Abstract
Video is becoming a dominant medium for the delivery of educational material. Despite the widespread use of video for learning, there is still a lack of understanding about how best to help people learn in this medium. This study demonstrates the use of thermal camera as compared to traditional self-reported methods for assessing learners' cognitive load while watching video lectures of different styles. We evaluated our approach in a study with 78 university students viewing two variants of short video lectures on two different topics. To incorporate subjective measures, the students reported on mental effort, interest, prior knowledge, confidence, and challenge. Moreover, through a physical slider device, the students could continuously report on their perceived level of difficulty. Lastly, we used thermal sensor as an additional indicator of students' level of difficulty and associated cognitive load. This was achieved through, continuous real-time monitoring of students by using a thermal imaging camera. This study aims to address the following: firstly, to analyze if video styles differ in terms of the associated cognitive load. Secondly, to assess the effects of cognitive load on learning outcomes; could an increase in the cognitive load be associated with poorer learning outcomes? Third, to see if there is a match between students' perceived difficulty levels and a biological indicator. The results suggest that thermal imaging could be an effective tool to assess learners' cognitive load, and an increased cognitive load could lead to poorer performance. Moreover, in terms of the lecture styles, the animated video lectures appear to be a better tool than the text-only lectures (in the content areas tested here). The results of this study may guide future works on effective video designs, especially those that consider the cognitive load.
Original language | English |
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Title of host publication | LAK 2020 Conference Proceedings |
Editors | Maren Scheffel, Vitomir Kovanović, Niels Pinkwart, Katrien Verbert |
Place of Publication | New York NY USA |
Publisher | Association for Computing Machinery (ACM) |
Pages | 250-259 |
Number of pages | 10 |
ISBN (Electronic) | 9781450377126 |
DOIs | |
Publication status | Published - 2020 |
Externally published | Yes |
Event | International Learning Analytics & Knowledge Conference 2020 - Frankfurt, Germany Duration: 23 Mar 2020 → 27 Mar 2020 Conference number: 10th https://lak20.solaresearch.org (Website) https://dl-acm-org.ezproxy.lib.monash.edu.au/doi/proceedings/10.1145/3375462 (Website) |
Conference
Conference | International Learning Analytics & Knowledge Conference 2020 |
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Abbreviated title | LAK 2020 |
Country/Territory | Germany |
City | Frankfurt |
Period | 23/03/20 → 27/03/20 |
Internet address |
Keywords
- Cognitive load
- Instructional design
- Thermal Imaging
- Video lectures