Impact of class size on student evaluations for traditional and peer instruction classrooms

Soohyun Nam Liao, William G. Griswold, Leo Porter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

As student enrollments in computer science increase, there is a growing need for pedagogies that scale. Recent evidence has shown Peer Instruction (PI) to be an effective in-class pedagogy that reports high student satisfaction even with large classes. Yet, the question of the scalability of traditional lecture versus PI is largely unexplored. To explore this question, this work examines publicly available student evaluations of computer science courses across a wide range of class sizes (50{374 students) over a four year period. It first compares evaluations regardless of size and confirms prior work that PI classes are better appreciated by students than traditional lecture. It then examines how course evaluations change with class size and provides evidence that PI achieves a smaller decline in evaluations as class size increases.

Original languageEnglish (US)
Title of host publicationSIGCSE 2017 - Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education
PublisherAssociation for Computing Machinery
Pages375-380
Number of pages6
ISBN (Electronic)9781450346986
DOIs
StatePublished - Mar 8 2017
Event48th ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2017 - Seattle, United States
Duration: Mar 8 2017Mar 11 2017

Publication series

NameProceedings of the Conference on Integrating Technology into Computer Science Education, ITiCSE

Conference

Conference48th ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2017
Country/TerritoryUnited States
CitySeattle
Period3/8/173/11/17

All Science Journal Classification (ASJC) codes

  • General Engineering

Keywords

  • Class size
  • Peer instruction
  • Student evaluations

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