Encontrando os padrões sequenciais em apresentações orais de estudantes utilizando Sequential Pattern Mining
Resumo
O presente trabalho descreve uma abordagem de Mineração de Padrão Sequencial para identificar as principais sequências corporais em apresentações orais de estudantes durante um determinado curso. Os dados das apresentações dos alunos foram coletados através do uso do Microsoft Kinect e do software Leikelen, totalizando 65 observações. As 7 características coletadas foram utilizadas como informações de entrada na ferramenta SPMF, permitindo a identificação das principais sequências dos apresentadores. Sequências com o atributo Mãos Baixas foram as mais frequentes em todas as apresentações. Verificou-se também que as apresentações 1 e 3 são mais semelhantes em termos de sequência do que com a segunda. A avaliação das sequências pode ser integrada na ferramenta para que o professor possa retornar feedback aos alunos sobre suas posturas.
Palavras-chave:
Mineração de Padrão Sequencial, Apresentações Orais, Microsoft Kinect, Sequências Corporais
Referências
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Fournier-Viger, P., Lin, J.C.-W., Gomariz, A., Gueniche, T., Soltani, A., Deng, Z., and Lam, H.T. (2016). The spmf open-source data mining library version 2. In Joint European conference on machine learning and knowledge discovery in databases, pages 36–40. Springer.
Le, T., Nguyen, M., and Nguyen, T. (2013). Human posture recognition using human skeleton provided by kinect. In 2013 International Conference on Computing, Management and Telecommunications (ComManTel), pages 340–345.
Mehrabian, A. (2017). Nonverbal Communication. Routledge.
Ochoa, X. (2017). Multimodal Learning Analytics. In Lang, C., Siemens, G., Wise, A.F., and Gaševic, D., editors, The Handbook of Learning Analytics, pages 129–141. Society for Learning Analytics Research (SoLAR), Alberta, Canada, 1 edition.
Ochoa, X., Chiluiza, K., Méndez, G., Luzardo, G., Guamán, B., and Castells, J. (2013). Expertise estimation based on simple multimodal features. In Proceedings of the 15th ACM on International Conference on Multimodal Interaction, ICMI’13, pages 583–590, New York, NY, USA. ACM.
Ochoa, X., Worsley, M., Weibel, N., and Oviatt, S. (2016). Multimodal learning analytics data challenges. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge - LAK16. ACM Press.
Raca, M. and Dillenbourg, P. (2013). System for assessing classroom attention. In Proceedings of the Third International Conference on Learning Analytics and Knowledge, LAK’13, pages 265–269, New York, NY, USA. ACM.
Reilly, J., Ravenell, M., and Schneider, B. (2018). Exploring collaboration using motion sensors and multimodal learning analytics. In Proceedings of the 11th International Conference on Educational Data Mining.
Sabin, M., Alrumaih, H., Impagliazzo, J., Lunt, B., Zhang, M., Byers, B., Newhouse, W., Paterson, B., Peltsverger, S., Tang, C., et al. (2017). Curriculum guidelines for baccalaureate degree programs in information technology. Technical report, Technical Report. ACM, New York, NY, USA.
Saraf, P., Sedamkar, R., and Rathi, S. (2015). Prefixspan algorithm for finding sequential pattern with various constraints. International Journal of Applied Information Systems (IJAIS), pages 2249–0868.
Scherer, S., Worsley, M., and Morency, L. (2012). 1st international workshop on multimodal learning analytics. In ICMI’12 - Proceedings of the ACM International Conference on Multimodal Interaction.
York, D. (2013). Investigating a Relationship between Nonverbal Communication and Student Learning. PhD thesis, Lindenwood University.
Zhao, Q. and Bhowmick, S.S. (2003). Sequential pattern mining: A survey. Technical Report CAIS, Nayang Technological University Singapore, 1:26.
Echeverría, V., Avendaño, A., Chiluiza, K., Vásquez, A., and Ochoa, X. (2014). Presentation skills estimation based on video and kinect data analysis. In Proceedings of the 2014 ACM Workshop on Multimodal Learning Analytics Workshop and Grand Challenge, MLA’14, pages 53–60, New York, NY, USA. ACM.
Fournier-Viger, P., Lin, J.C.-W., Gomariz, A., Gueniche, T., Soltani, A., Deng, Z., and Lam, H.T. (2016). The spmf open-source data mining library version 2. In Joint European conference on machine learning and knowledge discovery in databases, pages 36–40. Springer.
Le, T., Nguyen, M., and Nguyen, T. (2013). Human posture recognition using human skeleton provided by kinect. In 2013 International Conference on Computing, Management and Telecommunications (ComManTel), pages 340–345.
Mehrabian, A. (2017). Nonverbal Communication. Routledge.
Ochoa, X. (2017). Multimodal Learning Analytics. In Lang, C., Siemens, G., Wise, A.F., and Gaševic, D., editors, The Handbook of Learning Analytics, pages 129–141. Society for Learning Analytics Research (SoLAR), Alberta, Canada, 1 edition.
Ochoa, X., Chiluiza, K., Méndez, G., Luzardo, G., Guamán, B., and Castells, J. (2013). Expertise estimation based on simple multimodal features. In Proceedings of the 15th ACM on International Conference on Multimodal Interaction, ICMI’13, pages 583–590, New York, NY, USA. ACM.
Ochoa, X., Worsley, M., Weibel, N., and Oviatt, S. (2016). Multimodal learning analytics data challenges. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge - LAK16. ACM Press.
Raca, M. and Dillenbourg, P. (2013). System for assessing classroom attention. In Proceedings of the Third International Conference on Learning Analytics and Knowledge, LAK’13, pages 265–269, New York, NY, USA. ACM.
Reilly, J., Ravenell, M., and Schneider, B. (2018). Exploring collaboration using motion sensors and multimodal learning analytics. In Proceedings of the 11th International Conference on Educational Data Mining.
Sabin, M., Alrumaih, H., Impagliazzo, J., Lunt, B., Zhang, M., Byers, B., Newhouse, W., Paterson, B., Peltsverger, S., Tang, C., et al. (2017). Curriculum guidelines for baccalaureate degree programs in information technology. Technical report, Technical Report. ACM, New York, NY, USA.
Saraf, P., Sedamkar, R., and Rathi, S. (2015). Prefixspan algorithm for finding sequential pattern with various constraints. International Journal of Applied Information Systems (IJAIS), pages 2249–0868.
Scherer, S., Worsley, M., and Morency, L. (2012). 1st international workshop on multimodal learning analytics. In ICMI’12 - Proceedings of the ACM International Conference on Multimodal Interaction.
York, D. (2013). Investigating a Relationship between Nonverbal Communication and Student Learning. PhD thesis, Lindenwood University.
Zhao, Q. and Bhowmick, S.S. (2003). Sequential pattern mining: A survey. Technical Report CAIS, Nayang Technological University Singapore, 1:26.
Publicado
11/11/2019
Como Citar
VIEIRA, Felipe; CECHINEL, Cristian; MUNOZ, Roberto; LEMOS, Robson; WEBER, Tiago.
Encontrando os padrões sequenciais em apresentações orais de estudantes utilizando Sequential Pattern Mining. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 30. , 2019, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 1896-1905.
DOI: https://doi.org/10.5753/cbie.sbie.2019.1896.
