Individually weighted-average models (IWAMs) assume that domain-specific self-perceptions are weighted by their personal importance when forming global self-evaluations, an assumption derived from William James's (1890) classic formulation of self-worth. Despite its intuitive appeal and continued widespread acceptance, empirical support for this assumed weighting mechanism remains weak and inconsistent. We provide a comprehensive test of whether self-reported importance functions as the psychological weight implied by IWAMs. We compare IWAMs with unweighted and group-weighted models based on aggregated importance ratings and empirically derived regression weights, using a staged design incorporating multitrait–multimethod validation, manifest model comparisons, and fully latent structural equation models. IWAMs did not outperform empirically derived group-weighted models and provided little evidence that self-perceived importance functions as the psychological weight implied by the Jamesian formulation. Across analytic frameworks, self-concept × importance interactions contributed negligible additional variance. Multiple measures of importance demonstrated acceptable construct validity, including convergent and discriminant validity, core–non-core differences in means, and expected relations with global self-concept, indicating that while importance ratings have construct validity, they do not function as the actual weighting mechanism assumed by the Jamesian model. Instead, although weighting processes are clearly evident, they are not captured by explicit self-reports of importance, providing little support for an idiographic weighting process. Rather, weighting appears to reflect shared weighting structures not captured by importance ratings. More broadly, these findings challenge the use of subjective self-reports as indicators of weighting mechanisms and highlight the need to distinguish construct validity from mechanism validity when evaluating weighted-average models.

Abstract This paper addresses the underexplored domain of teacher self-concept by introducing the ROPE model—a process-oriented framework that conceptualizes self-concept as a dynamic interplay of motivations, beliefs, and attributes. The proposal is that teacher self-concept is primarily driven by two core motivational strands: self-improving (seeking growth and feedback to enhance impact) and self-aligning (seeking confirmation and consistency with existing self-views). The ROPE model weaves together three levels—motivations (strands), beliefs (yarns), and attributes (fibers)—to illustrate how teachers form, maintain, and enact their professional identities. Part I outlines the theoretical foundations and structure of the ROPE model; Part II explores how self-improving and self-aligning orientations manifest in classroom practice, pedagogical choices, student engagement, and adaptability; and Part III discusses implications for teacher recruitment, professional development, performance appraisal, and future research.

It is understood that teachers' beliefs exist within complex systems, yet there is limited empirical research on such systems. This study investigated systems of teachers' pedagogical beliefs (e.g., teaching, curriculum, learning), motivational beliefs (e.g., self-efficacy, personal responsibility, goal orientation), and beliefs about students. Integrated clusters of teacher beliefs were identified within five higher-order factors. One cluster included motivations to teach based on social contribution, mastery goals, and focus on deep learning and relational teaching. Another cluster connected fixed attitudes about self and learners, personal utility motivations, and pedagogical beliefs focused on surface-level knowledge and transmission-type approaches to teaching, in addition to lower expectations for learners. Other clusters of beliefs related to intrinsic motivation and self-efficacy, assessment beliefs, and teacher sense of personal responsibility. Findings provide new insights into the structure of teacher belief systems and illustrate opportunities to strengthen empirically supported understandings of the complex constructs of teacher belief systems.

By quantitatively integrating results of meta-analyses, second-order meta-analyses (SOMAs) from educational psychology address far-reaching questions of interest to adjacent scientific fields, policy, and educational practice. Conducting a SOMA, however, is time-consuming, particularly the extraction of statistical results from meta-analyses. Large Language Models (LLMs) have the potential to accelerate data extraction, as evidenced by evaluations of data extraction from primary studies. Evaluations of their accuracy in extracting results from meta-analyses to conduct SOMA are needed. We compare the accuracy of three LLMs with that of human experts extracting data from 156 educational meta-analyses investigating students’ achievement, randomly chosen from the Visible Learning database. LLMs and humans extracted effect sizes, the number of included studies, and the number of students. To assess accuracy, we established a gold standard benchmark by resolving discrepancies between LLMs and human experts through expert adjudication. Results show that the distributions of data from all coders and the standard were similar and showed no systematic bias. Accuracy reached ICCs of 0.95/0.81 for the two human experts, and 0.96/0.97/0.96 for LLMs (Gemini2.5Pro/GPT4.1/GPTo3), with percentage agreement of 86

For decades, feedback to students has been discussed as one of the most powerful predictors of student learning and achievement. Previous studies have suggested that the type of feedback and its degree of elaboration, immediacy, and relatability are central to its effectiveness. However, these factors explain only parts of the variability in effects of feedback on student learning. Therefore, more recent work has proposed a shift toward models that more strongly emphasize the role of the student in the effectiveness of feedback and investigate how teacher feedback is perceived and how it is related to specific student characteristics (e.g., motivation and achievement). In this study, we echo the call for a stronger focus on the student when investigating the long-term effectiveness of teacher feedback using rich data from 2,121 German lower secondary school students who were repeatedly assessed in Grades 5 to 7. More specifically, we investigated reciprocal relationships between students’ perceptions of different types of teacher feedback (i.e., at the self-level, the process level, and the self-regulation level) and students’ self-concept, intrinsic value, and achievement in mathematics using full-forward cross-lagged panel models (FF-CLPMs) and random intercept cross-lagged panel models (RI-CLPMs). Considering these variables simultaneously, we found evidence for associations between prior self-concept, intrinsic value, achievement, and perceptions of different forms of subsequent teacher feedback. Furthermore, we found that prior perceptions of feedback were related to subsequent self-concept but not to any of the other variables. Our results underscore the need to more thoroughly investigate how feedback is longitudinally and reciprocally related to student motivation and achievement.

The mechanism through which emotional states impact learning is not yet fully understood. Through the lens of cognitive load theory, this study examines the relationship between emotional valence and learning during an algebra-based mathematics task and explores cognitive load as a potential mechanism through which emotions impact learning. Using structural equation modelling and path analysis of Australian Year 7 and 8 Secondary School students completing an algebraic learning task, we test a hypothesised model whereby extraneous cognitive load mediates the relationship between positive emotions, painful emotions, and learning. This model was tested against an alternative model with emotions mediating the relationship between extraneous cognitive load and learning. Results demonstrate that extraneous cognitive load mediates the relationship between painful emotions and learning. Alternatively, positive emotions were related to learning but not mediated by extraneous cognitive load. Implications of these findings for teachers and educators are also discussed.

AbstractWe, in education, all have a common aim: We want students to be able to think deeply about what we teach them, go beyond their current experiences, and have a deep understanding of the world. We want to enable them to think critically, work together, solve problems, read for understanding, and carry out complex cognitive tasks. If we want students to be able to do all this, we should just include itt in the curriculum and teach them, right? In this chapter, we discuss why this apparently obvious strategy of simply teaching children how to think deeply does not work, and offer an alternative way forward. This chapter discusses the prominent role of knowledge in how we learn, think, read, understand, and solve problems. Insights from cognitive and educational psychology, sociology, and curriculum studies are used to underpin the current knowledge revival that is widely being observed in education.

IntroductionTeaching materials are more than just classroom tools — they shape how teachers teach and how they grow professionally. While widely used, their impact across different stages of a teacher’s career has received limited attention. This study explores how different types of materials support both instructional design and professional development, revealing their evolving role across a teacher’s journey.MethodsWe conducted a large-scale survey (n = 2,585) of German-speaking educators, all active users of an online educational platform (eduki). The survey included Likert-scale and open-ended items on material usage, instructional impact, professional growth, and classroom confidence. We analyzed the results using factor analysis and MANOVA to identify patterns and differences across career stages.ResultsFindings show that instructional impact is highest among trainees (mean = 3.55), while the influence on professional growth increases with experience, peaking among very experienced teachers (mean = 3.91). Teacher-created materials were rated as most useful (90.1%), and teachers reported high autonomy (94.1%) in selecting and adapting materials — a factor closely tied to increased classroom confidence. Two strongly correlated factors emerged from the analysis: “Instructional Effectiveness” and “Improve Me as a Teacher.”DiscussionRather than plateauing over time, professional development remains vibrant — and even deepens — with experience. Teaching materials play a key role not only in early-career structure but also in later-career reflection and refinement. Empowering teachers to select and adapt resources appears to strengthen both instructional design and long-term growth, challenging traditional linear models of teacher development.

AbstractThe curriculum is a complex concept central to educational debates. Over the years, the role of knowledge in the curriculum has, like a pendulum, shifted between two extremes, from highly visible to virtually invisible knowledge elements. In this chapter, we consider the lessons learned from both extremes, proposing a knowledge-rich curriculum as the soundest way forward to both effectively acquire knowledge and complex cognitive skills in school, but also as a crucial lever to achieve equitable opportunities for all students. In understanding how a knowledge-rich curriculum can enhance learning, three overarching principles are discussed: (1) content-richness, (2) coherence, and (3) clarity. These principles are illustrated through practical examples from schools and educators who have effectively implemented knowledge-rich curricula, and combined with insights from relevant research on curriculum studies.

IntroductionDespite substantial global investment in curricular resources, surprisingly little empirical research has explored how teachers themselves define and evaluate the quality of instructional materials, particularly as these perceptions evolve across different stages of the teaching career. This study examined how teachers’ approaches to evaluating instructional material quality evolve across career stages.MethodsWe surveyed 2,102 educators from Germany, Austria, and Switzerland, all active users of the eduki platform. Through exploratory factor analysis and multivariate analysis of variance (MANOVA), we identified three distinct response patterns in how teachers evaluate materials: teacher perceptions of peer-created material quality, pedagogical and structural characteristics of high-quality materials, and teacher-centric considerations and practical benefits.ResultsTeachers’ priorities across these evaluation approaches vary significantly with experience. The overall MANOVA was statistically significant (Wilks’ Lambda = 0.89, F(81, 4,476) = 1.97, p < 0.001). Early-career teachers emphasize peer-created materials for lesson delivery (M = 4.34, SD = 0.69) and professional development (M = 3.88, SD = 0.87), along with stimulating content (M = 4.16, SD = 0.95) and curriculum compliance (M = 3.85, SD = 0.96). In contrast, experienced teachers prioritize practical benefits such as ease of use (M = 3.84, SD = 0.93), technology integration (M = 3.29, SD = 0.94), support for diverse learning needs (M = 3.85, SD = 0.88), and inclusion of current research (M = 3.34, SD = 0.90), with effect sizes ranging from small to moderate (d = −0.33 to 0.54). The greatest differences were observed between early-career and experienced teachers.DiscussionThese findings indicate that quality evaluation is a developmental process that evolves with teaching expertise. We propose a career-responsive approach to material development with implications for content design, professional development, and platform personalization.

The persistence of learning styles as a concept in educational discourse and research is paradoxical, given the overwhelming evidence discrediting the matching hypothesis, the notion that aligning teaching methods with students’ preferred learning styles enhances achievement. This paper examines the resurgence of learning styles across meta-analyses and proposes an explanation for their enduring appeal. Drawing on 17 meta-analyses, we distinguish between studies testing the matching hypothesis (effect size d = .04) and correlational studies (average correlation r = .24), revealing that the latter often conflates learning styles with learning strategies. Much of the research is flawed, and the argument is that there needs to be a shift away from matching learning styles toward teaching students adaptable and effective learning strategies that align more closely with task complexity and learning goals.

This study investigated the effects of a teacher professional learning intervention, underpinned by a student-centred model of feedback, on student perceptions of feedback helpfulness. The study was conducted in the context of primary education English writing in Queensland, Australia. No overall differences in feedback perceptions of students in 13 intervention and 9 comparison schools were identified following the intervention. However, more detailed analyses revealed significantly greater increases in perceived helpfulness among intervention group students for six feedback strategies. This suggests the intervention changed teachers’ feedback practices, enhancing student perceptions of feedback helpfulness. Student focus group data provided valuable qualitative insights into student feedback perceptions. Overall findings highlight the interrelatedness between feedback strategies across the feedback cycle for enhancing student learning.