ERIC Number: EJ1042412
Record Type: Journal
Publication Date: 2013-Aug
Pages: 22
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-1946-6226
EISSN: N/A
Available Date: N/A
Can Peer Instruction Be Effective in Upper-Division Computer Science Courses?
Bailey Lee, Cynthia; Garcia, Saturnino; Porter, Leo
ACM Transactions on Computing Education, v13 n3 Article 12 Aug 2013
Peer Instruction (PI) is an active learning pedagogical technique. PI lectures present students with a series of multiple-choice questions, which they respond to both individually and in groups. PI has been widely successful in the physical sciences and, recently, has been successfully adopted by computer science instructors in lower-division, introductory courses. In this work, we challenge readers to consider PI for their upper-division courses as well. We present a PI curriculum for two upper-division computer science courses: Computer Architecture and Theory of Computation. These courses exemplify several perceived challenges to the adoption of PI in upper-division courses, including: exploration of abstract ideas, development of high-level judgment of engineering design trade-offs, and exercising advanced mathematical sophistication. This work includes selected course materials illustrating how these challenges are overcome, learning gains results comparing these upper-division courses with previous lower-division results in the literature, student attitudinal survey results (N = 501), and pragmatic advice to prospective developers and adopters. We present three main findings. First, we find that these upper-division courses achieved student learning gains equivalent to those reported in successful lower-division computing courses. Second, we find that student feedback for each class was overwhelmingly positive, with 88% of students recommending PI for use in other computer science classes. Third, we find that instructors adopting the materials introduced here were able to replicate the outcomes of the instructors who developed the materials in terms of student learning gains and student feedback.
Descriptors: Computer Science Education, Advanced Courses, Active Learning, Statistical Analysis, Qualitative Research, College Students, Audience Response Systems, Student Attitudes, Student Surveys, Instructional Effectiveness, Teaching Methods, College Instruction
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: National Science Foundation
Authoring Institution: N/A
Identifiers - Location: California
Grant or Contract Numbers: 1140636
Author Affiliations: N/A