Minneapolis, MN
August 23, 2022
June 26, 2022
June 29, 2022
11
10.18260/1-2--41563
https://peer.asee.org/41563
326
Dr. Dallal is an assistant professor at the department of electrical and computer engineering, Unversity of Pittsburgh, since August 2017. Dr. Dallal's primary focus is on education development and innovation. His research interests include biomedical signal processing, biomedical image analysis, computer vision, machine learning, networked control systems, and human-machine learning. Dr. Dallal's pedagogy and engineering research interests are on active learning, flipped classroom, problem-based learning, and collaborative learning.
The flipped classroom is a relatively new pedagogical approach for student-centric learning. It is ushering in a new cohort of active learners. With the transition to remote education due to COVID-19, the flipped instruction style gained more popularity among instructors. But, since both instructors and students developed a feeling of increased workload, the adoption rate of flipped instruction in engineering courses has been slow. Research before the pandemic suggests that student learning is likely to improve in the flipped setup compared to the traditional classroom. However, there is still a need for more comprehensive studies to investigate the effectiveness of flipped pedagogy. This work studies the students' performance and perception of partial flipping in three machine learning classes. The modules from the first half of the semester were taught in a traditional fashion, and the modules in the second half of the semester were flipped. All of the course modules are of comparable difficulty. Thus, to measure the effectiveness of flipped instructions, we compared the homework and test scores from the modules studied in the first half of the semester to those from the second half of the semester where the flipped approach was used. No statistical difference in the scores was observed between the flipped and non-flipped modules. Nonetheless, 90% of the survey responses indicated that the video lectures helped them achieve the intended learning outcomes of the flipped modules. Besides scores, we used online surveys to gather student feedback and measure their perception of flipped learning. Content analysis of the survey responses showed a positive perception of the flipped instructions and the complementary in-class activities and elevated participation in class discussions despite some students' resistance to flipped learning. Also, flipping introduced flexibility on how the students first encounter the course contents.
Dallal, A. (2022, August), Evaluation of Students Performance and Perception of Partial Flipping in Machine Learning Classes Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41563
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