Motivating Students to Learn AI Through Social Networking Sites: A Case Study in Hong Kong
Open accessAbstract
In Hong Kong, after-school activities have long been used to foster friendships and to allow students to pursue their interests in an informal setting. This case study reports on a three-phase action research process in which information technology teachers delivered after-school activities focused on artificial intelligence during the COVID-19 transition to remote learning. Using semi-structured interviews, a motivational questionnaire, and lesson observations, this study describes how extracurricular activities were delivered online using social networking sites and how students perceived the new experience. Our results suggest that, in order to deploy meaningful activities via social media, teachers need to build collaborative environments that facilitate social engagement among students. These findings have implications for new practices in social media and other blended technologies, and can help students strike a healthy balance between their academic and non-academic life during this challenging period.
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Social media can offer easy access to learning content, engagement with AI communities, networking opportunities, and current AI trends; however, the information may be fragmented, unlike when it is delivered via structured formal courses.
“Social media can offer easy access to learning content, engagement with AI communities, networking opportunities, and current AI trends; however, the information may be fragmented, unlike when it is delivered via structured formal courses [29].”
From Shaping the future: perspectives on the Integration of Artificial Intelligence in health profession education: a multi-country survey (2024) · cites this paper as [29]
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“Social media can offer easy access to learning content, engagement with AI communities, networking opportunities, and current AI trends; however, the information may be fragmented, unlike when it is delivered via structured formal courses [29].”
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- Authors
- Ng, T. K., & Chu, K. W.
- Venue
- Online Learning
- Publisher
- The Online Learning Consortium
- Published
- 2021-03-01
- Volume
- 25
- Issue
- 1
- ISSN
- 1092-8235 (ISSN-L)
- 2472-5730
- 2472-5749
- OpenAlex
- W3135828953
- Cited by
- 80
- References
- 46
- Citations by year
- 2026: 10 · 2025: 11 · 2024: 24 · 2023: 17 · 2022: 14 · 2021: 4
- FWCI
- 25.92
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Online Learning (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Education › Online and Blended Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Keywords
- artificial intelligence in education, student motivation, social networking sites, after-school activities, extracurricular activities, distance education, COVID-19 pandemic, information technology teachers, online collaboration, social engagement, blended learning, Hong Kong
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