2026 ASEE Annual Conference & Exposition

A Gateway to Educational Research: Development of a Toolkit to Make Statistical Analysis Accessible

Presented at Entrepreneurship & Engineering Innovation Division (ENT) Technical Session 3 -Social, Equity & Research Support Topics

Engineering education currently struggles to recruit technical engineering faculty to perform educational research in their classrooms. A few common barriers for technical engineering faculty in improving their classroom are access to introductory educational research tools, lack of time and energy to dedicate towards extracurricular activities, and lack of incentive to participate in and publish research. Many technical instructors tend to monitor the students’ success using grades (a measure of more technical skills), but there is a need to measure student impact beyond the technical. One method for conceptualizing these technical and non-technical skills is through entrepreneurially-minded learning (EML), a pedagogical approach to supporting the development of engineering students’ attitudes, habits, and behaviors. This paper details the development and testing of a statistical toolkit that any engineering instructor, regardless of their experience with statistics, can use to measure student development of an entrepreneurial mindset (EM). The completed resource will include three survey instruments (developed as part of an ongoing KEEN grant to measure EM using the 3Cs), an excel worksheet which automates introductory statistical analysis, and written documentation describing how to use the survey and worksheet with appropriate rigor. The documentation describes each step of the process, starting from deploying the survey in a classroom and ending with reporting results to a conference venue such as ASEE. The statistical toolkit is currently being designed and improved through think aloud sessions with graduate teaching assistants and teaching faculty at a large R1 university in the Midwest. The statistical toolkit currently walks users through descriptive statistics and a paired-sample t-test, with plans to incorporate an ANCOVA model using regression analyses for student learning gains. The development team aims to disseminate this statistical toolkit broadly via conference publications and workshops, hopefully creating a user-friendly gateway into the world of educational research.

Authors
  1. Dr. Connor Jenkins The Ohio State University [biography]
Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026