Revisão Sistemática da Literatura sobre Modelos de Visualizações Utilizados para Analisar Fenômenos Educacionais em Plataformas de LMS
Resumo
A visualização de informações referentes aos dados de estudantes auxilia no processo de ensino-aprendizado. Logo, este artigo tem o objetivo de responder a seguinte questão: “Quais são as lacunas da literatura acerca dos trabalhos que apresentam modelos de visualizações no contexto educacional?”. Para isso, essa pesquisa aborda uma revisão sistemática da literatura composta por quatro etapas: revisão terciária, planejamento, condução e interpretação dos resultados. Os resultados apontam carência de trabalhos que utilizam: técnicas de predição, visualizações sofisticadas, e análise dos modelos de visualização para a natureza das variáveis.
Palavras-chave:
Revisão sistemática da literatura, visualização, fenômenos educacionais
Referências
Alves, D. D., Rosa, J. C. S. e Matos, E. F. (2018) “Design Participativo na Comunidade Brasileira de Informática na Educação: um mapeamento sistemático”, In: Congresso Brasileiro De Informática Na Educação, p. 828-837.
Bañeres, D., Rodríguez, M. E., Guerrero-Roldán, Ana E., et al. An Early Warning System to Detect At-Risk Students in Online Higher Education. Applied Sciences, v. 10, n. 13, p. 4427, 2020.
Bodily, R. e Verbert, K. (2017) "Review of Research on Student-Facing Learning Analytics Dashboards and Educational Recommender Systems," in IEEE Transactions on Learning Technologies, pp. 405-418.
Carrillo, R. et al. (2017) “Dashboard for Monitoring Student Engagement in Mind Mapping Activities”, In: IEEE 17th International Conference on Advanced Learning Technologies (ICALT). p. 433-437.
de Leng, B. e Pawelka, F. (2020)“The use of learning dashboards to support complex in-class pedagogical scenarios in medical training: how do they influence students’ cognitive engagement?”, Research and Practice in Technology Enhanced Learning.
Dourado, R. et al. (2018) “Mapeamento Sistemático sobre o uso de Visualização de Dados para Análise Processual da Aprendizagem em Ambientes Virtuais”, In: VII Congresso Brasileiro de Informática na Educação, Fortaleza, CE.
Farahmand, A., Dewan, M.A.A. e Lin, F. (2020) "Student-Facing Educational Dashboard Design for Online Learners," In: IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress, pp. 345-349.
Felizardo, R. et al. (2017) “Revisão sistemática da literatura em engenharia de software : teoria e prática”, In: Elsevier, Rio de Janeiro, Brasil.
Fujii, K. et al. (2018) “Sync Class: Visualization System for In-Class Student Synchronization”. In Proceedings of the 9th Augmented Human International Conference (AH '18), p. 1–8.
Gutiérrez, F., Seipp, K., Ochoa, X., et al. LADA: A learning analytics dashboard for academic advising. Computers in Human Behavior, v. 107, p. 105826, 2020.
Jayashanka, R., Hettiarachchi, E. e Hewagamage, K. P. (2022). “Technology Enhanced Learning Analytics Dashboard in Higher Education”, In: The Electronic Journal of e-Learning, pp. 151-170.
Liu, Z., Levina, V., Frolova, Y. Information Visualization in the Educational Process: Current Trends. International Journal of Emerging Technologies in Learning (iJET), v. 15, n. 13, p. 49, 2020.
Matcha, W. et al. (2019) “A Systematic Review of Empirical Studies on Learning Analytics Dashboards: A Self-Regulated Learning Perspective”, In: IEEE Transactions on Learning Technologies. p. 1-1.
Mubarak, A.A. et al. (2021) “MOOC-ASV: analytical statistical visual model of learners’ interaction in videos of MOOC courses”, In: Interactive Learning Environments”.
Peral, J., Maté, A. e Marco, M. (2016) “Application of Data Mining techniques to identify relevant Key Performance Indicators”, Computer Standards & Interfaces.
Safsouf, Y. Mansouri, K. e Poirier, F. (2021) “Experimental Design of Learning Analysis Dashboards for Teachers and Learners”, In: Proceedings of the Eighth ACM Conference on Learning @ Scale (L@S '21). Association for Computing Machinery, New York, NY, USA, p. 347–350.
Schwendimann, B.A. et al. (2017) "Perceiving Learning at a Glance: A Systematic Literature Review of Learning Dashboard Research," In: IEEE Transactions on Learning Technologies, pp. 30-41.
Sedrakyan, G. et al. (2018) “Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation”, In: Computers in Human Behavior.
Silva, N. A. de L. et al. (2018) “Investigating the suitability of multi-dimensional data visualization as an instrument for assisting distance learning instructors”, In: Congresso Brasileiro De Informática Na Educação, Fortaleza (CE), p. 399-408.
Thiruppugal, M. (2020) “An Investigation Into the Design of Learning Analytic Dashboards (LAD) for the Enhancement of Motivation, Engagement and Achievements in an E-Learning Environment”, In: Proceedings of the 33rd International BCS Human Computer Interaction Conference (BCS HCI 2020).
Ullah, F., Sepasgozer, S., Tahmasebinia, F., et al. Examining the impact of students’ attendance, sketching, visualization, and tutors experience on students’ performance: a case of building structures course in construction management. Construction Economics and Building, v. 20, n. 3, 2020.
Valle, N. et al (2021) “The influence of task-value scaffolding in a predictive learning analytics dashboard on learners' statistics anxiety, motivation, and performance”, In: Computers & Education.
Vieira, C., Parsons, P. e Vetria Byrd, V. (2018) “Visual learning analytics of educational data: A systematic literature review and research agenda”, In: Computers & Education, p. 119-135,
Yang T.-C., Chen M.C. e Chen S.Y. (2018). “ The influences of self-regulated learning support and prior knowledge on improving learning performance”, In: Computers & Education, p. 37-52.
Yizhou, F. et al. (2021), “Learning Analytics to Reveal Links Between Learning Design and Self-Regulated Learning”, In: International Journal of Artificial Intelligence in Education, p. 980–1021.
Zeng, H. et al. (2021) "EmotionCues: Emotion-Oriented Visual Summarization of Classroom Videos," In IEEE Transactions on Visualization and Computer Graphics, p. 3168-3181.
Zheng, J. et al (2020) “Self-regulation and emotion matter: A case study of instructor interactions with a learning analytics dashboard”, In: Computers & Education.
Bañeres, D., Rodríguez, M. E., Guerrero-Roldán, Ana E., et al. An Early Warning System to Detect At-Risk Students in Online Higher Education. Applied Sciences, v. 10, n. 13, p. 4427, 2020.
Bodily, R. e Verbert, K. (2017) "Review of Research on Student-Facing Learning Analytics Dashboards and Educational Recommender Systems," in IEEE Transactions on Learning Technologies, pp. 405-418.
Carrillo, R. et al. (2017) “Dashboard for Monitoring Student Engagement in Mind Mapping Activities”, In: IEEE 17th International Conference on Advanced Learning Technologies (ICALT). p. 433-437.
de Leng, B. e Pawelka, F. (2020)“The use of learning dashboards to support complex in-class pedagogical scenarios in medical training: how do they influence students’ cognitive engagement?”, Research and Practice in Technology Enhanced Learning.
Dourado, R. et al. (2018) “Mapeamento Sistemático sobre o uso de Visualização de Dados para Análise Processual da Aprendizagem em Ambientes Virtuais”, In: VII Congresso Brasileiro de Informática na Educação, Fortaleza, CE.
Farahmand, A., Dewan, M.A.A. e Lin, F. (2020) "Student-Facing Educational Dashboard Design for Online Learners," In: IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress, pp. 345-349.
Felizardo, R. et al. (2017) “Revisão sistemática da literatura em engenharia de software : teoria e prática”, In: Elsevier, Rio de Janeiro, Brasil.
Fujii, K. et al. (2018) “Sync Class: Visualization System for In-Class Student Synchronization”. In Proceedings of the 9th Augmented Human International Conference (AH '18), p. 1–8.
Gutiérrez, F., Seipp, K., Ochoa, X., et al. LADA: A learning analytics dashboard for academic advising. Computers in Human Behavior, v. 107, p. 105826, 2020.
Jayashanka, R., Hettiarachchi, E. e Hewagamage, K. P. (2022). “Technology Enhanced Learning Analytics Dashboard in Higher Education”, In: The Electronic Journal of e-Learning, pp. 151-170.
Liu, Z., Levina, V., Frolova, Y. Information Visualization in the Educational Process: Current Trends. International Journal of Emerging Technologies in Learning (iJET), v. 15, n. 13, p. 49, 2020.
Matcha, W. et al. (2019) “A Systematic Review of Empirical Studies on Learning Analytics Dashboards: A Self-Regulated Learning Perspective”, In: IEEE Transactions on Learning Technologies. p. 1-1.
Mubarak, A.A. et al. (2021) “MOOC-ASV: analytical statistical visual model of learners’ interaction in videos of MOOC courses”, In: Interactive Learning Environments”.
Peral, J., Maté, A. e Marco, M. (2016) “Application of Data Mining techniques to identify relevant Key Performance Indicators”, Computer Standards & Interfaces.
Safsouf, Y. Mansouri, K. e Poirier, F. (2021) “Experimental Design of Learning Analysis Dashboards for Teachers and Learners”, In: Proceedings of the Eighth ACM Conference on Learning @ Scale (L@S '21). Association for Computing Machinery, New York, NY, USA, p. 347–350.
Schwendimann, B.A. et al. (2017) "Perceiving Learning at a Glance: A Systematic Literature Review of Learning Dashboard Research," In: IEEE Transactions on Learning Technologies, pp. 30-41.
Sedrakyan, G. et al. (2018) “Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation”, In: Computers in Human Behavior.
Silva, N. A. de L. et al. (2018) “Investigating the suitability of multi-dimensional data visualization as an instrument for assisting distance learning instructors”, In: Congresso Brasileiro De Informática Na Educação, Fortaleza (CE), p. 399-408.
Thiruppugal, M. (2020) “An Investigation Into the Design of Learning Analytic Dashboards (LAD) for the Enhancement of Motivation, Engagement and Achievements in an E-Learning Environment”, In: Proceedings of the 33rd International BCS Human Computer Interaction Conference (BCS HCI 2020).
Ullah, F., Sepasgozer, S., Tahmasebinia, F., et al. Examining the impact of students’ attendance, sketching, visualization, and tutors experience on students’ performance: a case of building structures course in construction management. Construction Economics and Building, v. 20, n. 3, 2020.
Valle, N. et al (2021) “The influence of task-value scaffolding in a predictive learning analytics dashboard on learners' statistics anxiety, motivation, and performance”, In: Computers & Education.
Vieira, C., Parsons, P. e Vetria Byrd, V. (2018) “Visual learning analytics of educational data: A systematic literature review and research agenda”, In: Computers & Education, p. 119-135,
Yang T.-C., Chen M.C. e Chen S.Y. (2018). “ The influences of self-regulated learning support and prior knowledge on improving learning performance”, In: Computers & Education, p. 37-52.
Yizhou, F. et al. (2021), “Learning Analytics to Reveal Links Between Learning Design and Self-Regulated Learning”, In: International Journal of Artificial Intelligence in Education, p. 980–1021.
Zeng, H. et al. (2021) "EmotionCues: Emotion-Oriented Visual Summarization of Classroom Videos," In IEEE Transactions on Visualization and Computer Graphics, p. 3168-3181.
Zheng, J. et al (2020) “Self-regulation and emotion matter: A case study of instructor interactions with a learning analytics dashboard”, In: Computers & Education.
Publicado
16/11/2022
Como Citar
DE OLIVEIRA, Pamella L. S.; RODRIGUES, Rodrigo Lins; MACIEL, Alexandre M. A..
Revisão Sistemática da Literatura sobre Modelos de Visualizações Utilizados para Analisar Fenômenos Educacionais em Plataformas de LMS. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 33. , 2022, Manaus.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 1006-1015.
DOI: https://doi.org/10.5753/sbie.2022.224997.
