Educational Psychology Review最新文献

When faced with challenging thinking tasks accompanied by a feeling of uncertainty, people often prefer to opt out (e.g., replying “I don’t know”, seeking advice) over giving low-confidence responses. In professions with high-stakes decisions (e.g., judges, medical practitioners), opting out is generally seen as preferable to making unreliable decisions. Contrarily, in educational settings, despite being designed to prepare students for real-life challenges, opting out is often viewed as an indication of low motivation or an avoidance of challenges. Presenting a complementary perspective, metacognitive research dealing with knowledge management and problem-solving shows substantial empirical evidence that both adults and children can use opt-out options to enhance the quality of their responses. Moreover, there are initial signs that strategic opting out can increase the efficiency of self-regulated effort. These opportunities to improve self-regulated learning have yet to be exploited in instructional design. Research guided by Cognitive Load Theory (CLT), which focuses on effort allocation in the face of cognitive challenges, has largely ignored the benefits of opting out as a strategy for improving effort allocation. The present review summarizes advantages and pitfalls within the current state of knowledge. Furthermore, we propose new avenues of inquiry for examining the impact of incorporating explicit opt-out options in instructional design to support knowledge and skill acquisition. As a novel avenue, we urge educators to develop effective opting-out skills in students to prepare them for real-life challenges.

This study aims to evaluate the effectiveness of concept maps on science achievement among elementary and secondary education students, including low-achieving students. A systematic search located 55 studies about concept mapping in science achievement published in peer-reviewed journals and dissertations between 1980 and 2020. We extracted 58 independent standardized mean difference effect sizes from 55 eligible studies involving 5,364 students from Grade 3 to Grade 12 who used concept maps for learning in physics/earth science, chemistry, and biology that met the specified design criteria. A random-effects model meta-analysis revealed that the mean effect size was moderate for overall science (g = 0.776). The mean effect sizes varied from moderate to large based on the subject area (g = 0.671 for biology; g = 0.590 for chemistry; g = 1.040 for physics and earth science); these differences between groups were not statistically significant (p = 0.220). Concept maps were generally associated with increased science learning across several learning and teaching conditions, and methodological features (low-achieving students, higher teaching guidance, intermediate grades, low- or middle-income countries, journal publications, and late year of publication). However, we found significant heterogeneity in most subsets. Implications for future research and practice recommendations are discussed.

This special issue was motivated by the realization that student motivation is inherently complex and no single framework can capture it in its full richness. However, the current zeitgeist in educational psychology seems to explicitly discourage attempts at integration as researchers are incentivized to stay within their own theoretical camps. In this special issue, we asked seven research teams to revisit their theoretical assumptions and cross-fertilize their own theories with other frameworks. We also invited three distinguished luminaries to critique and comment on this undertaking. We highlighted key issues that prevent cross-fertilization of ideas across theoretical borders, surfaced potential dangers associated with naïve integration, and proffered future directions that could nudge motivation science towards a more cumulative and integrative approach.

Our study is among the first to provide a comprehensive review of cross-national patterns of gender differences in various STEM-related constructs—achievement, beliefs, attitudes, aspirations, and participation, concerning country-level gender equality. We complement our review with empirical analyses utilizing rigorous methodologies and richer datasets from individual and country levels. Specifically, we examine gender differences in relative strength measures (e.g., strength in science relative to math and reading) and STEM aspirations and graduation, using PISA 2015 and PISA 2018 data from 78 countries/regions (N = 941,475). Our analysis corroborates our literature review, indicating that support for both the gender stratification hypothesis and the gender equality paradox (i.e., whether gender gaps favoring male students are smaller or larger in more gender-equal countries) is generally inconsistent and weak. Various factors contribute to this inconsistency, including specific outlier countries, different years of data collection, diverse data sources, a range of composite and domain-specific measures of gender equality, and statistical models. Our study also introduces a robust statistical model to compare performances in three subjects and evaluate the predictive power of relative strength measures for STEM aspirations at the student level. Our analyses reveal that general academic achievement and math achievement relative to reading are key predictors of STEM aspirations, compared with science achievement relative to math and reading. By juxtaposing both levels of analysis, our findings offer a more nuanced understanding of gender differences in decision-making processes that lead to careers in STEM-related fields.

In educational research, there is the general trade-off that empirical evidence should be generalizable to be applicable across contexts; at the same time, empirical evidence should be as specific as possible to be localizable in subject-specific educational interventions to successfully transfer the empirical evidence to educational practice. This trade-off is further increased by the fact that the diverse instructional contexts, such as school or student characteristics constrain the applicability of empirical evidence. Several approaches have been proposed to address this issue, however, emphasized the different problems (i.e., localization, generalization, transferability) rather in an isolated manner. To this end, in this article, we introduce a synergistic approach, the LoGeT (localize, generalize, transfer) model, which systematically integrates co-design (localization strategies) and ManyClasses principles (generalization strategies) with co-constructive transfer activities, to generate empirical evidence that may be applicable in educational practice. To illustrate the LoGeT model, we present three long-term projects, covering different granularities and durations of educational interventions across different fields of education (teacher education, adaptive teaching, non-interactive teaching) that successfully applied the LoGeT approach. Finally, we outline further directions for future iterations of the LoGeT model. We hope that the LoGeT approach may be a stimulus to guide researchers as well as practitioners alike to design generalizable and evidence-based educational interventions that are rooted in localized instructional contexts.

Educators and instructional designers have used the Universal Design for Learning (UDL) framework to guide their design of inclusive instruction for students with and without disabilities. Despite UDL having entered its 4th decade of development and research, there have been ongoing critiques of UDL for lacking clarity in definition, challenges with implementation, and insufficient evidence of its effectiveness. These critiques warrant further evaluation of UDL, especially with a focus on the theoretical underpinnings behind its conceptualization and implementation. Thus, we synthesized 32 peer-reviewed studies published between 1999 and 2023 that focused on UDL implementation in preK-12 educational settings and measured various aspects of student learning outcomes (e.g., cognitive, motivational, and behavioral). Specifically, we evaluated each study’s intervention or instructional design in terms of its alignment to UDL checkpoints, guidelines, and/or principles as well as existing theories of learning or instructional design. Results revealed several interrelated challenges that stymie UDL research, including the absence of explicit alignment between UDL checkpoints and intervention or instructional designs investigated in the extant literature, the uneven coverage of implemented checkpoints and corresponding guidelines, the overlap among multiple checkpoints and guidelines, and the lack of theoretical guidance regarding the design and implementation processes. Based on these findings, we provide recommendations for strengthening the research base for less frequently applied UDL checkpoints, recommendations for documenting checkpoints and relationships among checkpoints as indispensable components of UDL implementation, and directions for future research conducted via systematic UDL implementation guided by established theories.

We explored the potential of using a peer relations approach for researching children’s citizenship in elementary classrooms. Children express or enact citizenship through their behavior toward classmates and the relationships they engage in (i.e., lived citizenship). These behaviors and relationships can be more or less in line with goals for citizenship education. We propose that, through peer relations methodology, these behaviors and relationships can be assessed systematically. In addition, some of the widely researched behaviors and relationships in peer relations research already closely align with goals for citizenship education. With this theoretical and methodological argument, we consider recent publications on classroom behaviors (i.e., prosocial behavior and aggression) and relationships (i.e., positive and negative affect) and their meaning for exemplary goals for citizenship education (i.e., solidarity, peace, and social cohesion). We show how individual children and classroom peer groups differ in these regards and thus in their citizenship and how these differences can be stratified by gender, ethnic background, and socioeconomic status. Specific attention is paid to the role of teachers, as organizers of the social structures in their classrooms and as educators who can promote citizenship. Finally, we propose new ways for using peer reports to study citizenship in elementary classrooms more directly and to discover potential avenues for teachers to foster citizenship through peer relations.

The social-belonging intervention is a wise psychological intervention designed to convey the message that worries and doubts about belonging during transition into higher education are common to all first-year students and tend to dissipate with time. The aim of this first systematic review on the social-belonging intervention was to investigate whether it can reduce achievement gaps in postsecondary education. Moreover, research questions about other outcomes possibly affected by this intervention and factors that may affect its efficacy were investigated. The protocol of this systematic review was registered with INPLASY. Four databases were searched for randomised control trials published in peer-reviewed journals testing the intervention in higher education. In total, 17 articles, which included a total of 21 studies, satisfied the inclusion and exclusion criteria as well as the quality assessment and were therefore included in this review. The reviewed research suggests that the intervention can narrow achievement gaps in higher education, as well as affect sense of belonging, academic fit, perception of adversities, use of campus support and the mental and physical health of disadvantaged students. These findings and their limitations, future research directions and recommendations are discussed in the final section.

Abstract

Computer-based simulations for learning offer affordances for advanced capabilities and expansive possibilities for knowledge construction and skills application. Virtual agents, when powered by artificial intelligence (AI), can be used to scaffold personalized and adaptive learning processes. However, a synthesis or a systematic evaluation of the learning effectiveness of AI-powered virtual agents in computer-based simulations for learning is still lacking. Therefore, this meta-analysis is aimed at evaluating the effects of AI-powered virtual agents in computer-based simulations for learning. The analysis of 49 effect sizes derived from 22 empirical studies suggested a medium positive overall effect, (overline{g }=0.43) , SE = 0.08, 95% C.I. [0.27, 0.59], favoring the use of AI-powered virtual agents over the non-AI-powered virtual agent condition in computer-based simulations for learning. Further, moderator analyses revealed that intervention length, AI technologies, and the representation of AI-powered virtual agents significantly explain the heterogeneity of the overall effects. Conversely, other moderators, including education level, domain, the role of AI-powered virtual agents, the modality of AI-powered virtual agents, and learning environment, appeared to be universally effective among the studies of AI-powered virtual agents in computer-based simulations for learning. Overall, this meta-analysis provides systematic and existing evidence supporting the adoption of AI-powered virtual agents in computer-based simulations for learning. The findings also inform about evidence-based design decisions on the moderators analyzed.

Theories in motivation science, and in psychological science more generally, are in a state of fragmentation that impedes development of a robust body of knowledge. Furthermore, fragmentation hinders communication among scientists, with practitioners, and with policymakers and the public. Theoretical integration is needed to overcome this situation. In this commentary, I first provide an overview of the integrative frameworks presented in this collection of articles. Based on this overview, I discuss if and when we should integrate theories. Several non-trivial conditions need to be met for integration, including convergence of phenomena, constructs, and theoretical propositions. Next, I address strategies for integration, including rules for merging constructs and ways to integrate propositions. I also discuss how the generation of integrative frameworks, if not successfully enacted, can paradoxically lead to further proliferation rather than a reduction of theories. In contrast, successful integration reduces redundancy and simplifies the conceptual space used to describe, explain, or predict a set of phenomena. Successful integration may require not only theoretical work but also empirical validation, strategic efforts in the scientific community, and change of institutional policies. In conclusion, I argue that within-discipline integration alone is not sufficient to overcome the current theoretical stagnation in the field. Attention to advances in neighboring disciplines, formalization of models of motivation, and theoretical differentiation to consider the specificity of constructs, populations, and contexts are needed as well.