Katharina Scheiter

Universität Tübingen, Germany

Self-regulated learning from multiple representations: Using eye-tracking to uncover and support students’ processing in online learning environments

Many students show maladaptive study behaviours when learning in online environments that contain multiple representations (e.g., text, diagrams, animations). Rather than studying all representations in a balanced fashion and integrating the information extracted from them into a coherent mental model, students often focus on only of the representations (usually the text) at the expense of other representations as revealed by eye tracking studies. In the research conducted in my lab we consider this observation as an indication of students’ problems in self-regulating their learning in that they pick inadequate processing strategies or implement them in unsuited situations. In my presentation, I will report on studies in which we addressed these problems by instructional interventions aimed at improving students’ use of processing strategies. In a first set of studies, we asked students to internalize implementation intentions (i.e., if-then plans to apply certain processing strategies once a suitable opportunity arises) prior to studying multimedia materials. These implementation intentions not only fostered learning outcomes; in addition, they changed students’ processing behaviour in the expected ways and these changes explained the effectiveness of the intervention. In another set of studies, we modelled an effective use of learning strategies by showing students a video with the eye movements of a successful learner superimposed onto the learning materials. Students who watched the video-based modeling outperformed students receiving no strategy instruction, an effect that could be explained by more attention being allocated to the processing of the diagram of the prior students compared with the latter. A follow-up study revealed that the video-based modeling was effective only if students were told that these eye movements were recorded from another (regular) learner rather than telling them that the eye movements were those of an expert. These findings in line with social learning theory suggest that effects of modeling depend on the perceived distance between the learner and the model. Taken together, these findings suggest that eye tracking serves as a useful tool in uncovering students’ learning processes as well as in designing interventions aimed at improving their learning.

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