Why do CS1 Students Think They're Bad at Programming? Investigating Self-efficacy and Self-assessments at Three Universities

Jamie Gorson, Eleanor O'Rourke

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

1 Scopus citations

Abstract

Undergraduate computer science (CS) programs often suffer from high dropout rates. Recent research suggests that self-efficacy - an individual's belief in their ability to complete a task - can influence whether students decide to persist in CS. Studies show that students' self-assessments affect their self-efficacy in many domains, and in CS, researchers have found that students frequently assess their programming ability based on their expectations about the programming process. However, we know little about the specific programming experiences that prompt the negative self-assessments that lead to lower self-efficacy. In this paper, we present findings from a survey study with 214 CS1 students from three universities. We used vignette-style questions to describe thirteen programming moments which may prompt negative self-assessments, such as getting syntax errors and spending time planning. We found that many students across all three universities reported that they negatively self-assess at each of the thirteen moments, despite the differences in curriculum and population. Furthermore, those who report more frequent negative self-assessments tend to have lower self-efficacy. Finally, our findings suggest that students' perceptions of professional programming practice may influence their expectations and negative self-assessments. By reducing the frequency that students self-assess negatively while programming, we may be able to improve self-efficacy and decrease dropout rates in CS.

Original languageEnglish (US)
Title of host publicationICER 2020 - Proceedings of the 2020 ACM Conference on International Computing Education Research
PublisherAssociation for Computing Machinery
Pages170-181
Number of pages12
ISBN (Electronic)9781450370929
DOIs
StatePublished - Aug 10 2020
Event16th Annual ACM Conference on International Computing Education Research, ICER 2020 - Virtual, Online, New Zealand
Duration: Aug 10 2020Aug 12 2020

Publication series

NameICER 2020 - Proceedings of the 2020 ACM Conference on International Computing Education Research

Conference

Conference16th Annual ACM Conference on International Computing Education Research, ICER 2020
CountryNew Zealand
CityVirtual, Online
Period8/10/208/12/20

Keywords

  • cs1
  • persistence
  • self-assessments
  • self-efficacy

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Why do CS1 Students Think They're Bad at Programming? Investigating Self-efficacy and Self-assessments at Three Universities'. Together they form a unique fingerprint.

Cite this