Salt Lake City, Utah
June 23, 2018
June 23, 2018
July 27, 2018
Collaborative problem solving is a valuable skill encouraged in many engineering classrooms. This collaborative problem solving is an ABET requirement as well as a characteristic of the National Academy of Engineering’s “Engineer of 2020”. Course grades, however, are assigned individually, and the institution, which bears the ethical responsibility to validate baseline competence in the engineering profession, uses these grades to confer degrees to individuals and not groups. By observation and anecdote, “digital natives” (people who have lived their entire lives with easy access to information technology) approach learning and the propriety of knowledge differently than previous generations. To the digital native, “individual work” may mean that an assignment is submitted individually but its preparation can be collaborative. Upon submission, the instructor wrestles with validating a student’s individual understanding of course material while still encouraging synergistic peer-learning and the use of digital technology both in and out of the classroom. How can the framework of engineering courses change to meet how digital natives interact with information, maintain the integrity of the educational assessment process, and foster appreciation for individual ethical responsibility in the engineering profession? In a 3-year longitudinal study, the authors examined student performance and experimented with alternate assessment models in an introductory environmental engineering course for juniors with multi-disciplinary enrollment. This longitudinal study was designed to indicate better assessment and academic validation of digital natives while enhancing valuable peer-learning. Individual and course-wide grades as well as student feedback are used to assess student performance. Comparison of course-end comprehensive exam results (assumed to demonstrate individual material mastery) were compared with term grades (which will be influenced by collaboration on out-of-class assignments) using a Mastery of Material Indicator (MMI). Our study indicates that the traditional course assessment model still requires more maturation to provide targeted student learning feedback but a qualitative analysis establishes the digital natives respond favorably to an assessment model that deliberately emphasizes individual feedback both in terms of grades and instructor comments.
Sheehan, N. P., & Starke, J. A., & Zgonc, D. C. (2018, June), Collaboration in Assessment and Individual Validation for the 'Digital Native' Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/30200
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