Encouraging Grading: Per Aspera Ad A-Stars

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

Abstract

The surge in computer science student enrollment in Data Structures and Algorithm course necessitates flexible teaching strategies, accommodating both struggling and proficient learners. This study examines the shift from manual grading to auto-graded and peer-reviewed assessments, investigating student preferences and their impact on growth and improvement. Utilizing data from Plussa LMS and GitLab, auto-graders allow iterative submissions and quick feedback. Initially met with skepticism, peer-review gained acceptance, offering valuable exercises for reviewers and alternative solutions for reviewees. Auto-grading became the favored approach due to its swift feedback, facilitating iterative improvement. Furthermore, students expressed a preference for a substantial number of submissions, with the most frequently suggested count being 50 submissions. Manual grading, while supported due to its personal feedback, was considered impractical given the course scale. Auto-graders like unit-tests, integration tests, and perftests were well-received, with perftests and visualizations aligning with efficient code learning goals. In conclusion, used methods, such as auto-grading and peer-review, cater to diverse proficiency levels. These approaches encourage ongoing refinement, deepening engagement with challenging subjects, and fostering a growth mindset.

Original languageEnglish
Title of host publicationComputer Supported Education
Subtitle of host publication15th International Conference, CSEDU 2023 Prague, Czech Republic, April 21–23, 2023 Revised Selected Papers
EditorsBruce M. McLaren, James Uhomoibhi, Jelena Jovanovic, Irene-Angelica Chounta
PublisherSpringer
Pages23-46
Number of pages24
ISBN (Electronic)978-3-031-53656-4
ISBN (Print)978-3-031-53655-7
DOIs
Publication statusPublished - 2024
Publication typeA4 Article in conference proceedings
EventInternational Conference on Computer Supported Education, CSEDU - Prague, Czech Republic
Duration: 21 Apr 202323 Apr 2023

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume2052
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

ConferenceInternational Conference on Computer Supported Education, CSEDU
Country/TerritoryCzech Republic
CityPrague
Period21/04/2323/04/23

Keywords

  • Assessment and feedback
  • Automatic grading
  • Flipped learning
  • Growth mindset
  • Leaderboards
  • Learning analytics
  • Learning management system
  • Manual grading
  • Next-generation learning environment
  • Peer-reviews
  • The theory of formative assessment

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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