June 15, 2019
June 15, 2019
June 19, 2019
Educational Research and Methods
The need for acquiring data analysis skills is nowadays ubiquitous to all professions. In engineering, this need has been recognized through elements such as the current ABET student outcome 3.b. which expect engineering graduates to have “an ability to design and conduct experiments, as well as to analyze and interpret data.” While this outcome is a requirement of engineering programs, the length and depth of the data analysis training of undergraduate students vary significantly across engineering majors. The evolution in the capacity to produce and storage data, requires an exploration of the status on data analysis training of engineers. We propose that such exploration can start through the research question: what data analysis training has been available and has been procured by engineering undergraduate students? In this work, we aim to answer this question through a mixed methods approach, in which the courses available to engineering students are first coded according to their data analysis content. A comprehensive database with the records of courses taken by engineer students between 1987 and 2011 at two public institutions is then used to generate profiles reflecting different levels of data analysis preparation that students have engaged with. Results from this study will provide the baseline for evaluating if the training of engineers is satisfying the demands of employers, especially as it relates to the expanding employment opportunities related to data analysis skills. Through the generation of profiles, similarities and differences in the data analysis preparation across different engineering majors will come to the fore, as a first stage for potential programmatic evaluations and changes.
Kim, E., & Hicks, N. M., & Sanchez-Pena, M. L. (2019, June), Assessing the Data Analysis Training of Engineering Undergraduates Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. https://peer.asee.org/32119
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