Learning Analytics Desconectada: Um Estudo de Caso em Análise de Produções Textuais
Resumo
A utilização de Learning Analytics (LA) traz consigo diferentes benefícios às instituições de ensino. Porém, exige recursos computacionais e de internet inacessíveis às populações de baixa renda, tornando esta uma tecnologia que pode gerar desigualdade. Nesse contexto, este artigo tem dois objetivos: (i) apresentar o conceito de LA Desconectada, que permite a aplicação dessa tecnologia em ambientes com recursos limitados; e (ii) apresentar uma aplicação real para correção de produção textual de alunos de escolas públicas brasileiras, compatível com este conceito. O aplicativo permite a correção offline de redações escritas no papel e apresenta um dashboard impresso e com informações sumarizadas aos professores.
Palavras-chave:
Learning Analytics Desconectada, Equidade Educacional, Processamento de Linguagem Natural, Educação de Qualidade
Referências
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Gašević, D. (2018). Include us all! directions for adoption of learning analytics in the global south. Learning analytics for the global south, pages 1–22.
He, K., Zhang, X., Ren, S., and Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 770–778.
Jivet, I., Scheffel, M., Specht, M., and Drachsler, H. (2018). License to evaluate: Preparing learning analytics dashboards for educational practice. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge, pages 31–40.
Lim, C. P., Ra, S., Chin, B., and Wang, T. (2020). Information and communication technologies (ict) for access to quality education in the global south: A case study of sri lanka. Education and Information Technologies, 25(4):2447–2462.
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Perine, C. M. and Rowsell, J. (2019). Making it work in the global south: Stories of digital divides in a brazilian context. In Stories from inequity to justice in literacy education, pages 185–202. Routledge.
Puigjaner, R. (2016). Progressing toward digital equity. In IFIP World Information Technology Forum, pages 109–120. Springer.
Rambe, P. and Moeti, M. (2017). Disrupting and democratising higher education provision or entrenching academic elitism: towards a model of moocs adoption at african universities. Educational Technology Research and Development, 65(3):631–651.
Renz, A. and Hilbig, R. (2020). Prerequisites for artificial intelligence in further education: identification of drivers, barriers, and business models of educational technology companies. International Journal of Educational Technology in Higher Education, 17(1):1–21.
Rodríguez, M. R. B. and Cobo, C. (2022). Covid-19 and education in the global south: Emergency remote learning solutions with long-term implications.
Sharma, A. and Jayagopi, D. B. (2018). Automated grading of handwritten essays. In 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), pages 279–284. IEEE.
Sousa, E. B. d., Alexandre, B., Ferreira Mello, R., Pontual Falcão, T., Vesin, B., and Gašević, D. (2021). Applications of learning analytics in high schools: a systematic literature review. Frontiers in Artificial Intelligence, 4:737891.
Stevanim, L. F. et al. (2020). Exclusão nada remota: desigualdades sociais e digitais dificultam a garantia do direito a educação na pandemia.
Thompson, G. (2020). Two thirds of the world’s school-age children have no internet access at home, new unicef-itu report says. [link].
Tlili, A., Burgos, D., Altınay, F., Altınay, Z., Huang, R., and Jemni, M. (2021). Remote special education during covid-19: A combined bibliometric, content and thematic analysis. In 2021 international conference on advanced learning technologies (ICALT), pages 325–329. IEEE.
Varanasi, M. R., Fischetti, J. C., and Smith, M. W. (2018). Analytics framework for k-12 school systems. In Data Leadership for K-12 Schools in a Time of Accountability, pages 206–233. IGI Global.
Zanibbi, R. and Blostein, D. (2012). Recognition and retrieval of mathematical expressions. International Journal on Document Analysis and Recognition (IJDAR), 15(4):331–357
Camelo, R., Justino, S., and de Mello, R. F. L. (2020). Coh-metrix pt-br: Uma api web de analise textual para a educação. In Anais dos Workshops do IX Congresso Brasileiro de Informática na Educação , pages 179–186. SBC.
Devlin, J., Chang, M., Lee, K., and Toutanova, K. (2018). BERT: pre-training of deep bidirectional transformers for language understanding. CoRR, abs/1810.04805.
Freitas, E., Falcão, T. P., and Mello, R. F. (2020). Desmistificando a adoção de learning analytics: um guia conciso sobre ferramentas e instrumentos. Sociedade Brasileira de Computação.
Gaftandzhieva, S., Docheva, M., and Doneva, R. (2020). A comprehensive approach to learning analytics in Bulgarian school education. Education and Information Technologies.
Gašević, D. (2018). Include us all! directions for adoption of learning analytics in the global south. Learning analytics for the global south, pages 1–22.
He, K., Zhang, X., Ren, S., and Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 770–778.
Jivet, I., Scheffel, M., Specht, M., and Drachsler, H. (2018). License to evaluate: Preparing learning analytics dashboards for educational practice. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge, pages 31–40.
Lim, C. P., Ra, S., Chin, B., and Wang, T. (2020). Information and communication technologies (ict) for access to quality education in the global south: A case study of sri lanka. Education and Information Technologies, 25(4):2447–2462.
Matias, T. P., Imperador, A. M., Botezelli, L., Riondet-Costa, D. R. T., de Oliveira Costa, V. A., and de Alcantara Moreira, L. (2022). Vulnerable populations in south america and facing the pandemic: what can our experiences reveal to the world? Research, Society and Development, 11(4):e59511427924–e59511427924.
Ossai, A. (2022). Sustainable development goal four (sdg4): Challenges and the way forward. International Journal of Advance Research in Education & Literature, 8(2).
Patel, N., Thakkar, M., Rabadiya, B., Patel, D., Malvi, S., Sharma, A., and Lomas, D. (2022). Equitable access to intelligent tutoring systems through paper-digital integration. In Crossley, S. and Popescu, E., editors, Intelligent Tutoring Systems, pages 255–263, Cham. Springer International Publishing.
Perine, C. M. and Rowsell, J. (2019). Making it work in the global south: Stories of digital divides in a brazilian context. In Stories from inequity to justice in literacy education, pages 185–202. Routledge.
Puigjaner, R. (2016). Progressing toward digital equity. In IFIP World Information Technology Forum, pages 109–120. Springer.
Rambe, P. and Moeti, M. (2017). Disrupting and democratising higher education provision or entrenching academic elitism: towards a model of moocs adoption at african universities. Educational Technology Research and Development, 65(3):631–651.
Renz, A. and Hilbig, R. (2020). Prerequisites for artificial intelligence in further education: identification of drivers, barriers, and business models of educational technology companies. International Journal of Educational Technology in Higher Education, 17(1):1–21.
Rodríguez, M. R. B. and Cobo, C. (2022). Covid-19 and education in the global south: Emergency remote learning solutions with long-term implications.
Sharma, A. and Jayagopi, D. B. (2018). Automated grading of handwritten essays. In 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), pages 279–284. IEEE.
Sousa, E. B. d., Alexandre, B., Ferreira Mello, R., Pontual Falcão, T., Vesin, B., and Gašević, D. (2021). Applications of learning analytics in high schools: a systematic literature review. Frontiers in Artificial Intelligence, 4:737891.
Stevanim, L. F. et al. (2020). Exclusão nada remota: desigualdades sociais e digitais dificultam a garantia do direito a educação na pandemia.
Thompson, G. (2020). Two thirds of the world’s school-age children have no internet access at home, new unicef-itu report says. [link].
Tlili, A., Burgos, D., Altınay, F., Altınay, Z., Huang, R., and Jemni, M. (2021). Remote special education during covid-19: A combined bibliometric, content and thematic analysis. In 2021 international conference on advanced learning technologies (ICALT), pages 325–329. IEEE.
Varanasi, M. R., Fischetti, J. C., and Smith, M. W. (2018). Analytics framework for k-12 school systems. In Data Leadership for K-12 Schools in a Time of Accountability, pages 206–233. IGI Global.
Zanibbi, R. and Blostein, D. (2012). Recognition and retrieval of mathematical expressions. International Journal on Document Analysis and Recognition (IJDAR), 15(4):331–357
Publicado
16/11/2022
Como Citar
FREITAS, Elyda et al.
Learning Analytics Desconectada: Um Estudo de Caso em Análise de Produções Textuais. In: WORKSHOP DE APLICAÇÕES PRÁTICAS DE LEARNING ANALYTICS EM INSTITUIÇÕES DE ENSINO NO BRASIL (WAPLA), 1. , 2022, Manaus.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 40-49.
DOI: https://doi.org/10.5753/wapla.2022.226823.
