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Alexander Eitel; Marie-Christin Krebs; Claudia Schöne – Educational Psychology Review, 2025
Given the many opportunities for technology use in education nowadays (e.g., Large language models, explainer videos, digital quizzing), teachers should know and rely on evidence-based answers to questions about when, how, and why technology-augmented instruction helps or hinders learning. To date, finding these answers requires integrating…
Descriptors: Predictor Variables, Technology Uses in Education, Educational Technology, Computer Assisted Instruction
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Hoch, Emely; Sidi, Yael; Ackerman, Rakefet; Hoogerheide, Vincent; Scheiter, Katharina – Educational Psychology Review, 2023
It is well established in educational research that metacognitive monitoring of performance assessed by self-reports, for instance, asking students to report their confidence in provided answers, is based on heuristic cues rather than on actual success in the task. Subjective self-reports are also used in educational research on cognitive load,…
Descriptors: Metacognition, Self Efficacy, Self Evaluation (Individuals), Student Behavior
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Leppink, Jimmie; Pérez-Fuster, Patricia – Educational Psychology Review, 2019
Self-rated mental effort has been and continues to be the most widely used measure of cognitive load. This single-item measure is often used as a predictor variable in linear models for predicting performance or some other response variable. While an advantage of linear models is that they are fairly easy to understand, they fall short when the…
Descriptors: Cognitive Processes, Difficulty Level, Predictor Variables, Time on Task
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Rau, Martina A. – Educational Psychology Review, 2020
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…
Descriptors: Learning Theories, Visual Aids, STEM Education, Blended Learning