Validating theta power as an objective measure of cognitive load in educational video

Castro-Meneses, Leidy J.; Kruger, Jan‐Louis; Doherty, Stephen

doi:10.1007/s11423-019-09681-4

Cited by 53 publications

(40 citation statements)

References 57 publications

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“…Korbach et al (2020) provided an example of using eye‐tracking to investigate effects of pointing and tracing while learning from expository text and diagrams; while pointing and tracing was not associated with intrinsic and extraneous cognitive load self‐reports, eye‐tracking data revealed significant shifts in visual attention as well as deeper information processing. Kruger and Doherty (2016) have argued both intrinsic and extraneous cognitive load should be triangulated across “offline” self‐report measures collected alongside “online” pupillometric measures (e.g., averaged mean fixation duration, average fixation count, blink rate and blink latency) and electroencephalographic measures (e.g., alpha and theta power; see Castro‐Meneses, Kruger, & Doherty, 2020). Such studies may, however, present some interpretive challenges, as data from both pupillometry and electroencephalography are prone to movement artefacts that will need to be interpreted in the light of task‐relevant tracing actions as opposed to other task‐irrelevant movements.…”

Section: Discussionmentioning

confidence: 99%

“…More generally, systematically varying the level of element interactivity of lesson materials in the same experiment would support investigation of the extent to which the tracing effect is moderated by this key cognitive load theory construct (Sweller, 2010). extraneous cognitive load should be triangulated across "offline" selfreport measures collected alongside "online" pupillometric measures (e.g., averaged mean fixation duration, average fixation count, blink rate and blink latency) and electroencephalographic measures (e.g., alpha and theta power; see Castro-Meneses, Kruger, & Doherty, 2020). Such studies may, however, present some interpretive challenges, as data from both pupillometry and electroencephalography are prone to movement artefacts that will need to be interpreted in the light of task-relevant tracing actions as opposed to other task-irrelevant movements.…”

Section: Test Phasementioning

confidence: 97%

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Tracing enhances problem‐solving transfer, but without effects on intrinsic or extraneous cognitive load

Ginns

Bobis

2020

Applied Cognitive Psychology

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People can make pointing gestures and tracing actions with the index finger with little or no conscious effort. From the perspective of cognitive load theory, such "biologically primary" gestures and actions might help people learn "biologically secondary" concepts and skills requiring extended cognitive effort, such as reading, science, or mathematics. Studies on tracing or tracing and pointing have yielded mixed findings regarding hypothesized effects on intrinsic and extraneous cognitive load. The present study investigated whether computer-based instructions to trace elements of worked examples on angle relationships would affect school students' (N = 106) self-reports of intrinsic and extraneous cognitive load, as well as problemsolving transfer test performance. The tracing effect on transfer posttests seen in prior studies was replicated, but cognitive load hypotheses were not supported.

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Section: Discussionmentioning

confidence: 99%

Section: Test Phasementioning

confidence: 97%

Tracing enhances problem‐solving transfer, but without effects on intrinsic or extraneous cognitive load

Ginns

Bobis

2020

Applied Cognitive Psychology

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“…Importantly, the link between theta power and memory and the link between alpha power and attention, are more evident in some regions than others. The link between theta oscillations and memory is most prominent in the frontal and central regions (Castro‐Meneses, Kruger, & Doherty, 2020; Wang, Antonenko, Keil, & Dawson, 2020), whereas the link between alpha oscillations and attention is most pronounced in the occipital and parietal regions (Jensen, Gelfand, Kounios, & Lisman, 2002; Whitmarsh, Oostenveld, Almeida, & Lundqvist, 2017).…”

Section: Introductionmentioning

confidence: 99%

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

Pi¹,

Zhang²,

Zhou³

et al. 2020

Brit J Educational Tech

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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.

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“…There is no unique EEG feature that is directly related to cognitive load. Theta power has been suggested as an indicator for the average cognitive load of subjects and the linguistic complexity of educational videos (Castro-Meneses et al, 2019). Mu rhythm oscillations (8 − 13 Hz over the sensorimotor cortex) could be affected by the cognitive load during speech perception due to attention and working memory processes (Jenson et al, 2019).…”

Section: Eeg-pc Scores Related To Task Difficulty-based Cognitive Loadmentioning

confidence: 99%

EEG Correlates of Learning From Speech Presented in Environmental Noise

et al. 2020

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Validating theta power as an objective measure of cognitive load in educational video

Cited by 53 publications

References 57 publications

Tracing enhances problem‐solving transfer, but without effects on intrinsic or extraneous cognitive load

Tracing enhances problem‐solving transfer, but without effects on intrinsic or extraneous cognitive load

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

EEG Correlates of Learning From Speech Presented in Environmental Noise

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