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Worked examples in computer science

Published: 20 January 2014 Publication History

Abstract

Most instructors teaching Computer Science use examples to help students learn, and many instructors use worked examples (either in a static or a dynamic style) in their courses. However, the research on worked examples is not well known in the Computer Science Education community. This paper provides an overview of how worked examples have been studied, and the major findings from the literature, particularly as they relate to Computer Science.

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Information & Contributors

Information

Published In

cover image ACM Conferences
ACE '14: Proceedings of the Sixteenth Australasian Computing Education Conference - Volume 148
January 2014
174 pages
ISBN:9781921770319

Sponsors

  • Datacom: Datacom
  • Australian Comp Soc: Australian Computer Society
  • SERL: Software Engineering Research Lab, Auckland University of Technology
  • Auckland University of Technology
  • ACM: Association for Computing Machinery
  • Univ. of Western Sydney: University of Western Sydney
  • The University of Auckland, New Zealand
  • CORE - Computing Research and Education
  • Colab: Collaboratory of Design & Creative Technologies, Auckland University of Technology
  • RMIT University
  • IITP: Institute of IT Professionals New Zealand
  • SIGCSE: ACM Special Interest Group on Computer Science Education

Publisher

Australian Computer Society, Inc.

Australia

Publication History

Published: 20 January 2014

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Author Tags

  1. cognition
  2. cognitive load theory
  3. learning
  4. worked examples

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  • Research-article

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ACE '14 Paper Acceptance Rate 19 of 40 submissions, 48%;
Overall Acceptance Rate 161 of 359 submissions, 45%

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Cited By

View all
  • (2024)Evaluating the Efficacy of Peer-Created Worked-Example Videos in a Computer Systems CourseJournal of Computing Sciences in Colleges10.5555/3665609.366561539:8(83-97)Online publication date: 17-May-2024
  • (2024)The Role of Programming in Lower Secondary Math Education in ProbabilityProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699573(1-2)Online publication date: 12-Nov-2024
  • (2024)Example Output: A Sequentialist Rabbit Hole for Students Solving Concurrent ProblemsProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699565(1-11)Online publication date: 12-Nov-2024
  • (2024)Plagiarism in the Age of Generative AI: Cheating Method Change and Learning Loss in an Intro to CS CourseProceedings of the Eleventh ACM Conference on Learning @ Scale10.1145/3657604.3662046(75-85)Online publication date: 9-Jul-2024
  • (2024)Evaluating LLM-generated Worked Examples in an Introductory Programming CourseProceedings of the 26th Australasian Computing Education Conference10.1145/3636243.3636252(77-86)Online publication date: 29-Jan-2024
  • (2024)Hint Cards for Common Ozobot Robot Issues: Supporting Feedback for Learning Programming in Elementary SchoolsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630868(408-414)Online publication date: 7-Mar-2024
  • (2021)A Pedagogical Framework for Teaching Computer Programming: A Social Constructivist and Cognitive Load Theory ApproachProceedings of the 17th ACM Conference on International Computing Education Research10.1145/3446871.3469778(415-416)Online publication date: 16-Aug-2021
  • (2021)A Semblance of Similarity: Student Categorisation of Simple Algorithmic Problem StatementsProceedings of the 17th ACM Conference on International Computing Education Research10.1145/3446871.3469745(198-212)Online publication date: 16-Aug-2021
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  • (2019)FLOSS in Software Engineering EducationProceedings of the XXXIII Brazilian Symposium on Software Engineering10.1145/3350768.3353815(234-243)Online publication date: 23-Sep-2019
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