This project aims to enhance students’ learning in foundational engineering courses through oral exams based on the research conducted at the University of California San Diego. The adaptive dialogic nature of oral exams provides instructors an opportunity to better understand students’ thought processes, thus holding promise for improving both assessments of conceptual mastery and students’ learning attitudes and strategies. However, the issues of oral exam reliability, validity, and scalability have not been fully addressed. As with any assessment format, careful design is needed to maximize the benefits of oral exams to student learning and minimize the potential concerns. Compared to traditional written exams, oral exams have a unique design space, which involves a large range of parameters, including the type of oral assessment questions, grading criteria, how oral exams are administered, how questions are communicated and presented to the students, how feedback were provided, and other logistical perspectives such as weight of oral exam in overall course grade, frequency of oral assessment, etc. In order to address the scalability for high enrollment classes, key elements of the project are the involvement of the entire instructional team (instructors and teaching assistants). Thus the project will create a new training program tomore »
Evaluating Oral Exams in Large Undergraduate Engineering Courses
While studies have shown that oral exams are a valuable method of assessment, their use has been limited due to concerns about scalability, examiner bias, and student anxiety. This paper presents preliminary results on incorporating oral exams into two large undergraduate engineering courses, examining the potential viability of these assessment strategies. This work was done when the courses were offered remotely due to COVID-19, but the results offer valuable insights that could carry over to in-person instruction as well.
- Award ID(s):
- 2044472
- Publication Date:
- NSF-PAR ID:
- 10311805
- Journal Name:
- IEEE-AP-S URSI 2021
- Sponsoring Org:
- National Science Foundation
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