{"title":"Impact of Class Size on Student Evaluations for Traditional and Peer Instruction Classrooms","authors":"Soohyun Nam Liao, W. Griswold, Leo Porter","doi":"10.1145/3017680.3017764","DOIUrl":null,"url":null,"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.","PeriodicalId":344382,"journal":{"name":"Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3017680.3017764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
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.