Educational Psychology Review

Journal: Educational Psychology Review

Abbreviation

Educ. psychol. rev.

Publisher

Springer

ISSN

1040-726X
1573-336X

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Publications1 - 10 of 15

The Effects of Idealized and Grounded Materials on Learning, Transfer, and Interest: An Organizing Framework for Categorizing External Knowledge Representations
Belenky, Daniel M.; Schalk, Lennart (2014)
Educational Psychology Review
Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning
Rau, Martina (2017)
Educational Psychology Review
Visual representations play a critical role in enhancing science, technology, engineering, and mathematics (STEM) learning. Educational psychology research shows that adding visual representations to text can enhance students’ learning of content knowledge, compared to text-only. But should students learn with a single type of visual representation or with multiple different types of visual representations? This article addresses this question from the perspective of the representation dilemma, namely that students often learn content they do not yet understand from representations they do not yet understand. To benefit from visual representations, students therefore need representational competencies, that is, knowledge about how visual representations depict information about the content. This article reviews literature on representational competencies involved in students’ learning of content knowledge. Building on this review, this article analyzes how the number of visual representations affects the role these representational competencies play during students’ learning of content knowledge. To this end, the article compares two common scenarios: text plus a single type of visual representations (T+SV) and text plus multiple types of visual representations (T+MV). The comparison yields seven hypotheses that describe under which conditions T+MV scenarios are more effective than T+SV scenarios. Finally, the article reviews empirical evidence for each hypothesis and discusses open questions about the representation dilemma.
The Psychometric Modeling of Scientific Reasoning: a Review and Recommendations for Future Avenues
Edelsbrunner, Peter; Dablander, Fabian (2019)
Educational Psychology Review
Psychometric modeling has become a frequently used statistical tool in research on scientific reasoning. We review psychometric modeling practices in this field, including model choice, model testing, and researchers’ inferences based on their psychometric practices. A review of 11 empirical research studies reveals that the predominant psychometric approach is Rasch modeling with a focus on itemfit statistics, applied in a way strongly similar to practices in national and international large-scale educational assessment programs. This approach is common in the educational assessment community and rooted in subtle philosophical views on measurement. However, we find that based on this approach, researchers tend to draw interpretations that are not within the inferential domain of this specific approach and not in accordance with the related practices and inferential purposes. In some of the reviewed articles, researchers put emphasis on item infit statistics for dimensionality assessment. Item infit statistics, however, cannot be regarded as a valid indicator of the dimensionality of scientific reasoning. Using simulations as illustration, we argue that this practice is limited in delivering psychological insights; in fact, various recent inferences about the structure, cognitive basis, and correlates of scientific reasoning might be unwarranted. In order to harness its full potential, we make suggestions towards adjusting psychometric modeling practices to the psychological and educational questions at hand.
Comparing Multiple Theories about Learning with Physical and Virtual Representations: Conflicting or Complementary Effects?
Rau, Martina (2020)
Educational Psychology Review
In most STEM instruction, students interact with visual representations, which can be presented in either in a physical or a virtual mode or in a blended form that combines both modes. While much research has compared the effects of physical and virtual representations on students’ learning, the field is far from being able to predict when and why one representation mode is more effective than the other. One reason why making such predictions is particularly difficult is that multiple different theories have been used to explain differences between representation modes. The goal of this article is twofold. First, it presents a survey of the literature to examine which theoretical perspectives have been used to motivate comparisons of representation modes and what predictions they make about their effectiveness. A review of 54 articles reveals five theoretical perspectives: physical engagement, cognitive load, haptic encoding, embodied action schemas, and conceptual salience. While the first two make general predictions about the effectiveness of representation modes, the last three make concept-specific predictions. Second, this article compares these predictions to examine how they conflict and align. This comparison identified several conflicts between theories that predict opposite effects, as well as several alignments where theories make the same predictions but based on different mechanisms. Further, this comparison revealed common confounds in experimental designs of the reviewed studies. The article concludes with recommendations for research to address the identified conflicts and with recommendations for instructors and designers of blended technologies for appropriate choices of representation modes.
The Relative Merits of Explicit and Implicit Learning of Contrasted Algebra Principles
Ziegler, Esther; Edelsbrunner, Peter A.; Stern, Elsbeth (2018)
Educational Psychology Review
Knowledge representations that result from practicing problem solving can be expected to differ from knowledge representations that emerge from explicit verbalizing of principles and rules. We examined the degree to which the two types of learning improve problem-solving knowledge and verbal explanation knowledge in classroom instruction. We presented algebraic addition and multiplication problems to 153 sixth graders randomly assigned to two conditions. Students in the explicit learning condition had to verbally compare contrasted algebra problems. Students in the implicit learning condition had to generate and solve new problems. On three follow-up tests over 10 weeks, students in the explicit learning condition exhibited better problem-solving knowledge than students in the implicit learning condition, as well as some advantages in verbal concept knowledge. Implicit learning showed some advantages on not directly taught but incidentally learned aspects. Overall, this outcome favors the explicit learning of concepts. Explicit comparison fostered student performance on non-verbal and verbal measures, indicating that verbalization facilitates effective comparison.
Epistemic Beliefs in Science – A Systematic Integration of Evidence From Multiple Studies
Schiefer, Julia; Edelsbrunner, Peter; Bernholt, Andrea; et al. (2022)
Educational Psychology Review
Recent research has integrated developmental and dimensional perspectives on epistemic beliefs by implementing an approach in which profiles of learners' epistemic beliefs are modeled across multiple dimensions. Variability in study characteristics has impeded the comparison of profiles of epistemic beliefs and their relations with external variables across studies. We examined this comparability by integrating data on epistemic beliefs about the source, certainty, development, and justification of knowledge in science from six studies comprising N = 10,932 German students from elementary to upper secondary school. Applying latent profile analyses to these data, we found that profiles of epistemic beliefs that were previously conceptualized were robust across multiple samples. We found indications that profiles of epistemic beliefs homogenize over the course of students' education, are related to school tracking, and demonstrate robust relations with students' personal characteristics and socioeconomic background. We discuss implications for the theory, assessment, and education of epistemic beliefs.
Systematic Review of Educational Approaches to Misinformation
Rau, Martina; Premo, Anna Elisabeth (2025)
Educational Psychology Review
Misinformation can have severe negative effects on people’s decisions, behaviors, and on society at large. This creates a need to develop and evaluate educational interventions that prepare people to recognize and respond to misinformation. We systematically review 107 articles describing educational interventions across various lines of research. In characterizing existing educational interventions, this review combines a theory-driven approach with a data-driven approach. The theory-driven approach uncovered that educational interventions differ in terms of how they define misinformation and regarding which misinformation characteristics they target. The data-driven approach uncovered that educational interventions have been addressed by research on the misinformation effect, lie detection, information literacy, and fraud trainings, with each line of research yielding different types of interventions. Furthermore, this article reviews evidence about the interventions’ effectiveness. Besides identifying several promising types of interventions, comparisons across different lines of research yield open questions that future research should address to identify ways to increase people's resilience towards misinformation.
Using Electroencephalography to Measure Cognitive Load
Antonenko, Pavlo; Paas, Fred; Grabner, Roland; et al. (2010)
Educational Psychology Review
Application of physiological methods, in particular electroencephalography (EEG), offers new and promising approaches to educational psychology research. EEG is identified as a physiological index that can serve as an online, continuous measure of cognitive load detecting subtle fluctuations in instantaneous load, which can help explain effects of instructional interventions when measures of overall cognitive load fail to reflect such differences in cognitive processing. This paper presents a review of seminal literature on the use of continuous EEG to measure cognitive load and describes two case studies on learning from hypertext and multimedia that employed EEG methodology to collect and analyze cognitive load data.
How to Make Recommendations for Educational Practice from Correlational Data Using Structural Equation Models
Dumas, Denis; Edelsbrunner, Peter (2023)
Educational Psychology Review
In this commentary, we outline a five-phase process by which recommendations for educational practice can be distilled from correlational data using structural equation modeling (SEM). First, meta-theoretical beliefs associated with latent variables-that mental attributes cause behavior and can therefore be measured indirectly by observing multiple indicators of that behavior-must be adopted and made explicit. Next, an SEM must be formulated with relevant pathways and covariates that exhaustively represent our theoretical knowledge and assumptions about the structure of the psychological phenomena being studied. Third, model-data-fit indices and estimated parameters associated with the SEM should be carefully interpreted. Fourth, the model should be replicated across educational contexts, and any necessary changes should be incorporated into the relevant psychological theory. Fifth, the results of multiple studies can then be interpreted together with other sources of evidence as a basis for communicating our current theoretical understanding and caveats to practitioners. We also point out that educational recommendations should likely never be entirely prescriptive, and instead lie on a continuum of specificity based on the strength of the evidence.
Exploring Educational Approaches to Addressing Misleading Visualizations
Rho, Jihyun; Rau, Martina (2025)
Educational Psychology Review
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.

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