The DOI matches its Crossref record; 53 of the 54 references it cites were found in a registry or an index.
Using chatbots to support student goal setting and social presence in fully online activities: learner engagement and perceptions
Open accessAbstract
Although fully online learning is now the 'new normal' in many parts of the world, its implementation is often beset by challenges such as the lack of student self-regulation, and the sense of isolation. In this paper, we explored the use of chatbots to support student goal setting (Study 1) and social presence (Study 2) in online activities. In Study 1, participants in a fully online course were invited to complete a goal setting activity prior to attending class via a goal-setting chatbot. The chatbot engaged participants with five questions developed based on the SMART (specific, measurable, achievable, realistic, and timely) goal setting framework. In Study 2, English-as-Foreign-Language participants in a fully online course were tasked to complete listening practices. The learning buddy chatbot was designed based on the social presence framework (interpersonal communication, open communication, cohesive communication) to guide students through listening exercises. In both Study 1 and 2, we evaluated participants' behavioral engagement by measuring their conversation records with the chatbots, as well as participants' perceived usefulness and ease of use of the chatbots. We also gathered in-depth interview data concerning the participants' perceptions of interacting with the chatbots. Overall, our findings found positive learner experiences with both chatbots with regard to the chatbots' perceived usefulness and perceived ease of use. We also provided suggestions for instructors to apply chatbots in teaching and learning.
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Students’ voices on generative AI: perceptions, benefits, and challenges in higher education
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Jeon, J., & Lee, S. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11834-1 · Cited by 696
“…more complex structures designed by commercial developers for language learning (e.g., Wang et al., 2023), and (3) customized chatbots created by researchers or teachers for particular language learning contexts using visual chat-bot development platforms (e.g., Hew et al., 2023; Lee & Jeon, 2022).”
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Using AI-driven chatbots to foster Chinese EFL students’ academic engagement: An intervention study
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Metadata
- Authors
- Hew, K. F., Huang, W., Du, J., & Jia, C.
- Affiliations
- University of Hong Kong (HK)
- Zhejiang University (CN)
- Corresponding author
- Hew, Khe Foon
- Venue
- Journal of Computing in Higher Education
- Published
- 2022-09-09
- Volume
- 35
- Issue
- 1
- Pages
- 40-68
- ISSN
- 1042-1726 (ISSN-L)
- 1867-1233
- PMC
- PMC9458299
- OpenAlex
- W4295753326
- Cited by
- 245
- References
- 54
- Citations by year
- 2026: 53 · 2025: 89 · 2024: 59 · 2023: 43 · 2022: 1
- FWCI
- 15.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Computing in Higher Education (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Hong Kong (Teaching Development Grant)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Education › Online and Blended Learning
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- chatbots, student goal setting, social presence, fully online learning, student engagement, student self-regulation, learner isolation, SMART goals, English as a foreign language, listening practices, perceived usefulness, perceived ease of use, learner perceptions
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