Conference Session

ASEE TUESDAY PLENARY FEATURING BEST PAPERS & INDUSTRY DAY SPEAKER Sponsored by University of South Florida & University of Maryland

Collection

2019 ASEE Annual Conference & Exposition

Authors

Abisola Coretta Kusimo, Stanford University ; Marissa Elena Thompson, Stanford University ; Sara A. Atwood, Elizabethtown College; Sheri Sheppard, Stanford University

Tagged Topics

ASEE Board of Directors, Corporate Member Council

) was assessed with a 5-item self-report measure for anETSE Instrument which is defined as an individual’s belief in their ability to successfullyperform technical engineering tasks. The technical engineering tasks probed by the survey weremotivated by engineering and career outcomes in previous work [5]. The process of adapting theitems and selecting a representative five-item set from a more exhaustive list using factoranalysis is described in detail elsewhere [6-7]. This instrument asked participants "How confidentare you in your ability to do each of the following at this time?" The items on the survey wereranked on a 5-point Likert scale from 0 to 4 with five response options labeled: (0) not confident,(1) slightly confident, (2

Conference Session

ASEE TUESDAY PLENARY FEATURING BEST PAPERS & INDUSTRY DAY SPEAKER Sponsored by University of South Florida & University of Maryland

Collection

2019 ASEE Annual Conference & Exposition

Authors

Sadan Kulturel-Konak, Pennsylvania State University, Berks Campus

Tagged Topics

ASEE Board of Directors, Corporate Member Council

), Junior (njr = 154), and Senior (nsr = 146). Byexamining the development level within students’ class standing groups (freshman to senior), onecan gauge whether students over time perform at higher rates than previous years. Ideally, to testgains across a given span of time, data is collected longitudinally, tracking an individual acrosstheir college career. Because we assume that regardless of student ability and demographicbackground, as whole, students will have higher learning gains as they progress through theengineering program, we assert that by aggregating and averaging out values over different classstanding groups can provide insights similar to that of a longitudinal study.Figures 1 and 2, where average scores are examined across