Master of Science, University of Toledo, 2021, Chemical Engineering
Interactive textbooks generate big data through student reading participation, including animations, question sets, and auto-graded homework. Here, animations are multi-step, dynamic visuals with text captions where records of students' clicks confirm usage and view time. These multi-step animations divide new content into small chunks of information that engage the student, require attentiveness and interaction, and align with tenets of cognitive load theory.
Animation usage data from an interactive textbook for a chemical engineering course in Material and Energy Balances (MEB) is studied. This thesis uses MEB zyBook data collected across five cohorts between 2016 and 2020. Two metrics capture animation usage: 1) fraction of students watching and re-watching animations, 2) length of animation views. In addition to variation across content, parsed by book chapter, five animation characterizations investigate student usage for different types of visuals (Concept, Derivation, Figures and Plots, Physical World, and Spreadsheets). In addition, pre- and post-surveys for one cohort in 2021 assessed students' attitudes about engineering and animations.
The three important findings of the animation view data are 1) student animation usage is very close to or greater than 100% for all chapters, 2) median view time varies from 22 s for 2-step animations to 59 s for 6-step animations - a reasonable attention span for students' cognitive load, 3) Median watch time by characterization ranged from 40 s for Derivation to 20 s for Physical World. Finally, student attitudes about engineering and animations found small, positive shifts that were not statistically significant between pre and post surveys.
Committee: Matthew Liberatore (Advisor)
Subjects: Adult Education; Chemical Engineering; Educational Technology