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Discovery Model Based on Analogies for Teaching Computer Programming

Author

Listed:
  • Javier Alejandro Jiménez Toledo

    (Faculty of Engineering, Systems Engineering, CESMAG University, Pasto 520001, Colombia)

  • César A. Collazos

    (System Department, Faculty of Electronic Engineering and Telecommunications, University of Cauca, Popayán 190001, Colombia)

  • Manuel Ortega

    (Department of Technologies and Information Systems, Higher School of Informatics, Castilla-La Mancha University, 13001 Ciudad Real, Spain)

Abstract

Teaching the fundamentals of computer programming in a first course (CS1) is a complex activity for the professor and is also a challenge for them. Nowadays, there are several teaching strategies for dealing with a CS1 at the university, one of which is the use of analogies to support the abstraction process that a student needs to carry for the appropriation of fundamental concepts. This article presents the results of applying a discovery model that allowed for the extraction of patterns, linguistic analysis, textual analytics, and linked data when using analogies for teaching the fundamental concepts of programming by professors in a CS1 in university programs that train software developers. For that reason, a discovery model based on machine learning and text mining was proposed using natural language processing techniques for semantic vector space modeling, distributional semantics, and the generation of synthetic data. The discovery process was carried out using nine supervised learning methods, three unsupervised learning methods, and one semi-supervised learning method involving linguistic analysis techniques, text analytics, and linked data. The main findings showed that professors include keywords, which are part of the technical computer terminology, in the form of verbs in the statement of the analogy and combine them in quantitative contexts with neutral or positive phrases, where numerical examples, cooking recipes, and games were the most used categories. Finally, a structure is proposed for the construction of analogies to teach programming concepts and this was validated by the professors and students.

Suggested Citation

  • Javier Alejandro Jiménez Toledo & César A. Collazos & Manuel Ortega, 2021. "Discovery Model Based on Analogies for Teaching Computer Programming," Mathematics, MDPI, vol. 9(12), pages 1-21, June.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:12:p:1354-:d:573299
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    References listed on IDEAS

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    1. Oecd, 2015. "Teaching with technology," Teaching in Focus 12, OECD Publishing.
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    Cited by:

    1. Carmen Lacave & Ana Isabel Molina, 2023. "Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education," Mathematics, MDPI, vol. 11(6), pages 1-4, March.
    2. Pawan Saxena & Sanjay Kumar Singh & Gopal Gupta, 2023. "Achieving Effective Learning Outcomes through the Use of Analogies in Teaching Computer Science," Mathematics, MDPI, vol. 11(15), pages 1-18, July.

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