Identification of Tutorial Interventions for Virtual Learning Environments
Abstract
The objective of this work is to present which tutorial interventions, based on the classification of the type of error made by the learner, most contributed to a correct solution of exercises. For this purpose, an experiment using the game of mathematical fractions was performed in a real environment. In the game, a tutorial intervention model was implemented which, in addition to indicate the intervention based on error, performs the inference of the learner's emotions allowing to follow his changes in affective states. In this context, the results indicate that the interventions of the type Tips/Conveyed Information and the type Feedback/Explanatory and Goal or objective as the ones that most helped the apprentices to correctly answer the operations.
Keywords:
Tutorial Intervention, Affective States, Intelligent Tutoring Systems
References
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Marczal, D., Direne, A., Pimentel, A., e Krynski, E. M. (2015). FARMA: Uma ferramenta de autoria para objetos de aprendizagem de conceitos matemáticos. In Anais dos Workshops do IV Congresso Brasileiro de Informática na Educação (CBIE 2015).
Marczal, D., Direne, A. I., Pimentel, A. R., Maschio, E., e Borille, A. C. (2016). Metodologia e software educacional para a investigação e remediação de erros conceituais em matemática. Revista Brasileira de Informática na Educação, 24(02):77.
McKendree, J. (1990). Effective feedback content for tutoring complex skills. Human–Computer Interaction, 5(4):381–413.
McLoughlin, C. (2004). Achieving excellence in teaching through scaffolding learner competence. Seeking Educational Excellence, pages 9–10.
Movshovitz-Hadar, N., Zaslavsky, O., e Inbar, S. (1987). An empirical classification model for errors in high school mathematics. Journal for research in mathematics Education, pages 3–14.
Narciss, S. (2013). Designing and evaluating tutoring feedback strategies for digital learning environments on the basis of the interactive tutoring feedback model. Digital Education Review, 23:7–26.
Peng, A. e Luo, Z. (2009). A framework for examining mathematics teacher knowledge as used in error analysis. For the learning of mathematics, 29(3):22–25.
Pour, P. A., Hussain, M. S., AlZoubi, O., D’Mello, S., e Calvo, R. A. (2010). The impact of system feedback on learners’ affective and physiological states. InInternational Conference on Intelligent Tutoring Systems, pages 264–273. Springer.
Shen, L., Le ́on, E., Callaghan, V., e Shen, R. (2007). Exploratory research on an affective e-learning model.
Vanlehn, K. (2006). The behavior of tutoring systems. International journal of artificial intelligence in education, 16(3):227–265.
D’Mello, S., Picard, R. W., e Graesser, A. (2007). Toward an affect-sensitive autotutor. IEEE Intelligent Systems, 22(4):53–61.
Economides, A. A. (2005). Adaptive feedback evaluation. In Proceedings of the 5th WSEAS International Conference on Distance Learning and Web Engineering.
Ekman, P. (1992). An argument for basic emotions.Cognition and Emotion, 6:169–200.
Fleming, M. L. e Levi, W. H. (1993). Instructional message design: Principles from the behavioral and cognitive sciences. Educational technology.
Gottardo, E. e Pimentel, A. (2018). Reconhecimento e adaptação à dinâmica de estados afetivos relacionados à aprendizagem. InAnais do XXIX Simpósio Brasileiro de Informática na Educação (SBIE 2018).
Hannafin, M., Land, S., e Oliver, K. (1999). Open learning environments: Foundations, methods, and models. Instructional-design theories and models: A new paradigm of instructional theory, 2:115–140.
Hume, G., Michael, J., Rovick, A., e Evens, M. (1996). Hinting as a tactic in one-on-one tutoring. Journal of the Learning Sciences, 5(1):23–47.
Leite, D. M., Marczal, D., Krynski, E., Pimentel, A. R., Direne, A., e Reinaldo, F. (2015). Otimizando o processo de ensino e aprendizagem com a arquitetura para desenvolvimento de objetos de aprendizagem - adoa. Simpósio Brasileiro de Informática na Educação - SBIE, 26(1):1002.
Leite, M. D., Pimentel, A. R., e Pietruchinski, M. H. (2012). Remediação de erros baseada em múltiplas representações externas e classificação de erros aplicada a objetos de aprendizagem inteligentes. In Simpósio Brasileiro de Informática na Educação - SBIE, volume 23.
Marczal, D., Direne, A., Pimentel, A., e Krynski, E. M. (2015). FARMA: Uma ferramenta de autoria para objetos de aprendizagem de conceitos matemáticos. In Anais dos Workshops do IV Congresso Brasileiro de Informática na Educação (CBIE 2015).
Marczal, D., Direne, A. I., Pimentel, A. R., Maschio, E., e Borille, A. C. (2016). Metodologia e software educacional para a investigação e remediação de erros conceituais em matemática. Revista Brasileira de Informática na Educação, 24(02):77.
McKendree, J. (1990). Effective feedback content for tutoring complex skills. Human–Computer Interaction, 5(4):381–413.
McLoughlin, C. (2004). Achieving excellence in teaching through scaffolding learner competence. Seeking Educational Excellence, pages 9–10.
Movshovitz-Hadar, N., Zaslavsky, O., e Inbar, S. (1987). An empirical classification model for errors in high school mathematics. Journal for research in mathematics Education, pages 3–14.
Narciss, S. (2013). Designing and evaluating tutoring feedback strategies for digital learning environments on the basis of the interactive tutoring feedback model. Digital Education Review, 23:7–26.
Peng, A. e Luo, Z. (2009). A framework for examining mathematics teacher knowledge as used in error analysis. For the learning of mathematics, 29(3):22–25.
Pour, P. A., Hussain, M. S., AlZoubi, O., D’Mello, S., e Calvo, R. A. (2010). The impact of system feedback on learners’ affective and physiological states. InInternational Conference on Intelligent Tutoring Systems, pages 264–273. Springer.
Shen, L., Le ́on, E., Callaghan, V., e Shen, R. (2007). Exploratory research on an affective e-learning model.
Vanlehn, K. (2006). The behavior of tutoring systems. International journal of artificial intelligence in education, 16(3):227–265.
Published
2020-11-24
How to Cite
ASCARI, Soelaine Rodrigues; GOTTARDO, Ernani; PIMENTEL, Andrey Ricardo.
Identification of Tutorial Interventions for Virtual Learning Environments. In: BRAZILIAN SYMPOSIUM ON COMPUTERS IN EDUCATION (SBIE), 31. , 2020, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 842-851.
DOI: https://doi.org/10.5753/cbie.sbie.2020.842.
