Towards a Maturity Model for Learning Analytics adoption an overview of its levels and areas

Elyda Freitas; Fernando Fonseca; Vinicius Garcia; Rafael Ferreira; Dragan Gasevic

doi:10.1109/ICALT49669.2020.00059

Towards a Maturity Model for Learning Analytics adoption an overview of its levels and areas

Elyda Freitas, Fernando Fonseca, Vinicius Garcia, Rafael Ferreira, Dragan Gasevic

Department of Data Science & AI

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

Abstract

Learning Analytics is a new field in education whose adoption can bring benefits for teaching and learning processes. However, many higher education institutions may not be ready to start using learning analytics due to challenges such as organizational culture, infrastructure, and privacy. In this context, Maturity Models (MMs) can support institutions to systematize their processes, enabling them to progress successively in the learning analytics adoption. MMs are used in different fields to support the improvement of processes, describing them in terms of maturity levels, and identifying enhancements that could lead an organization to higher levels of such maturity. Thus, this paper presents an outline of a MM for Learning Analytics adoption in higher education institutions, describing its levels and areas, together with its development methodology.

Original language	English
Title of host publication	Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020
Editors	Maiga Chang, Demetrios G Sampson, Ronghuai Huang, Danial Hooshyar, Nian-Shing Chen, Kinshuk , Margus Pedaste
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	180-184
Number of pages	5
ISBN (Electronic)	9781728160900
ISBN (Print)	9781728160917
DOIs	https://doi.org/10.1109/ICALT49669.2020.00059
Publication status	Published - 2020
Event	IEEE International Conference on Advanced Learning Technologies 2020 - Virtual, Online, Estonia Duration: 6 Jul 2020 → 9 Jul 2020 Conference number: 20th https://ieeexplore.ieee.org/xpl/conhome/9146898/proceeding (Proceedings) https://icalt2020.ut.ee/home-0 (Website)

Publication series

Name	Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020
Publisher	The Institute of Electrical and Electronics Engineers, Inc.
ISSN (Print)	2161-3761
ISSN (Electronic)	2161-377X

Conference

Conference	IEEE International Conference on Advanced Learning Technologies 2020
Abbreviated title	ICALT 2020
Country/Territory	Estonia
City	Virtual, Online
Period	6/07/20 → 9/07/20
Internet address	https://ieeexplore.ieee.org/xpl/conhome/9146898/proceeding (Proceedings) https://icalt2020.ut.ee/home-0 (Website)

Keywords

Adoption
Learning analytics
Maturity model
Policy development

Access to Document

10.1109/ICALT49669.2020.00059

Cite this

Freitas, E., Fonseca, F., Garcia, V., Ferreira, R., & Gasevic, D. (2020). Towards a Maturity Model for Learning Analytics adoption an overview of its levels and areas. In M. Chang, D. G. Sampson, R. Huang, D. Hooshyar, N-S. Chen, K., & M. Pedaste (Eds.), Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020 (pp. 180-184). (Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICALT49669.2020.00059

Freitas, Elyda ; Fonseca, Fernando ; Garcia, Vinicius ; Ferreira, Rafael ; Gasevic, Dragan. / Towards a Maturity Model for Learning Analytics adoption an overview of its levels and areas. Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020. editor / Maiga Chang ; Demetrios G Sampson ; Ronghuai Huang ; Danial Hooshyar ; Nian-Shing Chen ; Kinshuk ; Margus Pedaste. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2020. pp. 180-184 (Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020).

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abstract = "Learning Analytics is a new field in education whose adoption can bring benefits for teaching and learning processes. However, many higher education institutions may not be ready to start using learning analytics due to challenges such as organizational culture, infrastructure, and privacy. In this context, Maturity Models (MMs) can support institutions to systematize their processes, enabling them to progress successively in the learning analytics adoption. MMs are used in different fields to support the improvement of processes, describing them in terms of maturity levels, and identifying enhancements that could lead an organization to higher levels of such maturity. Thus, this paper presents an outline of a MM for Learning Analytics adoption in higher education institutions, describing its levels and areas, together with its development methodology. ",

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Freitas, E, Fonseca, F, Garcia, V, Ferreira, R & Gasevic, D 2020, Towards a Maturity Model for Learning Analytics adoption an overview of its levels and areas. in M Chang, DG Sampson, R Huang, D Hooshyar, N-S Chen, K & M Pedaste (eds), Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020. Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 180-184, IEEE International Conference on Advanced Learning Technologies 2020, Virtual, Online, Estonia, 6/07/20. https://doi.org/10.1109/ICALT49669.2020.00059

Towards a Maturity Model for Learning Analytics adoption an overview of its levels and areas. / Freitas, Elyda; Fonseca, Fernando; Garcia, Vinicius; Ferreira, Rafael; Gasevic, Dragan.

Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020. ed. / Maiga Chang; Demetrios G Sampson; Ronghuai Huang; Danial Hooshyar; Nian-Shing Chen; Kinshuk; Margus Pedaste. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2020. p. 180-184 (Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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Freitas E, Fonseca F, Garcia V, Ferreira R, Gasevic D. Towards a Maturity Model for Learning Analytics adoption an overview of its levels and areas. In Chang M, Sampson DG, Huang R, Hooshyar D, Chen N-S, K, Pedaste M, editors, Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2020. p. 180-184. (Proceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020). https://doi.org/10.1109/ICALT49669.2020.00059

Towards a Maturity Model for Learning Analytics adoption an overview of its levels and areas

Abstract

Publication series

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Keywords

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