This paper documents the author’s application of data-enabled flipped learning (DEFL), to enhance quality teaching in a differentiated instruction context. To cater for his module in the school of Mechanical & Aeronautical Engineering, he customized the Singapore Polytechnic (SP) generic model into his DEFL model of quiz (1st step), intervention (2nd step) and survey (3rd step).

Via learning analytics dashboards of SP’s learning management system, data from online diagnostic quizzes (1st step) enabled the author to implement differentiated instruction for his engineering students. Customized in-class interventions (2nd step) were enabled for three differentiated student categories, namely “OK”, “Not OK” and “At-Risk” students. These interventions involved pastoral care, supplementary lesson and in-class feedback provided by the author to students, guided by his evidence-based reflective practice (EBRP) checklist. The ten core principles of learning embedded in his EBRP checklist, coupled with its inherent evidence-based approach, was a structured template to quantify and enhance quality teaching. Lastly, online surveys (3rd step) via SP’s learning management system provided regular and timely student feedback, and enabled formative evaluation to lecturers.

Overall analysis of both qualitative and quantitative data collected from students (n=164) and lecturers (n=7) involved in the 3-semester pilot run largely supported the use of DEFL in pedagogy. Limitations were discussed under reflections, reminding lecturers of noteworthy points when performing DEFL. This paper concludes with a quote from Singapore Minister for Education’s public speech, demonstrating the fruitful implementation of DEFL in SP.

Authors:
Ying-Wei Leong, Singapore Polytechnic, Singapore

About the Presenter(s)
Mr Ying-Wei Leong is currently a Senior Lecturer and the Teaching & Learning Mentor in the School of Mechanical & Aeronautical Engineering, Singapore Polytechnic. He teaches engineering core modules and also supervises final year industry projects.

Connect on Linkedin
https://www.linkedin.com/in/ying-wei-leong

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