Educational Psychology Review最新文献

After decades of being conceptualised solely as a lack of interest, boredom has recently gained attention as an important construct in its own right. However, there is still a lack of studies focusing on the relations and developmental interplay of these two closely related constructs. This study examines the overall long-term developmental structure and interplay of students’ boredom and interest in the school domains of mathematics and German from fifth to eighth grade. We investigated German secondary school students (N = 1471) over four waves of measurement, using self-report questionnaires. Confirmatory factor analyses in preparation to the longitudinal approach revealed a significantly better fit for two- vs. one-factor models, indicating an empirical separability of boredom and interest. This was further supported by different stabilities in our latent cross-lagged models with low autoregressive paths for boredom and high paths for interest. The latent cross-lagged models also revealed that higher levels of earlier interest were related to lower levels of later boredom. Surprisingly, individuals with higher boredom scores relative to others on average increased in their interest from the second time point onwards. Findings were robust for German and mathematics. Overall, the results show that while boredom and interest have a large phenomenological overlap, they are empirically separable constructs with different levels of stability and influence each other in a distinctive manner throughout their developmental interplay. Implications for research and practice are outlined.

Misleading data visualizations have become a significant issue in our information-rich world due to their negative impact on informed decision-making. Consequently, it is crucial to understand the factors that make viewers vulnerable to misleading data visualizations and to explore effective instructional supports that can help viewers combat the negative effects of such visualizations. Drawing upon the framework of graph comprehension, this article examines how poorly designed data visualizations can deceive viewers. A systematic review identified 26 pertinent articles that met our inclusion criteria. We identified two primary factors leading to viewers’ misinterpretations of misleading data visualizations: the graphical and contextual elements within the data visualizations themselves. Further, we identified two types of interventions aimed at reducing the negative impact of misleading data visualizations. One type of intervention focuses on providing external aids for viewers to recognize the misleading graphical and contextual elements within the data visualization. In contrast, another type of intervention aims at enhancing viewers’ ability to engage with data visualizations through additional interactions for reflection. Based on these findings, we identify areas that remain under-investigated, specifically those aiming at teaching viewers to interact with data visualizations. We conclude by proposing directions for future research to investigate interventions that strengthen viewers’ ability to go beyond their first (potentially false) impression with data visualizations through additional interactions with the data visualization.

Students involve themselves in learning activities multidimensionally, including behaviorally, cognitively, emotionally, and agentically. This multidimensional involvement predicts important outcomes, but it is also possible that each type of engagement might have its own specialized purpose or function. To investigate this possibility, we proposed and tested the specialized purpose hypothesis, which is that each type of engagement has its own specialized function targeted toward a specific purpose, such as to boost achievement, social support, motivation, or well-being. To test this hypothesis, we conducted four meta-analyses, utilizing multilevel random effects models. Each meta-analysis tested whether type of engagement differentially predicted students’ achievement (meta-analysis #1), social support (meta-analysis #2), motivation (meta-analysis #3), or well-being (meta-analysis #4). The database included 652 effect sizes from 62 studies within 54 articles involving 32,403 P-16 student-participants (M_age = 16.8 years-old; 51.2% female). All 62 studies measured all four types of engagement so that we could compare the relative strength of association between each type of engagement and each correlate. Behavioral engagement was the strongest predictor of achievement. Agentic engagement was the strongest predictor of social support. Cognitive engagement did not show a specialized relation with any outcome. Emotional engagement was strongly associated with both motivation and well-being. These findings generally support the specialized purpose hypothesis, but they also raise important and challenging questions for future theory and research about how to better conceptualize and measure each type of engagement.

Students with or at risk of reading difficulties (RD) benefit from accurate early identification and intervention. Previous research has employed various decoding measures to screen students for RD, but the criteria for identification have been inconsistent. Assessing students with RD is especially challenging in English Language Learners (ELLs), as vocabulary deficits can impact decoding. Additionally, few research syntheses have examined whether researchers use different measures to screen ELLs and EL1s for RD, and whether these differences result in distinct decoding profiles between ELLs with RD and EL1s with RD. To address these gaps, this study uses a meta-analysis to examine the decoding measures used in RD assessments and whether outcomes differ for ELLs and EL1s. The findings show that real word reading assessments identify students with more pronounced decoding deficits than nonword reading assessments. Despite the use of different RD screening measures for ELLs and EL1s, the gap between ELLs with and without RD was similar to that between EL1s with and without RD. These results suggest that real word-reliant measures, which are influenced by word knowledge, provide a more comprehensive assessment of RD than nonword-reliant measures for both ELLs and EL1s. We encourage future researchers to use consistent decoding measures when screening RD in both populations, to maximize comparability of findings.

Teacher burnout, stress, and turnover are increasing globally, underscoring the need to explore ways to reduce burnout and support teacher well-being. This scoping review identifies the contents, characteristics, and results of interventions to increase teacher well-being and reduce burnout. The search was conducted using two databases (Education Research Complete and ERIC). Out of 958 studies, 46 addressed interventions to support teacher well-being or reduce teacher burnout. The data covered 7369 participants in 15 countries. Of the 46 studies, 14 used mixed methods, four qualitative approaches, and 28 used quantitative approaches. The content of the interventions primarily focused on improving individual well-being, with some interventions incorporating communal activities. The qualitative content analysis revealed a broad spectrum of intervention activities, including physical activity, mindfulness and meditation, professional development, therapy-based techniques, gratitude practices, and a mix of multiple activities. The PERMA-H model of positive psychology is applied to unify the heterogeneous field of teacher well-being intervention research. The PERMA-H model's contents were broadly consistent with the intervention's contents, emphasising engagement (E), positive emotions (P), relationships (R), and health (H). The gratitude interventions, therapy-based interventions, physical activity interventions, and most mindfulness and meditation interventions, professional development and mixed activities interventions positively contributed to teacher well-being. Overall, the review highlights the diverse methods and theoretical frameworks employed to address teacher well-being, which the PERMA-H model can unify.

There is considerable research evaluating the effects of family members implementing shared book reading interventions, especially during early childhood. However, less is known about the effects of family members providing instruction to help their school-aged children develop literacy skills, including both code-focused and meaning-focused skills that facilitate reading comprehension. The purpose of this meta-analysis was to describe and evaluate recent research examining the effects of at-home, family-implemented literacy interventions for school-aged children. A total of 25 interventions across 22 studies (12 with group designs and 10 with single-case experimental designs) were analyzed. The average effect on combined literacy outcomes was estimated as g = 0.36 (p < .01; Q = 191.83; I² = 36.17) for group design studies and g = 1.50 (p < .01; Q = 114.58; I² = 38.58) for single-case experimental design studies. Notably, for group design studies, effects varied by literacy outcome type. The mean effect for code-focused outcomes (i.e., PA, decoding/word reading, spelling, text reading) was g = 0.28 (p < .01) and the mean effect for meaning-focused outcomes (i.e., vocabulary, listening comprehension, reading comprehension) was g = 0.41 (p < .01). Overall, these findings support the implementation of family-delivered literacy interventions to improve literacy outcomes for school-aged children. At the same time, this meta-analysis revealed the paucity of research examining the effects of family-implemented literacy interventions, especially for older children, indicating a need for more research on this topic.

Immersive learning is predominantly constrained to technology-based interventions but has the potential for more diverse applications. This study reports on an experiment investigating the learning affordances of psychological immersion evoked by narrative absorption. A total of 228 participants were randomly assigned to one of three forms of media, an image, a word list, and a narrative, all of which contained identical items to be memorized for immediate and delayed free recall memory tests. Other variables measured were immersion, extraneous cognitive load, and mental imagery. ANOVA and correlation analyses showed that the narrative media was found to be significantly more immersive and that it evoked mental imagery in individuals at higher levels than both the list and image media. Importantly, there was more decay in memory recall between immediate and delayed tests for those exposed to the list and the image than for those who read the narrative. This implies the utility of immersive narratives for spontaneous mental image generation, which leads to improved knowledge retention. Other implications for immersive learning theory are discussed, and practical solutions for incorporating narrative immersion in learning are also suggested.

Self-report measures are essential sources of information about learners’ studying perceptions. These perceptions also guide self-regulated learning (SRL) decisions and strategies in future studying. However, the development of self-report methods has not kept pace with other multi-modal methodological advancements, particularly in the field of self-regulated learning. The purpose of this study was to test the psychometric adequacy and predictive utility of four complementary SRL-grounded measures examining students’ perceptions of SRL during studying. Participants were two samples (N = 220; N = 473) of post-secondary students enrolled in various academic disciplines. Exploratory and confirmatory factor analyses confirmed the measurement adequacy of (a) a 4-factor SRL self-efficacy measure, (b) a 4-factor SRL importance measure, (c) a 6-factor self-regulated learning practices measure, and (d) a 6-factor academic challenges measure. The predictive validity of factors within each measure revealed that (a) prioritizing and feeling confident about planning and foundational academic behaviors positively predicted academic performance, and (b) SRL practices were either positively associated with academic performance or negatively associated with academic challenges. Despite being underrepresented in most measures of SRL, task understanding practices were found to be important for predicting academic performance beyond other SRL practices. Overall, findings indicate that student’s self-reports about SRL beliefs and practices can predict academic outcomes.

Training of self-regulated learning is most effective if it supports learning strategies in combination with metacognitive regulation, and learners can transfer their acquired metacognitive regulation skills to different tasks that require the use of the same learning strategy (near transfer). However, whether learners can transfer metacognitive regulation skills acquired in combination with a specific learning strategy to the regulation of a different learning strategy (far transfer) is still under debate. While there is empirical evidence that learners can transfer metacognitive regulation between different learning strategies of the same type (e.g., from one cognitive learning strategy to another), whether transfer also occurs between learning strategies of different types is an open question. Here, we conducted an experimental field study with 5th and 6th grade students (N = 777). Students were cluster-randomized and assigned to one of three groups: two experimental groups receiving different training on the metacognitive regulation of a cognitive learning strategy and one control group receiving no training. After training, students worked on two different tasks; after each task, we measured their metacognitive regulation of a resource management strategy, that is, investing mental effort. Results (based on data from 368 students due to pandemic conditions) indicated far metacognitive regulation transfer: After training, students in the training groups were better able to metacognitively regulate their mental effort than students in the control group. Although effect sizes were small, our results support the hypothesis of far transfer of metacognitive regulation.

There is a need for robust evidence about which educational interventions work in preschool to foster children’s cognitive and socio-emotional learning (SEL) outcomes. Lab-based individually randomized experiments can develop and refine such interventions, and field-based randomized experiments (e.g., cluster randomized trials) evaluate their effectiveness in real-world daycare center settings. Applying reliable estimates of design parameters in the context of a priori power analyses is essential to ensure that the sample size of these studies is adequate to support strong statistical conclusions regarding the strength of the intervention effect. However, there is little knowledge on relevant design parameters with preschool children. We therefore utilized a systematic collection of individual participant data from four German probability samples (554 ≤ N ≤ 2928) with preschool children (aged two to six years) to estimate and meta-analyze design parameters. These parameters are relevant for planning single-level (e.g., in non-clustered lab-based settings), two-level (children nested in daycare centers), and three-level (children nested in groups, with groups nested in daycare centers) randomized intervention studies targeting cognitive and SEL outcomes assessed with three methods (standardized tests, parent ratings, and educator ratings). The design parameters depict between-group and -center differences as well as the proportion of variance in the outcomes explained by different covariate sets (socio-demographic characteristics, baseline measures, and their combination) at the child, group, and center level. In conclusion, this paper provides a rich source of design parameters, recommendations, and illustrations to support a priori power analyses for randomized intervention studies in early childhood education research.