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Hash Table Notional Machines: A Comparison of 2D and 3D Representations

  • Colleen M. Lewis
  • , Craig S. Miller
  • , Johan Jeuring
  • , Janice L. Pearce
  • , Andrew Petersen

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

Abstract

Background: Notional machines appear to be an essential aspect of computing education, but there are few papers that identify strengths and weaknesses of particular notional machines. Purpose: This article fills a gap in the notional machine literature by using a randomized controlled trial to compare the effectiveness of different notional machine representations. Methods: Our study used notional machines for two hash table algorithms: chaining and open addressing. Students were randomly assigned a video sequence using either 2D or 3D representations. Findings: We found minimal effect of 2D vs 3D representational form on students' learning and perceptions of helpfulness. Implications: Our paper provides an example of how educational research can inform the design and evaluation of notional machines.

Original languageEnglish (US)
Title of host publicationSIGCSE Virtual 2024 - Proceedings of the 2024 ACM Virtual Global Computing Education Conference V. 1
PublisherAssociation for Computing Machinery
Pages109-115
Number of pages7
ISBN (Electronic)9798400705984
DOIs
StatePublished - Dec 5 2024
Event1st ACM Virtual Global Computing Education Conference V. 1, SIGCSE Virtual 2024 - Virtual, Online, United States
Duration: Dec 5 2024Dec 8 2024

Publication series

NameSIGCSE Virtual 2024 - Proceedings of the 2024 ACM Virtual Global Computing Education Conference V. 1

Conference

Conference1st ACM Virtual Global Computing Education Conference V. 1, SIGCSE Virtual 2024
Country/TerritoryUnited States
CityVirtual, Online
Period12/5/2412/8/24

Keywords

  • hash tables
  • hashset
  • java
  • notional machine

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Education

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