Getting By With Help From My Friends: Group Study in Introductory Programming Understood as Socially Shared Regulation

James Prather, Lauren Margulieux, Jacqueline Whalley, Paul Denny, Brent N. Reeves, Brett A. Becker, Paramvir Singh, Garrett Powell, Nigel Bosch

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

Abstract

Background and Context. Metacognitive skills are important for all students learning to program and interest in applying pedagogical approaches in early programming courses that focus on metacognitive aspects is growing. However, most studies of such approaches are not rigorously based in theory, and when they are, almost always utilize foundational education and psychology theories from as far back as the 1970s. More recent theory is less tested, and not all relevant metacognitive theories have been explored in the computing education research literature. Objectives. We present the first use in a programming education context of a newer metacognitive theory that explicitly examines the differences between self-regulation, co-regulation, and socially shared regulation. Our research questions are: 1) How do students express their learning strategies, both when working alone and when working in groups, and how do these align with existing models of self-regulation and co-regulation? and 2) To what extent do written expressions of self-regulation, co-regulation, and socially shared regulation relate to student performance? Methods. Grounded in the above mentioned theory, we collected qualitative self-reflection and quantitative course performance data from nearly 1,000 students in an introductory programming course. We use these data to explore students' self-regulation habits when studying alone and their co-regulation habits when studying in groups. Findings. Our findings indicate that higher self-regulation correlates with higher performance, but higher co-regulation had the opposite effect. We explore these differences through a qualitative analysis of the self-reflection statements and identify co-regulation strategies to build upon existing models of self-regulation. Implications. We identify emergent themes in our data that align with those in recent literature in self-regulated learning in computing education and present the first set of co-regulation themes in computing education. This work is at the frontier of self- and co-regulation in introductory programming and identifies several factors that can be used to advance future work and, most importantly, improve student outcomes.

Original languageEnglish (US)
Title of host publicationICER 2022 - Proceedings of the 2022 ACM Conference on International Computing Education Research
PublisherAssociation for Computing Machinery
Pages164-176
Number of pages13
ISBN (Electronic)9781450391948
DOIs
StatePublished - Aug 3 2022
Event18th Annual ACM International Computing Education Research Conference, ICER 2022 - Virtual, Online, Switzerland
Duration: Aug 7 2022Aug 11 2022

Publication series

NameICER 2022 - Proceedings of the 2022 ACM Conference on International Computing Education Research
Volume1

Conference

Conference18th Annual ACM International Computing Education Research Conference, ICER 2022
Country/TerritorySwitzerland
CityVirtual, Online
Period8/7/228/11/22

Keywords

  • CS1
  • co-regulation
  • group work
  • groups
  • introductory programming
  • metacognition
  • programming education
  • self-regulation
  • socially shared regulation
  • study habits
  • studying

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Education
  • Computational Theory and Mathematics

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