Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom

Anna Y.Q. Huang, Owen H.T. Lu, Stephen J.H. Yang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The flipped classroom approach is aimed at improving learning outcomes by promoting learning motivation and engagement. Recommendation systems can also be used to improve learning outcomes. With the rapid development of artificial intelligence (AI) technology, various systems have been developed to facilitate student learning. Accordingly, we applied AI-enabled personalized video recommendations to stimulate students' learning motivation and engagement during a systems programming course in a flipped classroom setting. We assigned students to control and experimental groups comprising 59 and 43 college students, respectively. The students in both groups received flipped classroom instruction, but only those in the experimental group received AI-enabled personalized video recommendations. We quantitatively measured students’ engagement based on their learning profiles in a learning management system. The results revealed that the AI-enabled personalized video recommendations could significantly improve the learning performance and engagement of students with a moderate motivation level.

Original languageEnglish
Article number104684
JournalComputers and Education
Volume194
DOIs
StatePublished - Mar 2023

Keywords

  • Data science applications in education
  • Distance education and online learning
  • Improving classroom teaching

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