Exploring the Impact of Multiple Representations in Introductory Programming: A Pilot Study

Naaz Sibia, Valeria Ramirez Osorio, Angela Zavaleta Bernuy, Efthimia Aivaloglou, Rutwa Engineer, Andrew Petersen, Michael Liut, Carolina Nobre

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

This pilot study explores how visualization strategies, grounded in multiple representations theory, impact novice students’ engagement, and cognitive load during program tracing tasks. Students were were shown a visualization of the three-variable swap problem at the start of an introductory programming course (CS1) at a large public North American research-intensive university. We compared three conditions: interactive multiple representations, Python Tutor (a single-representation tool), and text-only methods. Preliminary results indicate that interactive multiple representations increase engagement for students with prior programming experience, while no significant differences were observed for students without prior experience. These findings suggest that while multiple representations may boost engagement, identifying how to effectively support students of all experience levels and reduce cognitive load requires further study.

Original languageEnglish
Title of host publicationProceedings of 24th International Conference on Computing Education Research, Koli Calling 2024
PublisherACM
Number of pages2
ISBN (Electronic)9798400710384
DOIs
Publication statusPublished - 2024
Event24th International Conference on Computing Education Research, Koli Calling 2024 - Koli, Finland
Duration: 14 Nov 202417 Nov 2024

Publication series

NameACM International Conference Proceeding Series

Conference

Conference24th International Conference on Computing Education Research, Koli Calling 2024
Country/TerritoryFinland
CityKoli
Period14/11/2417/11/24

Keywords

  • code tracing
  • introductory programming
  • multiple representations theory
  • visualization

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