Novice programmers inaccurately monitor the quality of their work and their peers' work in an introductory computer science course

Elizabeth B. Cloude, Pranshu Kumar, Ryan S. Baker, Eric Fouh

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

1 Citation (Scopus)
48 Downloads (Pure)

Abstract

A student's ability to accurately evaluate the quality of their work holds significant implications for their self-regulated learning and problem-solving proficiency in introductory programming. A widespread cognitive bias that frequently impedes accurate self- assessment is overconfidence, which often stems from a misjudgment of contextual and task-related cues, including students' judgment of their peers' competencies. Little research has explored the role of overconfidence on novice programmers' ability to accurately monitor their own work in comparison to their peers' work and its impact on performance in introductory programming courses. The present study examined whether novice programmers exhibited a common cognitive bias called the "hard-easy effect", where students believe their work is better than their peers on easier tasks (overplace) but worse than their peers on harder tasks (underplace). Results showed a reversal of the hard-easy effect, where novices tended to overplace themselves on harder tasks, yet underplace themselves on easier ones. Remarkably, underplacers performed better on an exam compared to overplacers. These findings advance our understanding of relationships between the hard-easy effect, monitoring accuracy across multiple tasks, and grades within introductory programming. Implications of this study can be used to guide instructional decision making and design to improve novices' metacognitive awareness and performance in introductory programming courses.

Original languageEnglish
Title of host publicationLAK 2024 Conference Proceedings - 14th International Conference on Learning Analytics and Knowledge
PublisherACM
Pages35-45
Number of pages11
ISBN (Electronic)979-8-4007-1618-8
DOIs
Publication statusPublished - 18 Mar 2024
Publication typeA4 Article in conference proceedings
EventInternational Conference on Learning Analytics and Knowledge - Kyoto, Japan
Duration: 18 Mar 202422 Mar 2024
Conference number: 14
https://www.solaresearch.org/events/lak/lak24/

Conference

ConferenceInternational Conference on Learning Analytics and Knowledge
Abbreviated titleLAK 2024
Country/TerritoryJapan
CityKyoto
Period18/03/2422/03/24
Internet address

Keywords

  • CS1
  • Hard-easy Effect
  • Metacognition
  • Overconfidence

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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