Minneapolis, MN
August 23, 2022
June 26, 2022
June 29, 2022
14
10.18260/1-2--41126
https://strategy.asee.org/41126
250
Danielle Dickson received her PhD from the University of Illinois at Urbana-Champaign in 2016 with a dissertation examining the memory system’s representation of numerical information, using behavioral and electro-physiological (EEG, brainwaves) measures. She extended this work into comparisons of children and adults’ arithmetic processing as a postdoctoral scholar at The University of Texas San Antonio. Her most recent research examines creative thinking processes as an area of postdoctoral research at The Pennsylvania State University.
Elif Elçin Günay is an assistant professor in the Department of Industrial Engineering at Sakarya University, Turkey. She received her B.S.E., M.S.E., and Ph.D. degrees in Industrial Engineering from Sakarya University, Turkey, in 2007, 2009, and 2016 respectively. She worked in the Department of Industrial and Manufacturing Systems Engineering at Iowa State University as a post-doctoral research associate between 2017-2018. Her research interest includes optimization in manufacturing and service systems, stochastic processes, and engineering education. Her recent research interests focus on enhancing creativity in engineering classrooms.
Zahed Siddique is a Professor in the School of Aerospace and Mechanical Engineering at the University of Oklahoma.
Measuring an individual’s creativity typically relies on labor-intensive subjective ratings of the quality of ideas and solutions to problems. In the Alternate Uses Task (AUT), frequently used in engineering design education for concept generation and to gauge creative function-object relationships, participants generate as many novel uses of everyday objects as possible within a given time frame. Unfortunately, objective and rapid evaluation of AUT responses for levels of originality and usefulness is difficult. Recently, an automatized method for generating scores has been developed, the freely accessible Semantic Distance (SemDis) tool [1]. Given the linguistic and cultural diversity of engineering students in the U.S., it seems fair to question how well this type of automatic rating system, based on prototypical language models, captures the creativity of engineering students who may be nonnative speakers of English. We extensively trained human raters to score the AUT responses of multilingual engineering students living in either a non-English environment or in the US, and the AUT responses of monolingual English engineering students. We found that the human ratings of all three groups of engineering students correlated strongly, and positively, with the automatic SemDis ratings. This forms proof of concept for using automatic rating systems such as SemDis in engineering classroom settings. In addition to saving evaluators’ time, this method may also be preferred because it is unbiased to cultural and linguistic features of responders’ answers that might reveal their gender, race, ethnic or linguistic background information.
Dickson, D., & Jonczyk, R., & Gunay, E., & Van Hell, J., & Siddique, Z. (2022, August), Utilization of Automatized Creativity Ratings in Linguistically Diverse Populations: Automated Scores Align with Human Ratings Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41126
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