期刊名称：Proceedings of the Canadian Engineering Education Association
出版年度：2017
期号：Proceedings of the Canadian Engineering Education Association (CEEA) Conference- June 4-7, 2017 University of Toronto
DOI：10.24908/pceea.v0i0.7329
出版社：The Canadian Engineering Education Association (CEEA)
摘要：This paper provides results from the first three years of a 4-year longitudinal assessment project on the development of cognitive skills using the Collegiate Learning Assessment (CLA+). The CLA+ is an online test, designed to measure cognitive skills (CS) (critical thinking, problem solving and written communication, with sub-scores reporting scientific and quantitative reasoning, critical reading and evaluation, and critiquing an argument). Cognitive skills are fundamental elements of engineering programs and central to the practice of engineering. The Canadian Engineering Accreditation Board’s (CEAB) requires programs to assess their student’s graduate attributes and have a system in place to use the assessment for curriculum improvement. CLA+ assessment constructs relate to the CEAB attributes of problem analysis, investigation and communication. The testing was initiated as part of a strategy to track development of cognitive skills and to inform course improvement efforts. The testing was embedded in a range of engineering courses. Student achievement on written communication outcomes appeared to fall over time, and critiquing an argument was identified as an area of weakness, specifically for the first year students. Strategies were subsequently implemented as part of a curriculum improvement initiative. With the goal of maximizing success for all students, we investigated differences in achievement based on sex, language, and parental education, as well as the amount of effort put into the test. There were significant differences in achievement, prompting concerns about motivation and relevance to the engineering discipline. Students without English as a first language demonstrated negative gains over time. Parental education level was the strongest predictor of performance, but the most significant factor impacting on students’ scores was self-reported effort.
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