Enhancing learner satisfaction through human-like digital instructors: an empirical study on the role of visual and verbal human likeness in e-learning
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Learning satisfaction serves as a subjective indicator for assessing the learning process and outcomes and more directly reflects learners' experiences and perceptions within GenAI-supported learning environments.
“learning satisfaction serves as a subjective indicator for assessing the learning process and outcomes. It more directly reflects learners’ experiences and perceptions within GenAI-supported learning environments”
From Exploring the factors influencing college students’ learning satisfaction in generative AI-supported MOOCs learning environment: a learning experience framework perspective (2025) · cites this paper as Chu, 2025
Cites
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.002 · Cited by 4,611 · cited 1× · see citing works
“The continuous advancements in Artificial Intelligence (AI) technology have led to its growing ability to simulate, and in some cases surpass, human capabilities in tasks such as judgment, classification, and creation (Dwivedi et al., 2021).”
Kim, J., Lee, H., & Cho, Y. H. (2022) · Education and Information Technologies · doi:10.1007/s10639-021-10831-6 · Cited by 669 · cited 2× · see citing works
“First, when developing educational content utilizing AI technology, it is essential to enhance the human likeness of digital human instructors (including both visual and verbal elements) to improve learner experience and satisfaction (Kim et al., 2022a).”
Digital support for student engagement in blended learning based on self-determination theory
Chiu, T. K. F. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106909 · Cited by 395 · see citing works
Amankwah-Amoah, J., Abdalla, S., Mogaji, E., Elbanna, A., & Dwivedi, Y. K. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2024.102759 · Cited by 305 · see citing works
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Lv, P., Wang, X., Nie, Y., Wu, R., & Wang, L. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1633686 · Cited by 5 · see citing works
“This provides a crucial complement to comprehensively evaluating the learning effectiveness of GenAI-supported MOOCs (Banihashem et al., 2023; Belkina et al., 2025; Chu, 2025; Sun et al., 2008; Wu et al., 2010; Zhang et al., 2024).”
- Authors
- Chu, L.
- Affiliations
- Xi'an Shiyou University (CN)
- Corresponding author
- Chu, Lianghai
- Venue
- Education and Information Technologies
- Published
- 2024-11-20
- Volume
- 30
- Issue
- 7
- Pages
- 8713-8731
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4404543745
- Cited by
- 15
- References
- 4
- Citations by year
- 2026: 8 · 2025: 6 · 2024: 1
- FWCI
- 7.12
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Education and Information Technologies (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Education › Online and Blended Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- human-likeness, student satisfaction, online learning, uncanny valley, experience economy, AI-generated avatars, educational videos, escapism, nonverbal communication, gender effects
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