Minneapolis, MN
August 23, 2022
June 26, 2022
June 29, 2022
8
10.18260/1-2--41836
https://peer.asee.org/41836
341
Katie Basinger-Ellis is an Instructional Assistant Professor and the Undergraduate Program Coordinator at The University of Florida, in ISE. She obtained her Ph.D., M.S., and B.S. in ISE at North Carolina State University. Her research is focused on practical applications of active and supplemental learning techniques for Generation Z students
with a focus on content development.
Diego Alvarado is an Instructional Assistant Professor in the Department of Engineering Education at the University of Florida. He obtained his M.Eng. in Industrial Engineering from Texas A&M University and his B.S. in Industrial Engineering from Texas A&M University. His research interests involve engineering education research for video development to increase engagement and methods to teach artificial intelligence and machine learning in higher education.
Dr. Michelle Alvarado is an Assistant Professor at the University of Florida. She obtained her Ph.D. and M.Eng. in Industrial Engineering from Texas A&M University and her B.S. in Industrial Engineering from the University of Alabama. Dr. Alvarado is the Co-Founder and Co-Director of the HEALTH-Engine Laboratory. The aim of her engineering education research is to develop new methods and best practices of flipped classroom video development for simulation and programming courses to better fit the needs of Generation Z engineering students.
Online teaching is rapidly integrating into courses at all levels of learning. This wave of online education was coming with Generation - Z; however, the pandemic catapulted the movement of online learning in ways educators never thought possible. GenZ is the first truly digital native generation meaning they are excellent at engaging with multiple devices (5 or more) at a time, therefore simultaneously filtering "un-important" information. While this skill is a superpower in some situations, it is challenging to focus on a single device in an educational environment like an online lecture. Therefore, this work investigates using active learning in an online course to determine the effect on students' perceived and performance learning outcomes based on time of engagement with the material compared to traditional passive online videos. Active lectures require students to continually engage with the video via practice problems and immediately watch solutions for incorrect questions. This work compares two modules in an online engineering economy course. Students choose to opt into the active group or remain in the passive group. Perceived learning outcomes are measured based on responses to a survey in which students indicated their ability to apply topics in a real-world scenario. Performance learning outcomes are measured by a student's performance on the midterm exam. Since this is a work in progress with only one semester of data, we hypothesize that students in the active group will have a higher time of engagement with the material and, therefore, higher performance learning outcomes. There is no evidence to suggest that students have higher confidence in their knowledge (better-perceived learning outcomes) based on their group (active vs. passive). Audience: Anyone teaching an online course with mathematical content.
Basinger, K., & Ortega, A., & Alvarado, D., & Alvarado, M. (2022, August), The effect on perceived and performance learning outcomes from active online learning Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41836
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