skip to main content
10.1145/3564721.3565951acmotherconferencesArticle/Chapter ViewAbstractPublication Pageskoli-callingConference Proceedingsconference-collections
research-article

An Analysis of Tutors’ Adoption of Explicit Instructional Strategies in an Introductory Programming Course

Published: 17 November 2022 Publication History

Abstract

In this paper we analyse in detail how tutors of an undergraduate-level introductory programming course use two explicit instructional strategies in practice with their students. The two strategies they used were an explicit tracing strategy and a subgoal learning strategy. We explored what triggered their use of these strategies, how faithfully they followed the proposed strategies, and how they adapted it in practice to their classroom setting. We rely on literature on fidelity of implementation to assess tutors’ adoption of these strategies. The tracing strategy was much more used and with higher fidelity than the subgoal learning strategy. Tutors adopted both strategies with adaptations, simplifications and even combining them. From our observations we draw good and bad practices on the adoption of such explicit instructional strategies for future generations of tutors.

References

[1]
Maura Borrego, Stephanie Cutler, Michael Prince, Charles Henderson, and Jeffrey E. Froyd. 2013. Fidelity of Implementation of Research-Based Instructional Strategies (RBIS) in Engineering Science Courses. Journal of Engineering Education 102, 3 (2013), 394–425. https://doi.org/10.1002/jee.20020 _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/jee.20020.
[2]
Virginia Braun and Victoria Clarke. 2019. Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health 11, 4 (Aug. 2019), 589–597. https://doi.org/10.1080/2159676X.2019.1628806 Publisher: Routledge _eprint: https://doi.org/10.1080/2159676X.2019.1628806.
[3]
Richard Catrambone. 2011. Task Analysis by Problem Solving (TAPS): Uncovering Expert Knowledge to Develop High-Quality Instructional Materials and Training. In Learning and Technology Symposium, Columbus, GA.
[4]
Richard Clark, David Feldon, Jeroen J. G. Van Merrienboer, Kenneth Yates, and Sean Early. 2008. Cognitive Task Analysis. In Handbook of Research on Educational Communications and Technology. Chapter 43, 577–593.
[5]
Kathryn Cunningham, Sarah Blanchard, Barbara Ericson, and Mark Guzdial. 2017. Using tracing and sketching to solve programming problems: replicating and extending an analysis of what students draw. In Proceedings of the 2017 ACM Conference on international computing education research. 164–172.
[6]
Michael De Raadt, Mark Toleman, and Richard Watson. 2007. Incorporating Programming Strategies Explicitly into Curricula. In Proceedings of the Seventh Baltic Sea Conference on Computing Education Research-Volume 88. Australian Computer Society, Inc., 41–52.
[7]
Michael de Raadt, Richard Watson, and Mark Toleman. 2006. Chick Sexing and Novice Programmers: Explicit Instruction of Problem Solving Strategies. In Proceedings of the 8th Australasian Conference on Computing Education-Volume 52. Australian Computer Society, Inc., 55–62.
[8]
Paul E Dickson and Toby Dragon. 2021. A Memory Diagram for All Seasons. In Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1. 150–156.
[9]
Paul E Dickson, Toby Dragon, and Adam Lee. 2017. Using undergraduate teaching assistants in small classes. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education. 165–170.
[10]
Toby Dragon and Paul E. Dickson. 2016. Memory Diagrams: A Consistant Approach Across Concepts and Languages. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education(SIGCSE ’16). ACM, New York, NY, USA, 546–551. https://doi.org/10.1145/2839509.2844607
[11]
Barbara J. Ericson, Lauren E. Margulieux, and Jochen Rick. 2017. Solving Parsons Problems Versus Fixing and Writing Code. In Proceedings of the 17th Koli Calling International Conference on Computing Education Research(Koli Calling ’17). ACM, New York, NY, USA, 20–29. https://doi.org/10.1145/3141880.3141895
[12]
Jeffrey Forbes, David J Malan, Heather Pon-Barry, Stuart Reges, and Mehran Sahami. 2017. Scaling introductory courses using undergraduate teaching assistants. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on computer science education. 657–658.
[13]
Mariane Frenay, Benoît Galand, Elie Milgrom, and Benoît Raucent. 2007. Project-and Problem-Based Learning in the Engineering Curriculum at the University of Louvain. In Management of Change. Brill Sense, 93–108.
[14]
Benoît Galand, Mariane Frenay, and Benoît Raucent. 2012. Effectiveness of Problem-Based Learning in Engineering Education: A Comparative Study on Three Levels of Knowledge Structure. International Journal of Engineering Education 28, 4 (2012), 939.
[15]
Olivier Goletti. 2021. Promoting Learning Transfer in Computer Science Education by Training Teachers to Use Explicit Programming Strategies. In ICER ’17. ACM, Virtual Event USA, 411–412. https://doi.org/10.1145/3446871.3469776
[16]
Olivier Goletti, Florian De Pierpont, and Kim Mens. 2022. Création d’exemples résolus avec objectifs étiquetés pour l’apprentissage de la programmation avec Python. In Didapro 9–DidaSTIC.
[17]
Olivier Goletti and Kim Mens. 2022. Atelier : Utiliser des stratégies d’instruction explicites dans l’enseignement de la programmation. https://dial.uclouvain.be/pr/boreal/object/boreal:263637
[18]
Olivier Goletti, Kim Mens, and Felienne Hermans. 2021. Tutors’ Experiences in Using Explicit Strategies in a Problem-Based Learning Introductory Programming Course. In ITiCSE ’21. ACM Press, Virtual Event, Germany, 7. https://doi.org/10.1145/3430665.3456348
[19]
Matthew Hertz and Maria Jump. 2013. Trace-based teaching in early programming courses. In Proceeding of the 44th ACM technical symposium on Computer science education. 561–566.
[20]
Paul A. Kirschner. 2002. Cognitive Load Theory: Implications of Cognitive Load Theory on the Design of Learning. Learning and Instruction 12, 1 (Feb. 2002), 1–10. https://doi.org/10.1016/S0959-4752(01)00014-7
[21]
Paul A. Kirschner, John Sweller, and Richard E. Clark. 2006. Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching. Educational Psychologist 41, 2 (June 2006), 75–86. https://doi.org/10.1207/s15326985ep4102_1
[22]
Amy J. Ko, Thomas D. LaToza, Stephen Hull, Ellen A. Ko, William Kwok, Jane Quichocho, Harshitha Akkaraju, and Rishin Pandit. 2019. Teaching Explicit Programming Strategies to Adolescents. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education(SIGCSE ’19). ACM, New York, NY, USA, 469–475. https://doi.org/10.1145/3287324.3287371
[23]
Thomas D. LaToza, Maryam Arab, Dastyni Loksa, and Amy J. Ko. 2020. Explicit Programming Strategies. Empirical Software Engineering 25, 4 (July 2020), 2416–2449. https://doi.org/10.1007/s10664-020-09810-1
[24]
Raymond Lister, Elizabeth S. Adams, Sue Fitzgerald, William Fone, John Hamer, Morten Lindholm, Robert McCartney, Jan Erik Moström, Kate Sanders, and Otto Seppälä. 2004. A Multi-National Study of Reading and Tracing Skills in Novice Programmers. In ACM SIGCSE Bulletin, Vol. 36. ACM, 119–150.
[25]
Raymond Lister, Colin Fidge, and Donna Teague. 2009. Further evidence of a relationship between explaining, tracing and writing skills in introductory programming. Acm sigcse bulletin 41, 3 (2009), 161–165.
[26]
Dastyni Loksa, Amy J. Ko, Will Jernigan, Alannah Oleson, Christopher J. Mendez, and Margaret M. Burnett. 2016. Programming, Problem Solving, and Self-Awareness: Effects of Explicit Guidance. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 1449–1461.
[27]
Lauren Margulieux, Richard Catrambone, and Mark Guzdial. 2013. Subgoal Labeled Worked Examples Improve K-12 Teacher Performance in Computer Programming Training. In Proceedings of the Annual Meeting of the Cognitive Science Society, Vol. 35.
[28]
Lauren E Margulieux, Mark Guzdial, and Richard Catrambone. 2012. Subgoal-labeled instructional material improves performance and transfer in learning to develop mobile applications. In Proceedings of the ninth annual international conference on International computing education research. 71–78.
[29]
Lauren E. Margulieux, Briana B. Morrison, and Adrienne Decker. 2019. Design and Pilot Testing of Subgoal Labeled Worked Examples for Five Core Concepts in CS1. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education - ITiCSE ’19. ACM Press, Aberdeen, Scotland Uk, 548–554. https://doi.org/10.1145/3304221.3319756
[30]
Briana B. Morrison, Lauren E. Margulieux, and Mark Guzdial. 2015. Subgoals, Context, and Worked Examples in Learning Computing Problem Solving. In Proceedings of the Eleventh Annual International Conference on International Computing Education Research. ACM Press, 21–29. https://doi.org/10.1145/2787622.2787733
[31]
Carol T Mowbray, Mark C Holter, Gregory B Teague, and Deborah Bybee. 2003. Fidelity Criteria: Development, Measurement, and Validation. American Journal of Evaluation 24, 3 (2003), 315–340.
[32]
Carol L. O’Donnell. 2008. Defining, conceptualizing, and measuring fidelity of implementation and its relationship to outcomes in K–12 curriculum intervention research. Review of educational research 78, 1 (2008), 33–84. Publisher: Sage Publications.
[33]
Fred Paas, Alexander Renkl, and John Sweller. 2003. Cognitive load theory and instructional design: Recent developments. Educational psychologist 38, 1 (2003), 1–4.
[34]
David N Perkins, Chris Hancock, Renee Hobbs, Fay Martin, and Rebecca Simmons. 1986. Conditions of learning in novice programmers. Journal of Educational Computing Research 2, 1 (1986), 37–55.
[35]
Emma Riese, Madeleine Lorås, Martin Ukrop, and Tomáš Effenberger. 2021. Challenges Faced by Teaching Assistants in Computer Science Education Across Europe. In Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1. 547–553.
[36]
Sue Sentance. 2021. Teaching computing in school: is K-12 research reaching classroom practice?. In 21st Koli Calling International Conference on Computing Education Research. 1–2.
[37]
Elliot Soloway. 1986. Learning to Program= Learning to Construct Mechanisms and Explanations. Commun. ACM 29, 9 (1986), 850–858.
[38]
John Sweller. 1988. Cognitive load during problem solving: Effects on learning. Cognitive science 12, 2 (1988), 257–285.
[39]
John Sweller, Paul Ayres, and Slava Kalyuga. 2011. Cognitive Load Theory, Volume 1 of Explorations in the Learning Sciences, Instructional Systems and Performance Technologies. Springer, New York.
[40]
John Sweller, Jeroen JG van Merriënboer, and Fred Paas. 2019. Cognitive Architecture and Instructional Design: 20 Years Later. Educational Psychology Review(2019), 1–32. Publisher: Springer.
[41]
J Gregory Trafton and Brian J Reiser. 1993. Studying examples and solving problems: Contributions to skill acquisition. In Proceedings of the 15th conference of the Cognitive Science Society. Citeseer, 1017–1022.
[42]
Vesa Vainio and Jorma Sajaniemi. 2007. Factors in novice programmers’ poor tracing skills. ACM SIGCSE Bulletin 39, 3 (2007), 236–240.
[43]
Tamara van Gog, Fred Paas, and John Sweller. 2010. Cognitive Load Theory: Advances in Research on Worked Examples, Animations, and Cognitive Load Measurement. Educational Psychology Review 22, 4 (Dec. 2010), 375–378. https://doi.org/10.1007/s10648-010-9145-4
[44]
Jeroen J. G. van Merriënboer and John Sweller. 2005. Cognitive Load Theory and Complex Learning: Recent Developments and Future Directions. Educational Psychology Review 17, 2 (June 2005), 147–177. https://doi.org/10.1007/s10648-005-3951-0
[45]
Mark Ward and John Sweller. 1990. Structuring effective worked examples. Cognition and instruction 7, 1 (1990), 1–39.
[46]
Benjamin Xie, Greg L. Nelson, and Amy J. Ko. 2018. An Explicit Strategy to Scaffold Novice Program Tracing. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education. ACM, 344–349.

Cited By

View all
  • (2024)Interrelation between Teaching Assistants' debugging strategies and adherence to sound tutoring practices during office hoursProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699562(1-11)Online publication date: 12-Nov-2024
  • (2024)An Observational Study of Undergraduate Teaching Assistants’ Use of Subgoal Learning Integrated in an Introductory Programming CourseProceedings of the 2024 ACM SIGPLAN International Symposium on SPLASH-E10.1145/3689493.3689986(77-88)Online publication date: 17-Oct-2024

Index Terms

  1. An Analysis of Tutors’ Adoption of Explicit Instructional Strategies in an Introductory Programming Course

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    Koli Calling '22: Proceedings of the 22nd Koli Calling International Conference on Computing Education Research
    November 2022
    282 pages
    ISBN:9781450396165
    DOI:10.1145/3564721
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 November 2022

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. CS1
    2. adaptation
    3. explicit strategy
    4. fidelity of implementation
    5. observation
    6. subgoal learning
    7. tracing

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    Koli 2022

    Acceptance Rates

    Overall Acceptance Rate 80 of 182 submissions, 44%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)40
    • Downloads (Last 6 weeks)11
    Reflects downloads up to 07 Mar 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Interrelation between Teaching Assistants' debugging strategies and adherence to sound tutoring practices during office hoursProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699562(1-11)Online publication date: 12-Nov-2024
    • (2024)An Observational Study of Undergraduate Teaching Assistants’ Use of Subgoal Learning Integrated in an Introductory Programming CourseProceedings of the 2024 ACM SIGPLAN International Symposium on SPLASH-E10.1145/3689493.3689986(77-88)Online publication date: 17-Oct-2024

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    HTML Format

    View this article in HTML Format.

    HTML Format

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media