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research-article

Analytics-driven redesign of an instructional course

Authors:

Rafael Molina-Carmona,

Carlos Villagrá-Arnedo,

Francisco Gallego-Durán,

Faraón Llorens-LargoAuthors Info & Claims

TEEM 2017: Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality

Article No.: 41, Pages 1 - 7

https://doi.org/10.1145/3144826.3145391

Published: 18 October 2017 Publication History

Abstract

Learning Analytics1 is a powerful tool that provides rich information for students, teachers and academic authorities. There is a wide range of possible applications, and one of them is leveraging the information to improve the instructional design of a course. In this research, we introduce the results of a Learning Analytics engine to improve all the stages of an Action Research experience. We have carried out three iterations: iteration 1, devoted to design an instructional course using an automated learning platform that collects data from the students; iteration 2, focused on the analysis of the individual and aggregated data collected from the students to obtain group behaviors; and iteration 3, currently under way, devoted to improve the structure of the course using the results of the previous iterations. We have made use of some graphical representations of the data that help to understand the aggregated data and to detect important events and moments of intervention. We have detected that the behavior of the students is strongly conditioned by the deadline structure of the course and that there is usually a crucial moment, by halfway of the course, where the situation is tending to stabilize and which is a good moment to reinforce the supervision on the student. Finally, we have stated that low performance students are usually recoverable to the last moment.

References

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Wilfred Carr and Stephen Kemmis. 1986. Becoming critical: education, knowledge, and action research. Falmer Press, London; Philadelphia.

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Francisco José Gallego-Durán, Carlos José Villagra-Arnedo, Faraón Llorens-Largo, and Rafael Molina-Carmona. 2007. PLMan: A Game-Based Learning Activity for Teaching Logic Thinking and Programming. Int. J. Eng. Educ. 33, 2(B) (2007), 807--815.

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Eric Miller. 2004. Analysis Driven Design For Electronic Systems. Phoenix Analysis & Design Technologies. Retrieved July 27, 2017 from http://www.ansys.com/-/media/Ansys/corporate/resourcelibrary/conference-paper/2004-Int-ANSYS-Conf-145.PDF

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Carlos Villagra-Arnedo, Francisco J. Gallego-Durán, Patricia Compañ-Rosique, Faraón Llorens-Largo, and Rafael Molina-Carmona. 2016. Predicting academic performance from behavioural and learning data. Int. J. Des. Nat. Ecodynamics 11, 3 (2016). Retrieved from http://www.witpress.com/journals/dne

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Carlos Villagrá Arnedo, Francisco J. Gallego-Durán, Faraón Llorens Largo, Patricia Compañ, Rosana Satorre Cuerda, and Rafael Molina-Carmona. 2015. Detección precoz de dificultades en el aprendizaje. Herramienta para la predicción del rendimiento de los estudiantes (Early detection of learning difficulties. Tool for predicting student performance). In La Sociedad del Aprendizaje. Actas del III Congreso Internacional sobre Aprendizaje, Innovación y Competitividad. CINAIC 2015. Fundación General de la Universidad Politécnica de Madrid, Madrid, Spain.

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Carlos Villagra-Arnedo, Francisco J. Gallego-Durán, Rafael Molina-Carmona, and Faraón Llorens-Largo. 2015. Boosting the Learning Process with Progressive Performance Prediction. In Design for Teaching and Learning in a Networked World, Gráinne Conole, Tomaž Klobučar, Christoph Rensing, Johannes Konert and Élise Lavoué (eds.). Springer International Publishing, Cham, 638--641. Retrieved January 28, 2016 from http://link.springer.com/10.1007/978-3-319-24258-3_77

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Cited By

Hai-Jew S(2023)What to Keep, What to DiscardHandbook of Research on Revisioning and Reconstructing Higher Education After Global Crises10.4018/978-1-6684-5934-8.ch015(305-318)Online publication date: 20-Jan-2023
https://doi.org/10.4018/978-1-6684-5934-8.ch015
Drugova EZhuravleva IZakharova ULatipov A(2023)Learning analytics driven improvements in learning design in higher education: A systematic literature reviewJournal of Computer Assisted Learning10.1111/jcal.1289440:2(510-524)Online publication date: 23-Oct-2023
https://doi.org/10.1111/jcal.12894
Soares Xavier Freitas ETabosa de Oliveira Tda Fonseca de Souza FCardoso Garcia V(2019)Learning Analytics: A Brief Overview about Applications and its Advantages2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT)10.1109/ICALT.2019.00064(190-191)Online publication date: Jul-2019
https://doi.org/10.1109/ICALT.2019.00064
Show More Cited By

Index Terms

Analytics-driven redesign of an instructional course
1. Applied computing
  1. Education
    1. Computer-managed instruction
    2. Interactive learning environments
2. Information systems
  1. Information systems applications
    1. Decision support systems
      1. Data analytics

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Information & Contributors

Information

Published In

cover image ACM Other conferences

TEEM 2017: Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality

October 2017

723 pages

ISBN:9781450353861

DOI:10.1145/3144826

Editors:
Juan Manuel Dodero
University of Cádiz
,
María Soledad Ibarra Sáiz
University of Cádiz
,
Iván Ruiz Rube
University of Cádiz

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Salamanca: University of Salamanca

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 October 2017

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TEEM 2017

TEEM 2017: 5th International Conference Technological Ecosystems for Enhancing Multiculturality

October 18 - 20, 2017

Cádiz, Spain

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TEEM 2017 Paper Acceptance Rate 84 of 109 submissions, 77%;

Overall Acceptance Rate 496 of 705 submissions, 70%

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Cited By

Hai-Jew S(2023)What to Keep, What to DiscardHandbook of Research on Revisioning and Reconstructing Higher Education After Global Crises10.4018/978-1-6684-5934-8.ch015(305-318)Online publication date: 20-Jan-2023
https://doi.org/10.4018/978-1-6684-5934-8.ch015
Drugova EZhuravleva IZakharova ULatipov A(2023)Learning analytics driven improvements in learning design in higher education: A systematic literature reviewJournal of Computer Assisted Learning10.1111/jcal.1289440:2(510-524)Online publication date: 23-Oct-2023
https://doi.org/10.1111/jcal.12894
Soares Xavier Freitas ETabosa de Oliveira Tda Fonseca de Souza FCardoso Garcia V(2019)Learning Analytics: A Brief Overview about Applications and its Advantages2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT)10.1109/ICALT.2019.00064(190-191)Online publication date: Jul-2019
https://doi.org/10.1109/ICALT.2019.00064
Real-Fernández AMolina-Carmona RPertegal-Felices MLlorens-Largo F(2019)Definition of a Feature Vector to Characterise Learners in Adaptive Learning SystemsResearch & Innovation Forum 201910.1007/978-3-030-30809-4_8(75-89)Online publication date: 29-Oct-2019
https://doi.org/10.1007/978-3-030-30809-4_8
Wong BLi K(2018)Learning Analytics Intervention: A Review of Case Studies2018 International Symposium on Educational Technology (ISET)10.1109/ISET.2018.00047(178-182)Online publication date: Jul-2018
https://doi.org/10.1109/ISET.2018.00047

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