted CPS task success and students’ subjective perceptions of the collaboration. In the classroom study, the influence was not related to team size (2–4) but was negatively related to teams’ adherence to collaborative norms. Analyses of collaborative discourse suggested that influence in this context may reflect the tendency to posit ideas and make claims without building on the ideas of others. Together, these results suggest that if the distribution of influence is dominated by a controlling team member, the collaboration may be less productive and negatively perceived than if influence is more distributed across the team. Feedback from semistructured interviews with four middle school teachers (Study 3) highlighted the potential for influence to be embedded in teacher interfaces (e.g., dashboards) to help them orchestrate classrooms for collaborative learning. (PsycInfo Database Record (c) 2024 APA, all rights reserved)