Learning by explaining to oneself and a peer enhances learners’ theta and alpha oscillations while watching video lectures

Abstract

In the present study, we tested the effectiveness of three learning strategies (self‐explanation, learning by teaching and passive viewing) used by students who were learning from video lectures. Effectiveness was measured not only with traditional measures, but also with electroencephalography (EEG). Using a within‐subjects design, 26 university students viewed three sets of short lectures, each presenting a different set of English vocabulary words and were asked to use a different learning strategy for each set of lectures. Participants’ EEG signals were assessed while watching the videos; learning experience (self‐reported motivation and engagement) and learning performance (vocabulary recall test score) were assessed after watching the videos. Repeated measures ANOVAs showed that the self‐explaining and teaching strategies were more beneficial than the passive viewing strategy, as indicated by higher EEG theta and alpha band power, a more positive learning experience (higher motivation and engagement) and better learning performance. However, whereas the teaching strategy elicited greater neural oscillations related to working memory and attention compared to the self‐explanation strategy, the two groups did not differ on self‐reported learning experience or learning performance. Our findings are discussed in terms of potential application in courses using video lectures and in terms of their heuristic value for future research on the neural processes that differentiate learning strategies. What is already known about this topic Watching video lectures does not always result in learners actively making sense of the learning material. Self‐explaining facilitates deep learning from viewing video lectures and in traditional educational settings. Learning by teaching also facilitates deep learning in traditional educational settings. What this paper adds Learning by teaching resulted in the highest theta and alpha band power in EEG assessment while viewing video lectures. Compared with passive viewing, learning by teaching enhanced students’ motivation to try to understand the material; in addition, both learning by teaching and self‐explaining enhanced the amount of mental effort students put into understanding the material. Learning was increased via both self‐explaining and teaching strategies after viewing video lectures. Implications for practice and/or policy Learners are encouraged to generate explanations during pauses in video lectures or after viewing them, in order to increase learning. Learners are also encouraged to learn by teaching, as this strategy can increase learning and also increase neural oscillations associated with memory and attention.

Impacts of Color Coding on Programming Learning in Multimedia Learning: Moving Toward a Multimodal Methodology

“…Neural oscillations in the alpha band are related to an increase in internal attention-demanding cognitive processing ( Klimesch, 2012 ; Fink and Benedek, 2014 ). Our study suggests that the color-coded group had a greater engagement of working memory and attention than the grayscale group, allowing information to be processed at a deeper level and thus resulting in better learning performance ( Pi et al, 2021 ).…”

“…The theta band is related to the working memory. The increases in theta oscillations are related to high working memory activity as well as successful memory encoding ( Miller et al, 2018 ) and retrieval ( Solomon et al, 2019 ; Pi et al, 2021 ). Therefore, deep processing of learning material in working memory can successfully encode memory ( Khader et al, 2010 ; Lin et al, 2017 ), and working memory maintenance can forecast long-term memory ( Hsieh and Ranganath, 2014 ).…”

“…The power of five standard EEG rhythms, i.e., delta (0.5–4 Hz), theta (5–8 Hz), alpha (9–12 Hz), beta (13–32 Hz), and gamma (33–50 Hz), were computed by averaging the spectral powers in the corresponding frequency bands ( Sghirripa et al, 2020 ; Pi et al, 2021 ). We slid the EEG data recorded in the experiment with a window size of 4 s to calculate the power of the five frequency bands corresponding to each window.…”

Learning-by-Teaching Without Audience Presence or Interaction: When and Why Does it Work?

“…However, recent research has shown that the learning-by-teaching effect also replicates in non-interactive settings (e.g., Fiorella & Mayer, 2013;Hoogerheide et al, 2014;Pi et al, 2021;Rittle-Johnson et al, 2008). Learning by non-interactive teaching entails studying learning materials and then teaching the material to an actual, remote, or imaginary audience, and lacks interaction with other students.…”

“…Any such examinations should preferably include (multiple) process measures. Recent studies did start to include process measures, such as arousal (Hoogerheide et al, 2019a;Pi et al, 2021), motivation (Hoogerheide, et al, 2019b;Jacob et al, 2021), or adaption processes Jacob et al, 2020a;Lachner et al, 2020). However, most studies only included a single process measure, making it difficult to compare the relative relevance and the interplay of different mechanisms.…”