Minneapolis, MN
August 23, 2022
June 26, 2022
June 29, 2022
15
10.18260/1-2--40500
https://peer.asee.org/40500
329
Matthew W. Liberatore is a Professor in the Department of Chemical Engineering at the University of Toledo. He earned a B.S. degree from the University of Illinois at Chicago and M.S. and Ph.D. degrees from the University of Illinois at Urbana-Champaign, all in chemical engineering. From 2005 to 2015, he served on the faculty at the Colorado School of Mines. In 2018, he served as an Erskine Fellow at the University of Canterbury in New Zealand. His research involves the rheology of complex fluids, especially traditional and renewable energy fluids and materials, polymers, and colloids. His educational interests include developing problems from YouTube videos, active learning, learning analytics, and interactive textbooks. His interactive textbooks for Material and Energy Balances, Spreadsheets, and Thermodynamics are available from zyBooks.com. His website is: https://www.utoledo.edu/engineering/chemical-engineering/liberatore/
Kayla E. Chapman earned a B.S. degree in chemical engineering from the University of Toledo in December of 2021. She assisted with multiple areas of research and data analysis regarding zyBooks reading participation and challenge activities. She became interested in performing research after completing a chemical engineering course that used zyBooks. She currently works as a Process Engineer for The J.M. Smucker Company.
Interactive textbooks and online homework can uncover trends about student engagement and study practices. Here, auto-graded and randomized problems provided big data related to students’ proficiency in a chemical engineering course on material and energy balances. Previously, aggregating hundreds of problems from a fully interactive online textbook, Material and Energy Balances zyBook, found a median 94% correct. For two recent cohorts, new, summative, end-of-chapter auto-graded problems were assigned. While summative problems written by an expert author were examined in the 2021 ASEE proceedings, this contribution will focus on summative problems derived from student-written problems that reverse engineer actions in YouTube videos. Previous research found that student-written “YouTube problems” were equally rigorous and required similar problem-solving skills to expert-written textbook problems when examining hand-written solutions. Now, auto-graded YouTube problems within the zyBook are investigated for the first time. Students were required to complete a fraction of the total summative YouTube problems before each of three midterm exams. For a single cohort of ~80 students, responses to ~20,000 online homework problems were analyzed. Research questions included: 1. Do students correctly solve more YouTube problems than required?, 2. Does completing more YouTube problems correlate with higher exam scores?, 3. Do formative and summative auto-graded problems correlate differently with final course grades?, and 4. How does solving end-of-chapter YouTube problems compare to end-of-chapter textbook problems with respect to final course grades? First, a median fraction correct of 100% for required YouTube problems was found for all three midterm exams, which generally shows persistence as auto-graded problems have unlimited attempts before the due date. Students scoring above the median midterm exam score correctly completed statistically significantly more YouTube problems. Correctly completing more YouTube problems positively correlated with midterm exam grades for all three exams. Almost no difference between cohorts was observed when correlating final course grades with correctly completing end-of-chapter textbook or YouTube problems. Thus, student-written YouTube problems appear equivalent to expert-written homework problems in terms of student success.
Liberatore, M., & Chapman, K. (2022, August), Can I have More Problems to Practice? Part 2. Student Success Related to Auto-graded, End-of-chapter YouTube Problems in a Material and Energy Balances Course Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--40500
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