Document Open Access Logo

Promoting Deep Learning Through a Concept Map-Building Collaborative Activity in an Introductory Programming Course

Author João Paulo Barros

PDF
Thumbnail PDF

File

OASIcs.ICPEC.2024.7.pdf
  • Filesize: 0.91 MB
  • 12 pages

Document Identifiers

Author Details

João Paulo Barros
  • Polytechnic Institute of Beja, Portugal
  • Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI), Caparica, Portugal

Funding

  • Barros, João Paulo: This research was funded by Portuguese Agency FCT - Fundação para a Ciência e a Tecnologia no âmbito da Unidade de Investigação CTS - Centro de Tecnologia e Sistemas/UNINOVA/FCT/NOVA, com a referência UIDB/00066/2020.

Cite AsGet BibTex

João Paulo Barros. Promoting Deep Learning Through a Concept Map-Building Collaborative Activity in an Introductory Programming Course. In 5th International Computer Programming Education Conference (ICPEC 2024). Open Access Series in Informatics (OASIcs), Volume 122, pp. 7:1-7:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/OASIcs.ICPEC.2024.7

Abstract

Programming courses focus heavily on problem-solving and coding practice. However, students also face numerous interrelated concepts that should be given more attention to foster more effective and comprehensive learning. Often, students only get an incomplete knowledge of those concepts and their relations as no adequate reflection is promoted or even seen as necessary. The result is a superficial surface learning about essential programming concepts and their relations. This experience report presents a learning activity to promote deep learning of concepts and their relations. The activity challenges students to specify relations between concepts. Students search definitions for a given set of concepts and define relations between those concepts in textual form. To that end, they use a freely available tool that produces a graph from textual descriptions. This tool dramatically simplifies and speeds up the creation of readable graphical representations. Although many different courses can take advantage of the presented activity, we present the activity’s application to an introductory object-oriented programming course. We also present and discuss the student’s feedback, which was highly positive. In the end, we provide recommendations, including possible variations. These can help educators to effectively foster active learning of concepts and their relations in their classrooms.

Subject Classification

ACM Subject Classification
  • Social and professional topics → Computing education
Keywords
  • active-learning
  • ontologies
  • concepts
  • concept maps
  • learning activity
  • object-oriented programming
  • oop
  • pedagogy
  • education

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
    0
    Metadata Views

References

  1. Olusola O. Adesope and John C. Nesbit. A Systematic Review of Research on Collaborative Learning with Concept Maps, pages 238-255. Handbook of Research on Collaborative Learning Using Concept Mapping. IGI Global, Hershey, PA, USA, 2010. URL: https://doi.org/10.4018/978-1-59904-992-2.ch012.
  2. Mordechai Ben-Ari. Constructivism in computer science education. In Proceedings of the Twenty-Ninth SIGCSE Technical Symposium on Computer Science Education, SIGCSE '98, pages 257-261, New York, NY, USA, 1998. Association for Computing Machinery. URL: https://doi.org/10.1145/273133.274308.
  3. Digital Education and Innovation, College of Education and Human Development, University of Minnesota. Videoant, 2023. Available at https://ant.umn.edu/, accessed on 2023/08/15.
  4. John Ellson, Emden Gansner, Lefteris Koutsofios, Stephen C. North, and Gordon Woodhull. Graphviz - open source graph drawing tools. In Petra Mutzel, Michael Jünger, and Sebastian Leipert, editors, Graph Drawing, pages 483-484, Berlin, Heidelberg, 2002. Springer Berlin Heidelberg. Google Scholar
  5. Emden R. Gansner and Stephen C. North. An open graph visualization system and its applications to software engineering. Software: Practice and Experience, 30(11):1203-1233, 2000. URL: https://doi.org/10.1002/1097-024X(200009)30:11<1203::AID-SPE338>3.0.CO;2-N.
  6. Graphviz online, 2022. Available at https://dreampuf.github.io/GraphvizOnline/, accessed on 2023/08/17.
  7. Thomas R. Gruber. Toward principles for the design of ontologies used for knowledge sharing? International Journal of Human-Computer Studies, 43(5):907-928, 1995. URL: https://doi.org/10.1006/ijhc.1995.1081.
  8. Luke Gusukuma, Austin Cory Bart, Dennis Kafura, and Jeremy Ernst. Misconception-driven feedback: Results from an experimental study. In Proceedings of the 2018 ACM Conference on International Computing Education Research, ICER '18, pages 160-168, New York, NY, USA, 2018. Association for Computing Machinery. URL: https://doi.org/10.1145/3230977.3231002.
  9. Bradford Hosack. Videoant: Extending online video annotation beyond content delivery. TechTrends, 54(3):45-49, May 2010. URL: https://doi.org/10.1007/s11528-010-0402-7.
  10. Hypothesis, Inc. Hypothesis, 2023. Available at https://web.hypothes.is/, accessed on 2023/08/15.
  11. ISO/IEC/IEEE 2017. Systems and software engineering - Vocabulary. Standard ISO/IEC/IEEE 24765, International Organization for Standardization, Geneva, CH, 2017. URL: https://standards.iso.org/ittf/PubliclyAvailableStandards/c071952_ISO_IEC_IEEE_24765_2017.zip.
  12. Gregor Kennedy John Biggs, Catherine Tang. Teaching for Quality Learning at University. McGraw Hill, 5 edition, 2022. Google Scholar
  13. Henry Julie, Dumas Bruno, Heymans Patrick, and Leclercq Tony. Object-oriented programming: Diagnosis understanding by identifying and describing novice perceptions. In 2020 IEEE Frontiers in Education Conference (FIE), pages 1-5, 2020. URL: https://doi.org/10.1109/FIE44824.2020.9273990.
  14. Lisa C. Kaczmarczyk, Elizabeth R. Petrick, J. Philip East, and Geoffrey L. Herman. Identifying student misconceptions of programming. In Proceedings of the 41st ACM Technical Symposium on Computer Science Education, SIGCSE '10, pages 107-111, New York, NY, USA, 2010. Association for Computing Machinery. URL: https://doi.org/10.1145/1734263.1734299.
  15. Ming-Che Lee, Ding Yen Ye, and Tzone I Wang. Java learning object ontology. In Fifth IEEE International Conference on Advanced Learning Technologies (ICALT'05), pages 538-542, 2005. URL: https://doi.org/10.1109/ICALT.2005.185.
  16. Henri Lipmanowicz and Keith McCandless. 1-2-4-all - liberating structures including and unleashing everyone, 2023. Available at https://www.liberatingstructures.com/1-1-2-4-all//, accessed on 2023/08/15.
  17. Syeda Fatema Mazumder. Investigating the role of explanative diagrams as a representation of notional machine on a novice programmer’s mental model. In Proceedings of the 17th ACM Conference on International Computing Education Research, ICER 2021, pages 409-410, New York, NY, USA, 2021. Association for Computing Machinery. URL: https://doi.org/10.1145/3446871.3469775.
  18. John C. Nesbit and Olusola O. Adesope. Learning with concept and knowledge maps: A meta-analysis. Review of Educational Research, 76(3):413-448, 2006. URL: https://doi.org/10.3102/00346543076003413.
  19. Joseph D. Novak. Concept mapping: A useful tool for science education. Journal of Research in Science Teaching, 27(10):937-949, 1990. URL: https://doi.org/10.1002/tea.3660271003.
  20. Joseph D Novak and Alberto J Cañas. The origins of the concept mapping tool and the continuing evolution of the tool. Information Visualization, 5(3):175-184, 2006. URL: https://doi.org/10.1057/palgrave.ivs.9500126.
  21. Protégé, 2020. Available at https://protege.stanford.edu/, accessed on 2023/08/17.
  22. Vijayalakshmi Ramasamy, Mourya Reddy Narasareddygari, Gursimran S. Walia, Andrew A. Allen, Debra M. Duke, James D. Kiper, and Debra Lee Davis. A multi-institutional analysis of cs1 students' common misconceptions of key programming concepts. In Maria Virvou, George A. Tsihrintzis, Nikolaos G. Bourbakis, and Lakhmi C. Jain, editors, Handbook on Artificial Intelligence-Empowered Applied Software Engineering: VOL.2: Smart Software Applications in Cyber-Physical Systems, pages 127-144. Springer International Publishing, Cham, 2022. URL: https://doi.org/10.1007/978-3-031-07650-3_8.
  23. Barry Smith. Ontology, chapter 11, pages 153-166. John Wiley & Sons, Ltd, 2004. URL: https://doi.org/10.1002/9780470757017.ch11.
  24. Kristian Stancin, Patrizia Poscic, and Danijela Jaksic. Ontologies in education - state of the art. Education and Information Technologies, 25(6):5301-5320, November 2020. URL: https://doi.org/10.1007/s10639-020-10226-z.
  25. Ling Xu, Ming-Wen Tong, Bin Li, Jiang Meng, and Chen-Yao Fan. Application of concept map in the study of computational thinking training. In 2019 14th International Conference on Computer Science & Education (ICCSE), pages 454-459, 2019. URL: https://doi.org/10.1109/ICCSE.2019.8845505.
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact