Pedagogical agents in learning videos: Which one is best for children?

ABSTRACT

An increasing number of MOOCs use learning videos featuring an instructor and slides, but there are few specific guidelines for the design of instructor images for these videos. A pedagogical agent (PA) is a kind of virtual instructor image in a learning video, and its image design is mostly guided by anthropomorphism. Our research attempts to introduce zoomorphism, which is the opposite of traditional anthropomorphism, into the image design of PA. This study tested the effects of two different types of PA images (i.e. anthropomorphic and zoomorphic) as well as a control condition of no PA image on learning from a learning video in a sample of 94 s-grade children. The children were randomly assigned to watch one of three learning videos on pandas. The ANOVA and Kruskal–Wallis tests showed that children who watched the zoomorphic PA image video obtained significantly higher retention, transfer, learning interest, and experience than children who watched the other two types of videos. Children self-reported more enjoyment in the zoomorphic PA image condition than in the no PA condition. Furthermore, the results of multiple regression analysis showed that children’s learning interest and experience positively predicted retention and transfer scores; boredom negatively predicted transfer scores. These findings highlight the positive effect of zoomorphism on PA image design, suggesting that zoomorphism holds great prospects in PA image development.

KEYWORDS:

• Pedagogical agent
• Image design
• Zoomorphism
• Learning outcomes
• Learning interest
• Learning experience

Data availability statement

The data used to support the findings of this study are available from the corresponding author upon request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the undergraduate teaching reform project of Sichuan Normal University (2021), construction of first-class undergraduate courses, the methods of educational technology research [20210304XKC]; the school-level project of Sichuan Normal University (2022), research on the image design of pedagogical agent and its cognitive mechanism on learning [22XW070]; natural science foundation of Sichuan rovince, research on key techniques of machine understanding of deaf sign language by integrating knowledge and multi-modal semantic analysis [2022NSFSC0570]; and national natural science foundation of china, research on the contagion, evolution, and countermeasures of panic in the face of emergency evacuation of significant emergencies [72204180].

Notes on contributors

Bin Jing

Bin Jing is a postgraduate student in the School of Computer Science at Sichuan Normal University (SICNU). His research interests include pedagogical agent and learning video.

Jinrong Liu

Jinrong Liu is a postgraduate student in the School of Computer Science at Sichuan Normal University (SICNU). Her research interest is learning video.

Xue Gong

Xue gong is a postgraduate student in the School of Computer Science at Sichuan Normal University (SICNU). Her research interests are learning video and peer assessment.

Yangli Zhang

Yangli Zhang is an associate professor in the School of Computer Science at Sichuan Normal University (SICNU). His research interests include education informatization and information technology education (ITE).

Haojie Wang

Haojie Wang is an experimentalist in the School of Computer Science at Sichuan Normal University (SICNU). Her research interest is instructional design.

Changcheng Wu

Changcheng Wu is an associate professor and Ph.D. in the School of Computer Science at Sichuan Normal University (SICNU). His research interests include video course development and design, peer assessment, and teaching reform supported by information technology.