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The alignment between learning analytics and the general data protection regulation
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Keywords

Systematic literature review
General data protection regulation
Learning analytics

How to Cite

BASSANI, Rafael Vescovi; CAZELLA, Sílvio César. The alignment between learning analytics and the general data protection regulation: a systematic literature review. ETD - Educação Temática Digital, Campinas, SP, v. 23, n. 4, p. 1022–1040, 2021. DOI: 10.20396/etd.v23i4.8658829. Disponível em: https://periodicos.sbu.unicamp.br/ojs/index.php/etd/article/view/8658829. Acesso em: 5 jul. 2024.

Abstract

The growth of the distance education modality allows researchers to present varied studies related to the theme. Together with these studies emerge concepts such as Learning Analytics (LA). The LA is an area that will analyze, measure, collect and relate student data in their contexts. However, the use of this data brings with it a new concern regarding the protection, privacy and correct use of the data. The European Union already finds personal data protection legislation with a broad General Data Protection Regulation (GDPR). In Brazil, the legislation available today is available in the law called - Lei Geral de Proteção de Dados Pessoais (LGPDP) and its effect begins in August 2020. This article aims to present the result of a Systematic Literature Review (RSL) that search to identify academic research related to Learning Analytics (LA) and General Data Protection Regulation (GDPR). After applying the inclusion and exclusion requirements of the selected articles ten articles were selected for analysis. With the analysis it is possible to identify an alignment between the LA and GDPR showing that LA should follow the guidelines of GDPR.

https://doi.org/10.20396/etd.v23i4.8658829
PDF (Português (Brasil))

References

ALTMAN, I. The environment and social behavior: privacy, personal space, territory, and crowding. Monterey, California 93940: Brooks/Cole Publishing Company, 1975.

ANTUNES, N.; BALBY, L.; FIGUEIREDO, F.; LOURENCO, N.; MEIRA JR, W.; SANTOS, W. Fairness and transparency of machine learning for trustworthy cloud services. 2018, 48th Annual IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS WORKSHOPS (DSN-W), 2018, p. 188-193, Doi: 10.1109/DSN-W.2018.00063.

BUTTERWORTH, M. The ICO and artificial intelligence: The role of fairness in the GDPR framework. Computer Law & Security Review, v.34, 2018, p.257-268.

CASTILHO, Carlos Albano Volkmer de. O processo colaborativo na produção de informações: gênese, sistemas e possíveis aplicações no jornalismo comunitário. 2009. Dissertação (Mestrado) - Universidade Federal de Santa Catarina. Florianópolis: UFSC, 2009.

CHATTI, M. A.; DYCKHOFF, A. L.; SCHROEDER, U.; THüS, H. A. Reference model for learning analytics. International Journal of Technology Enhanced Learning, Geneva, Switzerland, v.4, n.5/6, p. 318-331, Jan. 2012.

CHI ZHOU, Amelie Chi et al. Privacy regulation aware process mapping in geo-distributed cloud data centers. IEEE Transactions on Parallel and Distributed Systems, v. 30, n. 8, p. 1872-1888, 2019.

DRESCH, A.; LACERDA, D. P.; ANTUNES JUNIOR, J. A. V. Design Science Research: método de pesquisa para avanço da ciência e tecnologia. Porto Alegre: Bookmann, 2015.

HACK, Josias Ricardo. Introdução à educação a distância. Florianópolis: LLV/CCE/UFSC, 2011.

HOEL, T.; CHEN, W. Data Sharing for Learning Analytics – designing conceptual artefacts and processes to foster interoperability. 24th INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION, 24th. Proceedings… India: Asia-Pacific Society for Computers in Education, 2016.

HOEL, Tore; GRIFFITHS, Dai; CHEN, Weiqin. The influence of data protection and privacy frameworks on the design of learning analytics systems. In: INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE, 7., 2017. p. 243-252. Proceedings of the...New York, USA: ACM Press; 2017

JOHNSON, L.; SMITH, R.; WILLIS, H.; LEVINE, A.; HAYWOOD, K. The NMC Horizon Report: 2011 Higher Education Edition. New Media Consortium, 2011.

KITTO, K.; KNIGHT S. Practical ethics for building learning analytics. British Journal of Educational Technology, v.0, n.2019, p. 1-16. DOI: 10.1111/bjet.12868.

KITCHENHAM, B. A. Guidelines for performing Systematic Literature Reviews in Software Engineering. 2007.

KINDT, E. J. Why research may no longer be the same: about the territorial scope of the New Data Protection Regulation. Computer Law & Security Review, v.32, p.729-74, 2016.

KOEDINGER, Kenneth et al. An open repository and analysis tools for fine-grained, longitudinal learner data. In: EDUCATIONAL DATA MINING 2008: INTERNATIONAL CONFERENCE ON EDUCATIONAL DATA MINING, 1st., 2008. Proceedings…, 2008. p. 157-166.

MOISSA, B.; GASPARINI, I.; KEMCZINSKI, A. Educational data mining versus learning analytics: estamos reinventando a roda? Um mapeamento sistemático. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO, 26., 2015. Anais..., 2015. p.1167

SIEMENS, G.; BAKER, R. Learning analytics and educational data mining: towards communication and collaboration. In: Proceedings of the 2nd INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS AND KNOWLEDGE, 2., 2012. Anais…2012. p. 252-254, 2012.

SIEMENS, G., LONG, P. Penetrating the fog: analytics in learning and education. EDUCAUSE Review, v.46, n.5, 2011.

SONI, G.; KODALI, R. A critical analysis of supply chain management content in empirical Research. Business Process Management Journal, v. 17, n. 2, p. 238-266. 2011.

THORPE, R. et al. Using knowledge within small and medium sized firms: a sys-tematic review of the evidence. International Journal of Management Reviews, v. 7, n. 4, p. 257-281, 2005.

WACHTER, S. Normative challenges of identification in the Internet of Things: Privacy, profiling, discrimination, and the GDPR. Computer Law & Security Review, v.34, (2018), p.436-449.

WIERINGA, J.; MA, XIAO.; REUTTERER, T.; RISSELADA, H.; SKIERA, B. Data analytics in a privacy-concerned world. Journal of Business Research, https://doi.org/10.1016/j.jbusres.2019.05.005 .

WILLS, D. B. The technology foresight activities of European Union data protection authorities. Technological Forecasting & Social Change, v.116 (2017), p.142-150.

YU, X.; ZHAO, Y. Dualism in data protection: balancing the right to personal data and the data property right. Computer Law & Security Review, v. 35, 105318, 2019

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