The DOI matches its Crossref record; 45 of the 48 references it cites were found in a registry or an index.
Effects of artificial intelligence-enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom
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In the citing paper
“AI-enabled recommendation agents can facilitate content personalization in videos to increase engagement and improve learning outcomes [153].”
From Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis (2024) · cites this paper as [153]
In the citing paper
“The integration of biofeedback mechanisms, which track and react to the physiological states of the learners, will enable personalized instruction strategies and improve their engagement and performance [153].”
From Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis (2024) · cites this paper as [153]
In the citing paper
“The integration of chatbots to eliminate learning anxiety has shown significant promise in most studies ([28,46,47]).”
In the citing paper
“These studies revealed that AI-based conversational chatbots significantly improved EFL learners’ engagement.”
Citations
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Metadata
- Authors
- Huang, A. Y. Q., Lu, O. H. T., & Yang, S. J. H.
- Affiliations
- National Central University (TW)
- National Chengchi University (TW)
- Corresponding author
- Yang, Stephen J.H.
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2023-03
- Volume
- 194
- Pages
- 104684
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W4310249545
- Cited by
- 605
- References
- 48
- Citations by year
- 2026: 149 · 2025: 233 · 2024: 171 · 2023: 47
- FWCI
- 87.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Computers & Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Education › Innovative Teaching Methods
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Keywords
- flipped classroom, recommender systems, artificial intelligence in education, student engagement, student motivation, learning outcomes, learning management system data, student learning performance
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