research-article

Tutors' Experiences in Using Explicit Strategies in a Problem-Based Learning Introductory Programming Course

Authors:

Olivier Goletti,

Felienne HermansAuthors Info & Claims

ITiCSE '21: Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1

Pages 157 - 163

https://doi.org/10.1145/3430665.3456348

Published: 26 June 2021 Publication History

Abstract

In programming education, explicit strategies are gaining traction. The reason for this study was to improve an introductory programming course based on a problem-based methodology, by using more explicit programming strategies. After analysing a previous run of this course for first year undergraduate students, we concluded that such strategies could improve learning transfer for students across the different weeks of the semester. We introduced four instructional strategies to tutors with close to no pedagogical background: explicit tracing, subgoal labeled worked examples, Parsons problems and explicit problem solving. These explicit programming strategies aim to decrease cognitive load. Tutors tested these four strategies in the course.

Our goal was to explore how tutors could benefit in their tutoring from explicit strategies. Interviews with the tutors show that the easiest and most effective of the tested strategies were best used. For the more elaborate strategies, more time should be devoted to explain and model them or they can be misunderstood and misapplied.

We conclude that four criteria are key to successfully using an explicit strategy: easy to understand, straightforward to apply, useful on the long term and supported by literature.

References

[1]

Howard S. Barrows. 1996. Problem-Based Learning in Medicine and beyond: A Brief Overview. New directions for teaching and learning, Vol. 1996, 68 (1996), 3--12.

[2]

Danièle Bracke. 2004. Un Modèle Fonctionnel Du Tranfert Pour l'éducation .Presses Université Laval, 77--106.

[3]

National Research Council. 2000. How People Learn: Brain, Mind, Experience, and School: Expanded Edition .National Academies Press .

[4]

John W. Creswell. 2012. Analyzing and Interpreting Qualitative Data 4th ed ed.). Pearson, Boston, Chapter 8, 236--246. LB1028.C742 2012

[5]

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.

[6]

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.

[7]

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

[8]

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

Digital Library

[9]

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.

[10]

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, Vol. 28, 4 (2012), 939.

[11]

Cindy E. Hmelo-Silver, Ravit Golan Duncan, and Clark A. Chinn. 2007. Scaffolding and Achievement in Problem-Based and Inquiry Learning: A Response to Kirschner, Sweller, And. Educational psychologist, Vol. 42, 2 (2007), 99--107.

[12]

John R. Hollingsworth and Silvia E. Ybarra. 2017. Explicit Direct Instruction (EDI ): The Power of the Well-Crafted, Well-Taught Lesson .Corwin Press .

[13]

Jean-Claude Kaufmann. 2016. L'entretien Compréhensif-4e Éd. Armand Colin .

[14]

Paul A. Kirschner. 2002. Cognitive Load Theory: Implications of Cognitive Load Theory on the Design of Learning. Learning and Instruction, Vol. 12, 1 (Feb. 2002), 1--10. https://doi.org/10.1016/S0959--4752(01)00014--7

[15]

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, Vol. 41, 2 (June 2006), 75--86. https://doi.org/10.1207/s15326985ep4102_1

[16]

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

Digital Library

[17]

Thomas D. LaToza, Maryam Arab, Dastyni Loksa, and Amy J. Ko. 2020. Explicit Programming Strategies. Empirical Software Engineering, Vol. 25, 4 (July 2020), 2416--2449. https://doi.org/10.1007/s10664-020-09810--1

[18]

Raymond Lister. 2016. Toward a Developmental Epistemology of Computer Programming. In Proceedings of the 11th Workshop in Primary and Secondary Computing Education. ACM, 5--16.

Digital Library

[19]

Raymond Lister, Elizabeth S. Adams, Sue Fitzgerald, William Fone, John Hamer, Morten Lindholm, Robert McCartney, Jan Erik Moström, Kate Sanders, and Otto Sepp"al"a. 2004. A Multi-National Study of Reading and Tracing Skills in Novice Programmers. In ACM SIGCSE Bulletin, Vol. 36. ACM, 119--150.

[20]

Dastyni Loksa and Amy J. Ko. 2016. The Role of Self-Regulation in Programming Problem Solving Process and Success. In Proceedings of the 2016 ACM Conference on International Computing Education Research. ACM, 83--91.

[21]

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.

[22]

Jiali Luo, Laurie Bellows, and Marilyn Grady. 2000. Classroom Management Issues for Teaching Assistants. Research in Higher Education, Vol. 41, 3 (2000), 353--383.

[23]

Andrew Luxton-Reilly, Simon, Ibrahim Albluwi, Brett A. Becker, Michail Giannakos, Amruth N. Kumar, Linda Ott, James Paterson, Michael James Scott, Judy Sheard, and Claudia Szabo. 2018. Introductory Programming: A Systematic Literature Review. In Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2018 Companion ). Association for Computing Machinery, New York, NY, USA, 55--106. https://doi.org/10.1145/3293881.3295779

Digital Library

[24]

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.

[25]

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

Digital Library

[26]

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

Digital Library

[27]

Henk G. Schmidt, Sofie MM Loyens, Tamara Van Gog, and Fred Paas. 2007. Problem-Based Learning Is Compatible with Human Cognitive Architecture: Commentary on Kirschner, Sweller, And. Educational psychologist, Vol. 42, 2 (2007), 91--97.

[28]

Elliot Soloway. 1986. Learning to Program= Learning to Construct Mechanisms and Explanations. Commun. ACM, Vol. 29, 9 (1986), 850--858.

Digital Library

[29]

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 .

[30]

Jeroen J. G. van Merriënboer and John Sweller. 2005. Cognitive Load Theory and Complex Learning : Recent Developments and Future Directions. Educational Psychology Review, Vol. 17, 2 (June 2005), 147--177. https://doi.org/10.1007/s10648-005--3951-0

[31]

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

Marwan SIbrahim MMorrison BStone JYuen TShoop LRebelsky SPrather J(2025)How Good are Large Language Models at Generating Subgoal Labels?Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 210.1145/3641555.3705195(1541-1542)Online publication date: 18-Feb-2025
https://dl.acm.org/doi/10.1145/3641555.3705195
Pereira MCardoso PGreghi JUchôa JSilva R(2024)Exploring a Hybrid Methodology: Experience Report in Introductory Programming for Computer Science and Information Systems CoursesAnais do XXXV Simpósio Brasileiro de Informática na Educação (SBIE 2024)10.5753/sbie.2024.241851(72-84)Online publication date: 4-Nov-2024
https://doi.org/10.5753/sbie.2024.241851
Koç ATaşlıbeyaz E(2024)Coding AnalogyErzincan Üniversitesi Eğitim Fakültesi Dergisi10.17556/erziefd.148576026:4(554-564)Online publication date: 31-Dec-2024
https://doi.org/10.17556/erziefd.1485760
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Index Terms

Tutors' Experiences in Using Explicit Strategies in a Problem-Based Learning Introductory Programming Course
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education
        CS1

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cover image ACM Conferences

ITiCSE '21: Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1

June 2021

611 pages

ISBN:9781450382144

DOI:10.1145/3430665

General Chairs:
Carsten Schulte
Paderborn University, Germany
,
Brett A. Becker
University College Dublin, Ireland
,
Program Chairs:
Monica Divitini
NTNU, Norway
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Erik Barendsen
Radboud University & Open University, The Netherlands

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Published: 26 June 2021

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ITiCSE 2021: 26th ACM Conference on Innovation and Technology in Computer Science Education

June 26 - July 1, 2021

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Cited By

Marwan SIbrahim MMorrison BStone JYuen TShoop LRebelsky SPrather J(2025)How Good are Large Language Models at Generating Subgoal Labels?Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 210.1145/3641555.3705195(1541-1542)Online publication date: 18-Feb-2025
https://dl.acm.org/doi/10.1145/3641555.3705195
Pereira MCardoso PGreghi JUchôa JSilva R(2024)Exploring a Hybrid Methodology: Experience Report in Introductory Programming for Computer Science and Information Systems CoursesAnais do XXXV Simpósio Brasileiro de Informática na Educação (SBIE 2024)10.5753/sbie.2024.241851(72-84)Online publication date: 4-Nov-2024
https://doi.org/10.5753/sbie.2024.241851
Koç ATaşlıbeyaz E(2024)Coding AnalogyErzincan Üniversitesi Eğitim Fakültesi Dergisi10.17556/erziefd.148576026:4(554-564)Online publication date: 31-Dec-2024
https://doi.org/10.17556/erziefd.1485760
Goletti OMens KHermans FHermans FBohrer R(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
https://dl.acm.org/doi/10.1145/3689493.3689986
Nigatu HPickoff-White LCanny JChasins S(2023)Co-Designing for Transparency: Lessons from Building a Document Organization Tool in the Criminal Justice DomainProceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency10.1145/3593013.3594093(1463-1478)Online publication date: 12-Jun-2023
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Ericson BDenny PPrather JDuran RHellas ALeinonen JMiller CMorrison BPearce JRodger SQuille KAlshaigy BBecker BQuille KLaakso M(2022)Parsons Problems and BeyondProceedings of the 2022 Working Group Reports on Innovation and Technology in Computer Science Education10.1145/3571785.3574127(191-234)Online publication date: 27-Dec-2022
https://dl.acm.org/doi/10.1145/3571785.3574127
Goletti OMens KHermans F(2022)An Analysis of Tutors’ Adoption of Explicit Instructional Strategies in an Introductory Programming CourseProceedings of the 22nd Koli Calling International Conference on Computing Education Research10.1145/3564721.3565951(1-12)Online publication date: 17-Nov-2022
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Jia XHermans F(2022)Teaching Quality in Programming Education:Proceedings of the 2022 ACM Conference on International Computing Education Research - Volume 110.1145/3501385.3543962(223-236)Online publication date: 3-Aug-2022
https://dl.acm.org/doi/10.1145/3501385.3543962
Goletti O(2021)Promoting Learning Transfer in Computer Science Education by Training Teachers to use Explicit Programming StrategiesProceedings of the 17th ACM Conference on International Computing Education Research10.1145/3446871.3469776(411-412)Online publication date: 16-Aug-2021
https://dl.acm.org/doi/10.1145/3446871.3469776
Tshukudu ECutts QGoletti OSwidan AHermans F(2021)Teachers’ Views and Experiences on Teaching Second and Subsequent Programming LanguagesProceedings of the 17th ACM Conference on International Computing Education Research10.1145/3446871.3469752(294-305)Online publication date: 16-Aug-2021
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