2023 ASEE Annual Conference & Exposition

Interactive textbooks paired with online homework generate big data that can help answer questions about student engagement and learning. Here, a fully interactive textbook for a material and energy balances course measured over 1,300 reading interactions per student per cohort. In addition, several hundred auto-graded homework questions were assigned to students each semester. The auto-grading allowed for individual or class-level interventions to occur in real time and not after the next quiz or exam. In total, seven cohorts representing over 600 students and over 700,000 reading interactions are aggregated, which expands upon previous publications. For example, median reading participation was over 93% for all seven cohorts. In aggregate, female students completed reading participation at a higher rate than male students with statistical significance. Thus, applying some learning best practices including visuals and chunking in animations, immediate feedback in learning questions, and varying the interactive reading activities quantitatively engaged all learners, but showed even higher engagement with female students – an underrepresented group in engineering. Next, analytics from over 130,000 auto-graded problems are examined. Median correct of 91% or higher was found across six cohorts. Thus, allowing unlimited attempts on these formative problems allows students to persist in answering the randomized questions correctly. As with reading participation, female students completed a greater percentage of auto-graded problems than male students, however, statistical significance was not found for auto-graded problems. Overall, few articles in engineering education present data where an underrepresented group, female students in this case, outperform the majority group. While reasons for the differences are speculative at this point, we hope this contribution stimulates other qualitative and quantitative research on gender differences and educational technology.