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Liu, D.Y.T., Bartimote-Aufflick, K., Pardo, A. and Bridgeman, A.J. (2017) Data-Driven Personalization of Student Learning Support in Higher Education. In: Peña-Ayala, A., Ed., Learning Analytics: Fundaments, Applications, and Trends, Springer, Cham, 143-169. https://doi.org/10.1007/978-3-319-52977-6_5

has been cited by the following article:

• TITLE: Integrating Learning Analytics into the Flipped Classroom: A Study on Data-Enabled Flipped Learning

  AUTHORS: Edwin Seng, Neo Chip Chuan

  KEYWORDS: Flipped Classroom, Learning Analytics, Data-Enabled Flipped Learning

  JOURNAL NAME: Open Access Library Journal, Vol.10 No.9, September 26, 2023

  ABSTRACT: The study explores the integration of Learning Analytics with the Flipped Classroom approach to improve student learning outcomes. The resultant Data-Enabled Flipped Learning (DEFL) model seeks to tackle challenges students face in comprehending and assimilating knowledge in a Business Analytics course. Educators can adapt teaching methods to individual student needs by strategically using pre-class surveys, in-class interventions, and post-class feedback. The efficacy of the DEFL model is shown via a quasi-experimental design, which highlights significant enhancements in students’ understanding of specific topics. Interestingly, students who initially assessed themselves lower showed notable improvement in performance. A comparison of cohort grades further reinforces the model’s capacity to elevate overall course outcomes. While recognising its constraints and proposing future refinements, the research emphasises DEFL’s potential to redefine contemporary education, providing educators with an effective instrument for tailored instruction and enhanced student achievements.