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A Priori Knowledge in Learning Analytics

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Learning Analytics: Fundaments, Applications, and Trends

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 94))

Abstract

Learning Analytics (LA) can be data driven: the process is oriented essentially by data and not according to a theoretical background. In this case, results can be, sometimes, not exploitable. This is the reason why some LA processes are theory driven: based on A Priori Knowledge (APK), on a theoretical background. Here, we investigate the relationship between APK and LA. We propose a “2-level framework” that considers LA as a level 2 learning process and includes five components: stakeholders, goals, data, technical approaches and feedbacks. Based on this framework, a sample of LA related works is analyzed to exhibit how such works relate LA with APK. We show that most of the time the APK used for LA is the learning theory sustaining the student’s learning. However, it can be otherwise and, according to the goal of LA, it is sometimes fruitful to use another theory.

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Notes

  1. 1.

    https://epress.lib.uts.edu.au/journals/index.php/JLA/issue/view/358.

Abbreviations

APK:

A Priori Knowledge

AT:

Activity Theory

BI:

Business Intelligence

EDM:

Educational Data Mining

ITS:

Intelligent Tutoring System

LA:

Learning Analytics

LMS:

Learning Management System

MOOC:

Massive Open Online Course

PLE:

Personal Learning Environments

SNA:

Social Network Analysis

TEL:

Technology Enhanced Learning

ZPD:

Zone of proximal development

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Authors and Affiliations

  1. Université de la Reunion, ESPE de la Réunion, Allée des Aigues Marines, 97400, Saint-Denis, France

    Jean Simon

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  1. Instituto Politécnico Nacional, WOLNM & Escuela Superior de Ingeniería,Mecánica y Eléctrica, Zacatenco, México DF, Mexico

    Alejandro Peña-Ayala

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Simon, J. (2017). A Priori Knowledge in Learning Analytics. In: Peña-Ayala, A. (eds) Learning Analytics: Fundaments, Applications, and Trends. Studies in Systems, Decision and Control, vol 94. Springer, Cham. https://doi.org/10.1007/978-3-319-52977-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-52977-6_7

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