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
Cites
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Content-Based Recommendation Systems
Pazzani, M. J., & Billsus, D. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-72079-9_10 · Cited by 2,600
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Vision, challenges, roles and research issues of Artificial Intelligence in Education
Hwang, G.-J., Xie, H., Wah, B. W., & Gašević, D. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100001 · Cited by 1,435
Recommendation systems: Principles, methods and evaluation
Isinkaye, F. O., Folajimi, Y. O., & Ojokoh, B. A. (2015) · Egyptian Informatics Journal · doi:10.1016/j.eij.2015.06.005 · Cited by 1,328
Mining LMS data to develop an “early warning system” for educators: A proof of concept
Macfadyen, L. P., & Dawson, S. (2010) · Computers & Education · doi:10.1016/j.compedu.2009.09.008 · Cited by 1,045
Measuring student engagement in technology-mediated learning: A review
Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015) · Computers & Education · doi:10.1016/j.compedu.2015.09.005 · Cited by 1,010
Hwang, G., & Chang, H.-F. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.12.002 · Cited by 842
Intelligent tutoring systems and learning outcomes: A meta-analysis
Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014) · Journal of Educational Psychology · doi:10.1037/a0037123 · Cited by 840
Research works printed but not linked: 1
- Huang, 2016, Effects of situated mobile learning approach on learning motivation and performance of EFL students, Journal of Educational Technology & Society, 19, 263
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Pembelajaran membaca bahasa indonesia di era digital: persepsi siswa Sekolah Menengah Pertama
Putri, T. K. W., Suryaman, M., Dianastiti, F. E., & Safitri, R. N. (2026) · Jurnal Genre (Bahasa Sastra dan Pembelajarannya) · doi:10.26555/jg.v8i2.16832
Perceptions of AI-assisted learning and learner development among Moroccan secondary school students
Kandirou, R., Youssfi, S. E., Atlassi, M. E., Dahman, A., & Hammoumi, M. M. E. (2026) · Discover Education · doi:10.1007/s44217-026-02109-1
A THEORETICAL FRAMEWORK FOR AI-ENHANCED METACOGNITIVE REGULATION IN ACTIVE LEARNING ENVIRONMENTS
Chirinos, R. A. G., Salazar, D. A. T., de la Vega, I. L. E., Choque, A. R. Q., Paricahua, E. W. P., & Churata, J. M. P. (2026) · Acta Innovations · doi:10.62441/actainnovations.v60i.786
Chumak, R. (2026) · International Russian Automation Conference (RusAutoCon) · doi:10.1109/rusautocon69876.2026.11707435
Shi, J., Jamaludin, K. A., & Ismail, H. H. (2026) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v20i18.59573
Hoerudin, C. W., Susanto, S., Ritonga, A. W., Desrani, A., Hude, D., Zamani, D. A., & Masyhuri, A. A. (2026) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v15.i5.pp4001-4014
Chang, Y. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2026.2748336
Zeng, R., 雷春涛, Jiang, Q., Gan, X., Zhang, X., Feng, Y., Xu, Q., Huang, Y., & Qian, Y. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1907218
AI-Driven Educational Innovation
Patil, D. S. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8740-6.ch003
Li, Z., Sitthiworachart, J., & Joy, M. S. (2026) · International Journal of Information and Education Technology · doi:10.18178/ijiet.2026.16.10.2720
Ascencio-Laguna, J. A., González-Lorence, A., Pérez, V. A. G., Mondragón-Solís, A. L., Soto-Osornio, J. E., & Silva, A. J. (2026) · Applied Sciences · doi:10.3390/app162010326
Smart questioning, answering, and clarifying to support adaptive learning
Nguyen, Q.-V., Sun, M.-T., Hwang, W., & Cao, T.-N. (2026) · Data Technologies and Applications · doi:10.1108/dta-02-2026-0223
Majid, I. J., Cahayawan, B. A., Nandika, I. R., Pratama, D. S., & Astuti, A. T. (2026) · Jendela Olahraga · doi:10.26877/jo.v11i04.743
Cranzo, A. G., Arnado, M. O., & Arnado, A. A. (2026) · International STEM Education Conference (iSTEM-Ed) · doi:10.1109/istem-ed69857.2026.11734337
Da, N. T., HÀ, G. T. T., & Nguyen, T. T. (2026) · International Journal of Education in Mathematics Science and Technology · doi:10.46328/ijemst.5812
Nguyen, N.-T., Tran, N.-K. H., Pham, K.-M. N., & Duong, N.-H. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2026.108061
Puentes digitales: la comprensión lectora en tiempos de inteligencia artificial
Olivares, H. R. D. L. C., & Quintana, A. L. B. (2026) · Revista Tribunal · doi:10.59659/revistatribunal.v6i17.578
A Meta-Analysis of the Effect of AI Use on English Learner Engagement
Lü, X., Peng, Y., & Lei, Y. (2026) · Language Teaching Research · doi:10.1177/13621688261498089
Untitled work
Chan, C. K. Y., Lo, N., & Wong, G. (2024)
How Students Use AI Feedback Matters: Experimental Evidence on Physics Achievement and Autonomy
Dai, X., Wen, Z., Jiang, J., Liu, H., & Zhang, Y. (2025) · arXiv · doi:10.48550/arxiv.2505.08672 · Cited by 2
“In a flipped classroom context, Huang et al. (2023) applied AI-enabled personalized video recommendations for 43 college students studying systems programming and compared their outcomes with 59 control participants; results indicated that personalized recommendations significantly enhanced…”
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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