(379a) Quantifying Spreadsheet Skills Using an Interactive Textbook | AIChE

(379a) Quantifying Spreadsheet Skills Using an Interactive Textbook

Authors 

Liberatore, M. - Presenter, University of Toledo
Valentine, G., University of Toledo
While chemical engineering students and practicing chemical engineers use spreadsheets for completing calculations and many other tasks, learning, practicing, and retaining new spreadsheet skills can be difficult to document. For example, applying a spreadsheet formula for the first time could include demonstration by an expert on YouTube. Spreadsheet programs are easily accessible and have been available for many years, including Microsoft Excel and Google Sheets. While most spreadsheet tasks are the same across platform and application, training on a specific operating system and version is unnecessary. Thus, moving from training to more educational presentation of spreadsheet skills that apply broadly and are transferrable is possible with an interactive textbook. Here, an interactive textbook combines interactive reading content with the opportunity to practice spreadsheet skills through auto-graded problems. The interactive textbook applies learning theories, including cognitive load, scaffolding, and deliberate practice, to both engage and assess learners. First, reading participation is measured by clicks within animations, multiple-choice and true/false questions, and matching exercises. Next, students have unlimited attempts to correctly answer over 140 auto-graded, randomized problems. In addition to the basics of spreadsheeting, advanced topics include solver, error, statistics, and lookup functions. Five cohorts representing over 400 students were studied. Median reading participation was over 96% for all cohorts. In addition, animation view rates were as high as 118%. Animation view rates were highest for more advanced topics, such as double interpolation. High auto-graded problem completion was observed. Median completion over 94% for each cohort was measured. For example, the interpolation section had the lowest mean fraction correct and highest median attempts before correct. By examining fraction correct and attempts before correct at the individual section level, real-time misconceptions and struggle can be noted, which leads to opportunities to provide interventions and facilitate learning. Hypothesis testing and other statistical measures will be presented for both reading participation and auto-graded problems.