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Instructing Students on Effective Sequences of Examples and Problems: Does Self-Regulated Learning Improve from Knowing What Works and Why?
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van Harsel, Milou; Hoogerheide, Vincent; Verkoeijen, Peter; van Gog, Tamara – Journal of Computer Assisted Learning, 2022
Nowadays, students often practice problem-solving skills in online learning environments with the help of examples and problems. This requires them to self-regulate their learning. It is questionable how novices self-regulate their learning from examples and problems and whether they need support. The present study investigated the open questions:…
Descriptors: Sequential Learning, Independent Study, Problem Solving, Electronic Learning
Looking through Sherlock's Eyes: Effects of Eye Movement Modelling Examples with and without Verbal Explanations on Deductive Reasoning
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van Marlen, Tim; van Wermeskerken, Margot; Jarodzka, Halszka; Raijmakers, Maartje; van Gog, Tamara – Journal of Computer Assisted Learning, 2022
Background: Eye movement modelling examples (EMME) are demonstrations in which learners' not only see a model's (e.g., a teacher's) task performance on a computer screen (as in regular video examples) but also the model's eye movements (represented as moving coloured dots overlaid on the screen). Thereby EMME help guide learners' attention towards…
Descriptors: Eye Movements, Logical Thinking, Technology Uses in Education, Task Analysis
Effects of Prior Knowledge and Joint Attention on Learning from Eye Movement Modelling Examples
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Chisari, Lucia B.; Mockeviciute, Akvile; Ruitenburg, Sterre K.; van Vemde, Lian; Kok, Ellen M.; van Gog, Tamara – Journal of Computer Assisted Learning, 2020
Eye movement modelling examples (EMMEs) are instructional videos of a model's demonstration and explanation of a task that also show where the model is looking. EMMEs are expected to synchronize students' visual attention with the model's, leading to better learning than regular video modelling examples (MEs). However, synchronization is seldom…
Descriptors: Eye Movements, Video Technology, Models, Attention
Attention to the Model's Face When Learning from Video Modeling Examples in Adolescents with and without Autism Spectrum Disorder
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van Wermeskerken, Margot; Grimmius, Bianca; van Gog, Tamara – Journal of Computer Assisted Learning, 2018
We investigated the effects of seeing the instructor's (i.e., the model's) face in video modeling examples on students' attention and their learning outcomes. Research with university students suggested that the model's face attracts students' attention away from what the model is doing, but this did not hamper learning. We aimed to investigate…
Descriptors: Video Technology, Autism, Pervasive Developmental Disorders, Outcomes of Education
Effects of Task Experience and Layout on Learning from Text and Pictures with or without Unnecessary Picture Descriptions
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Rop, Gertjan; Schüler, Anne; Verkoeijen, Peter P. J. L.; Scheiter, Katharina; van Gog, Tamara – Journal of Computer Assisted Learning, 2018
The presentation of extraneous (i.e., irrelevant or unnecessary) information may hamper learning with multimedia. The present study examined whether people can learn to ignore unnecessary information with increasing experience with the task and whether this depends on the layout of that information. In two experiments, participants learned about…
Descriptors: Multimedia Instruction, Teaching Methods, Learning Processes, Layout (Publications)