A Learning analytics for whom? A reflexion on the retrieval of learning information by the student

Darcio Costa Nogueira Junior; Isadora Valle Sousa; Frederico  Cordeiro Martins; Marta Macedo Kerr Pinheiro

doi:10.31686/ijier.vol9.iss2.2959

Authors

Darcio Costa Nogueira Junior

Universidade FUMEC
Isadora Valle Sousa

FUMEC University
Frederico Cordeiro Martins

FUMEC University
Marta Macedo Kerr Pinheiro

FUMEC University

DOI:

https://doi.org/10.31686/ijier.vol9.iss2.2959

Keywords:

Learning Analytics, Information Retrieval, User Study, Personalized Learning, Adapted Learning

Abstract

The present work aims at addressing how the use of Learning Analytics (LA) has enabled the retrieval of learning information by the student oneself, by analyzing data availability, self-management and student autonomy in learning processes inside and outside virtual environments. The bibliographic research conducted had a qualitative nature and consisted of a narrative literature review anchored in the theoretical foundations of information (information retrieval and representation) and Learning Analytics. Two relevant user case studies that dealt with LA were selected from the researched articles - the first analyzed the user approach in an adapted learning context with LA whereas the second analyzed the user approach in a personalized learning context with LA. One concluded that the student, as an information user, still has little access to an effective retrieval of what was consolidated throughout one’s own learning process. Besides, in relation to the effectiveness of LA, in the context of adapted and personalized learning, there was a perceived increase in student performance with regard to the use of activities and tasks.

References

Alvarenga, L. (2003). Representação do conhecimento na perspectiva da ciência da informação em tempo e espaço digitais. Encontros Bibli, 8 (15). Retrieved from http://www.periodicos.ufsc.br/index.php/eb. DOI: https://doi.org/10.5007/1518-2924.2003v8n15p18

Andrade, A. & Ferreira, S.A. (2016). Aspetos Morfológicos do Tratamento de dados na Gestão Escolar: O Potencial do Analytics. Revista Portuguesa de Investigação Educacional, 16, 289–316.

Araújo, C.A.A. (2012). Paradigma social nos estudos de usuários da informação: abordagem interacionista. Informação & Sociedade: Estudos, 22 (1).

Araújo, C.A.A. (2008). Estudos de usuários: pluralidade teórica, diversidade de objetos. Proceedings of Encontro Nacional de Ciência da Informação, São Paulo, Brasil, 9. Retrieved from http://www.eci.ufmg.br/bogliolo/downloads/ARAUJO%20Enancib%202008.pdf.

Avella, J.T., Kebritchi, M., Nunn, S.G., & Kanai, T. (2016). Learning Analytics Methods, Benefits, and Challenges in Higher Education: A Systematic Literature Review. Online Learning, 20(2), 13–29. Retrieved from https://doi.org/10.24059/olj.v20i2.790. DOI: https://doi.org/10.24059/olj.v20i2.790

Biagiotti, B. & Baldessar, M.J. (2017). Learning Analytics em MOOCs: análise da Big Data Educacional dos cursos Telelab. Paradoxos, 2 (1), 8-20.

Bräscher, M. (2002). A Ambiguidade na Recuperação da Informação. Data Grama Zero: Revista de Ciência da Informação, 3(1). Retrieved from http://www.brapci.inf.br/index.php/article/view/0000001257/e4de1f90f6dced1c96404f008dde12de.

Buckingham Shum, S., & Ferguson, R. (2012). Social Learning Analytics. Educational Technology & Society, 15(3), 3-26.

Capurro, R. & Hjørland, B. (2007). O Conceito de Informação. Perspectivas em Ciência da Informação, 12 (1), 148-207. DOI: https://doi.org/10.1590/S1413-99362007000100012

Capurro, R. (2010). Epistemología y ciencia de la información. ACIMED, 21 (2), 248-265. Retrieved from http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1024-94352010000200008&lng=es&nrm=iso.

Chatti, M.A., Dyckhoff, A.L., Schroeder, U. & Thus, H.A. (2012). Reference Model for Learning Analytics. International Journal of Technology Enhanced Learning, 5, 318-331. DOI: https://doi.org/10.1504/IJTEL.2012.051815

Chatti, M. A. & Muslim, A. (2019). The PERLA Framework: Blending Personalization and Learning Analytics. International Review of Research in Open and Distributed Learning, 20 (1). DOI: https://doi.org/10.19173/irrodl.v20i1.3936

Chiappe, A. & Rodriguez, L.P. (2017). Learning analytics na educação do século XXI: uma revisão. Ensaio, 25 (97), 971-991. Retrieved from http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0104-40362017000400971&lng=pt&nrm=iso. DOI: https://doi.org/10.1590/s0104-40362017002501211

Coll, C. (2012). Atenção à diversidade e qualidade do ensino. Revista Educação Especial, 07-17. Retrieved from https://periodicos.ufsm.br/educacaoespecial/article/view/5001/3030.

Cornelius, I. (2003). Theorizing Information for Information Science. ARIST. n.36, CHAP.9, P.393-421, 2003. Translation: Mário Lúcio Caixeta

Dawson, S., Gasevic, D., Siemens, G. & Joksimovis, S. (2014). Current state and future trends: a citation network analysis of the learning analytics field. Proceedings of the International Conference on Learning Analytics and Knowledge, ACM, New York, USA, 4. pp. 231-240. DOI: https://doi.org/10.1145/2567574.2567585

Kurilovas, E. (2019). Advanced machine learning approaches to personalise learning: learning analytics and decision making. Behaviour & Information Technology, 38(4), 410-421. DOI: https://doi.org/10.1080/0144929X.2018.1539517

Long, P. & Siemens, G. (2011). Penetrating the fog. Educause Review, 46 (5), 31–40.

Mendes-da-Silva, W. (2019). Contribuições e Limitações de Revisões Narrativas e Revisões Sistemáticas na Área de Negócios. Rev. adm. contemp., 23 (2), 1-11, 2019. Retrieved from http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-65552019000200001&lng=en&nrm=iso. DOI: https://doi.org/10.1590/1982-7849rac2019190094

Moissa, B., Gasparini, I. & Kemczinski, A. (2014). Learning Analytics: um mapeamento sistemático. Fortaleza: TISE.

Nogueira, S., Francisco, R., Silva, L., Fernandes, M., & Júnior, C. (2018). Big Data com Learning Analytics para apoiar o Planejamento Pedagógico Acadêmico. In Anais do VII Workshop de Desafios da Computação aplicada à Educação. Porto Alegre: SBC. DOI: https://doi.org/10.5753/desafie.2018.3101

Nunes, I., Silva, W., Laisa, J., Ugulino, F., & Lucena, M. (2016). Learning Analytics como ferramenta para a análise do desempenho dos alunos em Cursos Semipresenciais. Proceedings of the Brazilian Symposium on Computers in Education 27(1), 280. Retrieved from https://br-ie.org/pub/index.php/sbie/article/view/6708/4596. DOI: https://doi.org/10.5753/cbie.sbie.2016.280

Pardo, A., Jovanovic, J., Dawson, S., Gasevic, D. & Mirriahi, N. (2019). Using learning analytics to scale the provision of personalized feedback. British Journal of Educational Technology, 50 (1), 128–138. DOI: https://doi.org/10.1111/bjet.12592

Scheffel, M., Drachsler, H., Stoyanov, S., & Specht, M. (2014). Quality indicators for learning analytics. Journal of Educational Technology & Society, 17(4), 117-132.

Setzer, W. W. (1999). Dado, Informação, Conhecimento e Competência. Data Grama Zero: Revista de Ciência da Informação, 0, 328-338.

Teasley, S. D. (2019). Learning analytics: where information science and the learning sciences meet. Information and Learning Sciences, 120 (1/2), 59-73. DOI: https://doi.org/10.1108/ILS-06-2018-0045

Wendler, R. (2012). The maturity of maturity model research: a systematic mapping study. Information and software technology, 54 (12), 1317-1339. Retrieved from http://www.sciencedirect.com/science/article/pii/S0950584912001334. DOI: https://doi.org/10.1016/j.infsof.2012.07.007

Wise, A. F. (2014). Designing pedagogical interventions to support student use of learning analytics. In: Proceedings of the fourth international conference on learning analytics and knowledge. 2014. p. 203-211. DOI: https://doi.org/10.1145/2567574.2567588

Zhang, J.-H., Zhang, Y.-X., Zou, Q. & Huang, S. (2018). What Learning Analytics Tells Us: Group Behavior Analysis and Individual Learning Diagnosis based on Long-Term and Large-Scale Data. Educational Technology & Society, 21 (2), 245– 258.