Longitudinal Learning Outcomes from Engineering-Specific Adaptions of Hybrid Online Undergraduate Instruction

Authors

  • Ronald F. DeMara University of Central Florida
  • Tian Tian University of Central Florida
  • Wendy Howard University of Central Florida

DOI:

https://doi.org/10.3991/ijet.v16i23.17615

Keywords:

Mixed-Mode Delivery, STEM Instructional Frameworks, Modular Instructional Design, Virtualized Active Learning

Abstract


Hybrid online delivery, which is also referred to as mixed-mode delivery, utilizes a combination of online content and traditional face-to-face methods which may benefit significantly from specific delivery adaptations for undergraduate engi-neering curricula. Herein, a novel eight-step phased instructional flow with several targeted adaptations is used to accommodate the mixed-mode delivery of STEM curricula is evaluated with a longitudinal study of students afforded these adapta-tions versus those without them. This STEM Blended Delivery Protocol (STEM-BDP) emphasizes scaffolding of analytical procedures along with hands-on prob-lem solving throughout online and face-to-face components equally. Two high enrollment course case studies utilizing STEM-BDP are examined herein, includ-ing an Electrical and Computer Engineering required core undergraduate course and a Mechanical and Aerospace Engineering undergraduate course. The details of the STEM-BDP delivery strategies, learning activities, and student perceptions surveys are presented. Student-resolution longitudinal analysis within a controlled study using blinded evaluation indicates that over a five-year period, failure rates have decreased by 63% among students undergoing STEM-BDP while control and alternatives have not demonstrated similar improvements within the same degree programs. Given increasing enrollments within STEM curricula, it is sought to overcome challenges of conventional lecture-only delivery in high-enrollment courses.

Author Biographies

Ronald F. DeMara, University of Central Florida

Ronald F. DeMara is Pegasus Professor in the Department of Electrical and Computer Engineering, joint faculty of Computer Science, and the Digital Learning Faculty Fellow at the University of Central Florida, where he has been a full-time faculty member since 1993. His interests are in computer architecture, post-CMOS devices, and reconfigurable fabrics. He has applied these to autonomous, embedded, and intelligent/neuromorphic systems, on which he has completed over 300 articles, 50 funded projects as PI or Co-PI totaling $14.2M with one patent granted and one provisional patent, and 50 graduates as Ph.D. dissertation and/or M.S. thesis advisor. He was previously an Associate Engineer at IBM and a Visiting Research Scientist at NASA Ames, in total for four years, and is a registered Professional Engineer since 1992. He has served ten terms as a Topical Editor or Associate Editor including IEEE Transactions on Computers, Transactions on Emerging Topics in Computing, Transactions on VLSI, IEEE Spectrum, and Technical Program Committees of various IEEE conferences. He has been Keynote Speaker of IEEE RAW and IEEE ReConFig conferences, and Guest Editor of IEEE Transactions on Computers 2017 Special Section on Innovation in Reconfigurable Fabrics and 2019 Special Section on Non-Volatile Memories. He received the Joseph M. Biedenbach Outstanding Engineering Educator Award from IEEE.

Tian Tian, University of Central Florida

Tian Tian is an Associate Lecturer of Mechanical and Aerospace Engineering at the UCF, which she joined in 2013. She has been frequently teaching under-graduate lecture and laboratory components of Heat Transfer, Thermodynamics and Fluid Mechanics. Her educational research interests focus on project-based learning, online learning, and the digitization of STEM assessments. She received the Teaching Incentive Award, Excellence in Undergraduate Teaching Award, the Dean’s Advisory Board Faculty Fellow Award, Professor of the Year Award and Advisor of the Year Award.

Wendy Howard, University of Central Florida

Wendy Howard is the Program Director of the Pegasus Innovation Lab (iLab) at the University of Central Florida, which is an incubator of experimental projects focused on digital learning innovations that can be developed and refined through rapid prototyping and then promoted throughout the university to maximize col-lective impact on student success at scale. With over twenty years of experience in both instructional design and teaching, her current research is focused on faculty development, collaborative online learning and internationalizing the curriculum through technology.
Cover iJET Vol. 16 No. 23 (2021)

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Published

2021-12-08

How to Cite

DeMara, R. F., Tian, T., & Howard, W. (2021). Longitudinal Learning Outcomes from Engineering-Specific Adaptions of Hybrid Online Undergraduate Instruction. International Journal of Emerging Technologies in Learning (iJET), 16(23), pp. 171–201. https://doi.org/10.3991/ijet.v16i23.17615

Issue

Vol. 16 No. 23 (2021)

Section

Papers

License

Copyright (c) 2021 Ronald F DeMara, Tian Tian, Wendy Howard

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