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Assessing Self-regulation, a New Topic in Learning Analytics: Process of Information Objectification

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Machine Learning Paradigms

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 158))

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Abstract

This chapter concerns the theoretical viewpoint regarding the metacognitive process of academic knowledge object-building. An ontological perspective of the study of academic learning will be presented. First, considerations concerning the academic learning process will be stated to establish the main assertions regarding what has been found to be important in academic self-regulated learning. An example of learning math will then be analyzed to illustrate the passage from subjective knowing to objectivization.

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Notes

  1. 1.

    Only knowledge, and not objective knowledge, since for some philosophers, knowledge is by nature objective.

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Author information

Authors and Affiliations

  1. Chapingo Autonomous University, Texcoco, Mexico

    David Martín Santos Melgoza

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  1. David Martín Santos Melgoza
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Correspondence to David Martín Santos Melgoza .

Editor information

Editors and Affiliations

  1. Department of Informatics, University of Piraeus, Piraeus, Greece

    Maria Virvou

  2. Department of Informatics, University of Piraeus, Piraeus, Greece

    Efthimios Alepis

  3. University of Piraeus, Pireas, Greece

    George A. Tsihrintzis

  4. Faculty of Science, Technology and Mathematics, University of Canberra, Canberra, SA, Australia

    Lakhmi C. Jain

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Santos Melgoza, D.M. (2020). Assessing Self-regulation, a New Topic in Learning Analytics: Process of Information Objectification. In: Virvou, M., Alepis, E., Tsihrintzis, G., Jain, L. (eds) Machine Learning Paradigms. Intelligent Systems Reference Library, vol 158. Springer, Cham. https://doi.org/10.1007/978-3-030-13743-4_4

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