Assessment

Hybrid Teaching vs. Traditional Teaching in Computer Engineering Courses: What works and What does not work?

Authors
  • Andy S. Peng (University of Wisconsin - Stout)
  • Robert Nelson (University of Wisconsin - Stout)
  • Cheng Liu (University of Wisconsin - Stout)
  • Jai-Ling LIn (University of Minnesota)
  • Lynn M. Meredith (Thomas Reuters)

Abstract

This study compares student learning outcomes from two instructional approaches: hybrid vs. traditional teaching method. The study applies a previously developed framework in order to assess the learned curriculum for the same upper division computer engineering course. It also analyzes how it is aligned with the intended curriculum. The same undergraduate computer engineering course was taught by two different instructors during two different semesters. Both instructors have extensive technical background and many years of practical engineering experiences in the related field. Both classes used an identical textbook, delivered similar set of course topics, had similar lab setup, required homework assignments as well as a semester-long team project. The key difference is the use of online lectures. Based on students’ responses to series of surveys and the result of final grades, this study compares their development in content knowledge and cognitive abilities to determine the effectiveness of the instructional approach. The study provides an interest in finding ways to truly utilize technology for improving student learning, particularly their development of cognitive abilities. The study also seeks the impact of the technology on lecturing styles and in-classroom dynamics. Furthermore, this study will help gain insights into instructional approaches concerning teaching and learning along the technological dimension.

How to Cite:

Peng, A. S. & Nelson, R. & Liu, C. & LIn, J. & Meredith, L. M., (2014) “Hybrid Teaching vs. Traditional Teaching in Computer Engineering Courses: What works and What does not work?”, 2014 ASEE North Midwest Section Conference 2014(1), 1-6. doi: https://doi.org/10.17077/aseenmw2014.1047

Rights: Copyright © 2014, Andy S. Peng, Robert Nelson, Cheng Liu, Jai-Ling Lin, and Lynn M. Meredith

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Published on
17 Oct 2014
Peer Reviewed