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International Conference in Methodologies and intelligent Systems for Techhnology Enhanced Learning

MIS4TEL 2021: Methodologies and Intelligent Systems for Technology Enhanced Learning, 11th International Conference pp 156–165Cite as

Learning AnalyTICs: Exploring the Hypothetical Learning Trajectories Through Mathematical Games

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 326))

Abstract

Current conditions limit the direct observation of learning processes useful for teachers design the hypothetical learning trajectories. Fortunately, technology makes it possible to complement direct observation through cognitive and emotional monitoring of students during problem-solving processes. Monitoring the learning process open opportunities as tools can do scaffolding, teacher knowledge about the student’s learning process, teacher knowledge about the results of their scaffolding process, and self-knowledge of subjects about their learning processes. In order to develop technologies that engage learning through learning analytics, this document presents three mathematical games: Towers of Hanoi, Four Knights, and The Jumper, with the respective graphs that represent the problem space and a theoretical proposal to analyze the hypothetical learning trajectories generated in the solution of mathematical games. The theoretical proposal is composed of four hypotheses results from analyzing the students’ behavior while solving the game of the towers of Hanoi. All resources are free and available at git-hub.

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Acknowledged

The authors are grateful for the support of the Universidad Distrital Francisco José de Caldas.

Author information

Authors and Affiliations

  1. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    John Páez, Juan Cobos, David Aguirre, Rafael Molina & Lina Lievano

Authors
  1. John Páez
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  2. Juan Cobos
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  3. David Aguirre
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  4. Rafael Molina
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  5. Lina Lievano
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Corresponding author

Correspondence to John Páez .

Editor information

Editors and Affiliations

  1. Edificio Multiusos I+D+I, Sala 24.1, University of Salamanca, Salamanca, Salamanca, Spain

    Fernando De la Prieta

  2. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy

    Rosella Gennari

  3. Department of Computer, Control and Management Engineering, Sapienza University, Rome, Italy

    Marco Temperini

  4. Department of Information Engineering, Computer Science and Mathematics, University of L'Aquila, L'Aquila, L'Aquila, Italy

    Tania Di Mascio

  5. Department of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy

    Pierpaolo Vittorini

  6. Physics and Informatics, KDMFI, Comenius University, Faculty of Mathematics, Bratislava, Slovakia

    Zuzana Kubincova

  7. Computer and Information Technology, University of Craiova, Craiova, Romania

    Elvira Popescu

  8. CIICESI, ESTG, Polytechnic of Porto, Felgueiras, Portugal

    Davide Rua Carneiro

  9. Department of Life, Health and Environmental Sciences, University of L'Aquila, Coppito, Italy

    Loreto Lancia

  10. Università degli Studi di Salerno, Fisciano, Italy

    Agnese Addone

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Páez, J., Cobos, J., Aguirre, D., Molina, R., Lievano, L. (2022). Learning AnalyTICs: Exploring the Hypothetical Learning Trajectories Through Mathematical Games. In: De la Prieta, F., et al. Methodologies and Intelligent Systems for Technology Enhanced Learning, 11th International Conference. MIS4TEL 2021. Lecture Notes in Networks and Systems, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-030-86618-1_16

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