2026 ASEE Annual Conference & Exposition

The undergraduate laboratories in Energy Systems at our institution were recently reorganized to accommodate an increasing number of students without increasing the number of large-scale experimental equipment. During the course, groups of students take turns completing one of the six required experiments. Each experiment is completed within four class periods: the first class period is for data collection, the second and third class periods are dedicated to data processing and analysis, and the last class period is for reporting and assessment. The schedule requires that instructors are simultaneously working with groups who are in different phases of the experimental process. The new format has been mostly successful, but students told us they would like more time with instructors during class for help with the post-processing and data analysis phase.

Students must complete a pre-lab quiz individually before each experiment. The quizzes are intended to test students’ understanding of the preparatory material available on the course webpage. They were designed as an incentive to encourage students to review this material prior to coming to the labs. However, despite these quizzes, instructors find that many students come to the labs mostly unprepared. As a result, instructors often spend over half of the class time introducing experiments and reiterating content already available online, thus reducing the time available for helping students with data processing and analysis.

This work aims to evaluate why the combination of online preparatory material and pre-lab quizzes does not seem to be effective in ensuring students are well-prepared for laboratory sessions. The Work-In-Progress paper will review the literature on the use of pre-lab quizzes and other ways to incentivize student preparedness. It will also describe the framework in place for data collection. Data on students’ engagement with preparatory materials and pre-lab quizzes will be collected from the course’s Learning Management System during Spring 2026 and supplemented with student surveys. Results will be presented during the conference.
(If in MECH session, preferred format is Postcard)