Detecção de Traços de Personalidade em Textos para Apoiar a Formação de Grupos para Colaboração
Resumo
Com o objetivo de fornecer um meio de detectar traços de personalidade de forma transparente e disponibilizar esta informação para apoiar estratégias de agrupamento para colaboração, avaliamos textos escritos por alunos que podem ser capturados, por exemplo, em ambientes virtuais de aprendizagem. Os resultados da avaliação de textos indicam como mais eficaz para inferir os traços de personalidade dos algoritmos M5P, SMO e LWL. Também avaliamos estudantes trabalhando em grupo para entender como eles se organizam para atingir uma meta e formar uma base de combinações de alunos para apoiar o agrupamento usando os traços de personalidade.
Palavras-chave:
Traços de Personalidade, Agrupamento, Colaboração, Algoritmos, Avaliação de Textos
Referências
Akhtar, R., Boustani, L., Tsivrikos, D., e Chamorro-Premuzic, T. (2015). The engageable personality: Personality and trait EI as predictors of work engagement. Personality and Individual Differences, 73:44–49.
Alavi, M. (1994). Computer-mediated collaborative learning: An empirical evaluation. Journal MIS Quarterly, 18:159–174.
Altanopoulou, P. e Tselios, N. (2015). How does personality affect wiki-mediated learning? In Proceedings of International Conference on Interactive Mobile and Communication Technologies and Learning, pages 16–18.
Andrade, J.M. (2008). Evidências de Validade do Inventário dos Cinco Grandes Fatores de Personalidade para o Brasil. PhD thesis, Instituto de Psicologia - Universidade de Brasília.
Balage Filho, P.P., Aluísio, S.M., e Pardo, T.A.S. (2013). An evaluation of the brazilian portuguese liwc dictionary for sentiment analysis. In Proceedings of Brazilian Symposium in Information and Human Language Technology, pages 215–219.
Bozionelos, G. (2017). The relationship of the big-five with workplace network resources: More quadratic than linear. Personality and Individual Differences, 104:374–378.
Goldberg, L.R. (1981). Language and individual differences: The search for universal in personality lexicons. Review of personality and social psychology, 2:141–166.
Hron, A. e Friedrich, H.F. (2003). A review of web-based collaborative learning: factors beyond technology. Journal of Computer Assisted Learning, 19:70–79.
Hron, A. e Friedrich, H. F. (2003). A review of web-based collaborative learning: factors beyond technology. Journal of Computer Assisted Learning, 19:70–79.
John, O. e Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. Handbook of personality: Theory and research, 2:102–138.
Machado, A.A., Longhi, M.T., Nunes, M.A.S.N., e Pardo, T.A.S. (2015). Personalitatem lexicon: Um léxico em português brasileiro para mineração de traços de personalidade em textos. In Anais do XXVI Simpósio Brasileiro de Informática na Educação, pages 1122–1126.
Magnisalis, I., Demetriadis, S., e Karakostas, A. (2011). Adaptive and intelligent systems for collaboration learning support: A review of the field. IEEE Transactions on Learning Technologies, 4:5–20.
Manske, S., Hecking, T., Chounta, I., e Hoppe, H. (2015). Using differences to make a difference: a study on heterogeneity of learning groups. In Proceedings of International Conference on Computer Supported Collaborative Learning, pages 182–189.
Neto, A.T., Ferreira, T., e Fernandes, M. (2017). Development of a big-five personality traits classification approach via analysis of texts in brazilian portuguese. In Anais do IV WICSI-XIII Simpósio Brasileiro de Sistema de Informação, pages 57–60.
Paim, A., Camati, R., e Enembreck, F. (2016). Inferência de personalidade a partir de textos em português utilizando léxico linguístico e aprendizagem de máquina. In Anais do XIII Encontro Nacional de Inteligência Artificial e Computacional, pages 481–492.
Papamitsiou, Z. e Economides, A.A. (2014). The effect of personality traits on students’ performance during computer-based testing: a study of the big five inventory with temporal learning analytics. In Proceedings of IEEE 14th International Conference on Advanced Learning Technologies, pages 378–382.
Roberts, S.G.B., Wilson, R., Fedurek, P., e Dunbar, R.I.M. (2008). Individual differences and personal social network size and structure. Personality and Individual Differences, 44:954–964.
Spoelstra, H., Van Rosmalen, P., Houtmans, T., e Sloep, P. (2015). Team formation instruments to enhance learner interactions in open learning environments. Computers in Human Behavior, 45:11–20.
Tausczik, Y.R. e Pennebaker, J.W. (2010). The psychological meaning of words: Liwc and computerized text analysis methods. Journal of Language and Social Psychology, 29:24–54.
Vygotsky, L. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge, MA.
Wen, M., Yang, D., e Rose, C.P. (2014). Linguistic reflections of student engagement in massive open online courses. In Proceedings of the International Conference on Weblogs and Social Media.
Wu, W. e Chen, L. (2015). Implicit acquisition of user personality for augmenting movie recommendations. In Proceedings of International Conference on User Modeling, Adaptation and Personalization, pages 302–314.
Alavi, M. (1994). Computer-mediated collaborative learning: An empirical evaluation. Journal MIS Quarterly, 18:159–174.
Altanopoulou, P. e Tselios, N. (2015). How does personality affect wiki-mediated learning? In Proceedings of International Conference on Interactive Mobile and Communication Technologies and Learning, pages 16–18.
Andrade, J.M. (2008). Evidências de Validade do Inventário dos Cinco Grandes Fatores de Personalidade para o Brasil. PhD thesis, Instituto de Psicologia - Universidade de Brasília.
Balage Filho, P.P., Aluísio, S.M., e Pardo, T.A.S. (2013). An evaluation of the brazilian portuguese liwc dictionary for sentiment analysis. In Proceedings of Brazilian Symposium in Information and Human Language Technology, pages 215–219.
Bozionelos, G. (2017). The relationship of the big-five with workplace network resources: More quadratic than linear. Personality and Individual Differences, 104:374–378.
Goldberg, L.R. (1981). Language and individual differences: The search for universal in personality lexicons. Review of personality and social psychology, 2:141–166.
Hron, A. e Friedrich, H.F. (2003). A review of web-based collaborative learning: factors beyond technology. Journal of Computer Assisted Learning, 19:70–79.
Hron, A. e Friedrich, H. F. (2003). A review of web-based collaborative learning: factors beyond technology. Journal of Computer Assisted Learning, 19:70–79.
John, O. e Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. Handbook of personality: Theory and research, 2:102–138.
Machado, A.A., Longhi, M.T., Nunes, M.A.S.N., e Pardo, T.A.S. (2015). Personalitatem lexicon: Um léxico em português brasileiro para mineração de traços de personalidade em textos. In Anais do XXVI Simpósio Brasileiro de Informática na Educação, pages 1122–1126.
Magnisalis, I., Demetriadis, S., e Karakostas, A. (2011). Adaptive and intelligent systems for collaboration learning support: A review of the field. IEEE Transactions on Learning Technologies, 4:5–20.
Manske, S., Hecking, T., Chounta, I., e Hoppe, H. (2015). Using differences to make a difference: a study on heterogeneity of learning groups. In Proceedings of International Conference on Computer Supported Collaborative Learning, pages 182–189.
Neto, A.T., Ferreira, T., e Fernandes, M. (2017). Development of a big-five personality traits classification approach via analysis of texts in brazilian portuguese. In Anais do IV WICSI-XIII Simpósio Brasileiro de Sistema de Informação, pages 57–60.
Paim, A., Camati, R., e Enembreck, F. (2016). Inferência de personalidade a partir de textos em português utilizando léxico linguístico e aprendizagem de máquina. In Anais do XIII Encontro Nacional de Inteligência Artificial e Computacional, pages 481–492.
Papamitsiou, Z. e Economides, A.A. (2014). The effect of personality traits on students’ performance during computer-based testing: a study of the big five inventory with temporal learning analytics. In Proceedings of IEEE 14th International Conference on Advanced Learning Technologies, pages 378–382.
Roberts, S.G.B., Wilson, R., Fedurek, P., e Dunbar, R.I.M. (2008). Individual differences and personal social network size and structure. Personality and Individual Differences, 44:954–964.
Spoelstra, H., Van Rosmalen, P., Houtmans, T., e Sloep, P. (2015). Team formation instruments to enhance learner interactions in open learning environments. Computers in Human Behavior, 45:11–20.
Tausczik, Y.R. e Pennebaker, J.W. (2010). The psychological meaning of words: Liwc and computerized text analysis methods. Journal of Language and Social Psychology, 29:24–54.
Vygotsky, L. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge, MA.
Wen, M., Yang, D., e Rose, C.P. (2014). Linguistic reflections of student engagement in massive open online courses. In Proceedings of the International Conference on Weblogs and Social Media.
Wu, W. e Chen, L. (2015). Implicit acquisition of user personality for augmenting movie recommendations. In Proceedings of International Conference on User Modeling, Adaptation and Personalization, pages 302–314.
Publicado
30/10/2017
Como Citar
FERREIRA, Taís Borges; FERNANDES, Márcia Aparecida.
Detecção de Traços de Personalidade em Textos para Apoiar a Formação de Grupos para Colaboração. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 28. , 2017, Recife/PE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 1627-1636.
DOI: https://doi.org/10.5753/cbie.sbie.2017.1627.
