Affect Dynamics and Behavioral Patterns in Intelligent Learning Environments
Resumo
Esta pesquisa examina a interação entre emoções e comportamentos de aprendizagem em Ambientes de Aprendizagem Inteligentes (ILEs) utilizando dados de estudantes brasileiros. Analisamos as associações entre emoções—incluindo confusão, frustração, tédio e engajamento—e comportamentos de aprendizagem, focando na influência do gênero e na duração dessas emoções e comportamentos. Dados de 30 estudantes em um sistema tutor baseado em etapas de matemática foram anotados por codificadores humanos, com probabilidades de transição avaliadas utilizando a métrica L. Os principais achados indicam que o engajamento e a confusão correlacionam-se com o envolvimento ativo nas tarefas, enquanto o tédio e a frustração estão ligados à retirada das tarefas. Além disso, foram observadas dinâmicas específicas de gênero entre emoções e comportamentos. Esses resultados destacam o potencial de usar as relações observadas entre emoções e comportamentos para aprimorar experiências de aprendizagem personalizadas e informar o design de ambientes de aprendizagem adaptativos.
Palavras-chave:
Dinâmicas de Afeto, Padrões Comportamentais, Emoções, Aprendizagem, Ambientes de Aprendizagem Inteligentes
Referências
Baker, R. (2011). Gaming the System: A Retrospective Look. Philippine Computing Journal, 6(2):9–13.
Baker, R. S., D’Mello, S. K., Rodrigo, M. M. T., and Graesser, A. C. (2010). Better to be frustrated than bored: ... Int. J. of HCS, 68(4):223–241.
Baker, R. S., Moore, G. R., Wagner, A. Z., Kalka, J., Salvi, A., Karabinos, M., Ashe, C. A., and Yaron, D. (2011). The dynamics between student affect and behavior occurring outside of educational software. In ACII, pages 14–24. Springer.
Baker, R. S., Rodrigo, M. M. T., and Xolocotzin, U. E. (2007). The dynamics of affective transitions in simulation problem-solving environments. In ACII, pages 666–677.
D’Mello, S., Graesser, A., and Taylor, R. S. (2007). Monitoring affective trajectories during complex learning. In Annu. Meet. Cogn. Sci. Soc., volume 29.
D’Mello, S. K. (2020). Big data in the science of learning. In Big data in psychological research, pages 203–225. APA.
D’Mello, S. and Graesser, A. (2012). Dynamics of affective states during complex learning. Learning and Instruction, 22(2):145–157.
Fancsali, S. (2014). Causal discovery with models: behavior, affect, and learning in cognitive tutor algebra. In Educational Data Mining 2014. EDMS.
Fredrickson, B. L. (1998). What good are positive emotions? Review of General Psychology, 2(3):300–319.
Frenzel, A. C., Pekrun, R., and Goetz, T. (2007). Girls and mathematics—a “hopeless” issue? a control-value approach to gender differences in emotions towards mathematics. European Journal of Psychology of Education, 22(4):497–514.
Graesser, A. and D’Mello, S. K. (2011). Theoretical perspectives on affect and deep learning. In New Perspectives on Affect and Learning Tec., pages 11–21. Springer, NY.
Graesser, A. C., D’Mello, S. K., and Strain, A. C. (2014). Emotions in advanced learning technologies. In International handbook of emotions in education, pages 483–503. Routledge, New York.
Hembree, R. (1988). Correlates, causes, effects, and treatment of test anxiety. Review of Educational Research, 58(1):47–77.
Jaques, P. A., Seffrin, H., Rubi, G., Morais, F., Ghilardi, C., Bittencourt, I. I., and Isotani, S. (2013). Rule-based expert systems to support step-by-step guidance in algebraic problem solving: The case of the tutor PAT2math. Expert Systems with Applications, 40(14):5456–5465.
Karumbaiah, S., Baker, R. B., Ocumpaugh, J., and Andres, A. (2021). A re-analysis and synthesis of data on affect dynamics in learning. IEEE TAC.
Kostyuk, V., Almeda, M. V., and Baker, R. S. (2018). Correlating affect and behavior in reasoning mind with state test achievement. In LAK, pages 26–30.
Matayoshi, J., Karumbaiah, S., et al. (2020). Adjusting the l statistic when self-transitions are excluded in affect dynamics. J. of EDM, 12(4):1–23.
Morais, F. and Jaques, P. A. (2023). The dynamics of brazilian students’ emotions in digital learning systems. IJAIED.
Morais, F., Kautzmann, T. R., Bittencourt, I. I., and Jaques, P. A. (2019). EmAP-ML: A protocol of Emotions and behaviors Annotation for Machine Learning labels. In EC-TEL, pages 495–509, Netherlands. Springer.
Pardos, Z. A., Baker, R. S., San Pedro, M. O., Gowda, S. M., and Gowda, S. M. (2014). Affective states and state tests: Investigating how affect and engagement during the school year predict end-of-year learning outcomes. JLA, 1(1):107–128.
Pekrun, R. (2014). Emotions and learning. Technical Report Educational Practices Series24, UNESCO International Bureau of Education.
Perkins, H. V. (1965). Classroom behavior and underachievement. American Educational Research Journal, 2(1):1–12.
Rodrigo, M. M. T., Baker, R. S., Jadud, M. C., Amarra, A. C. M., Dy, T., Espejo-Lahoz, M. B. V., Lim, S. A. L., Pascua, S. A., Sugay, J. O., and Tabanao, E. S. (2009). Affective and behavioral predictors of novice programmer achievement. In ACM SIGCSE Conf. on Innovation and technology in CSE, pages 156–160.
Sabourin, J., Rowe, J. P., Mott, B. W., and Lester, J. C. (2011). When off-task is on-task: The affective role of off-task behavior in narrative-centered learning environments. In AIED, pages 534–536. Springer.
Zeidner, M. (1998). Test Anxiety: The State of the Art. Springer, New York.
Baker, R. S., D’Mello, S. K., Rodrigo, M. M. T., and Graesser, A. C. (2010). Better to be frustrated than bored: ... Int. J. of HCS, 68(4):223–241.
Baker, R. S., Moore, G. R., Wagner, A. Z., Kalka, J., Salvi, A., Karabinos, M., Ashe, C. A., and Yaron, D. (2011). The dynamics between student affect and behavior occurring outside of educational software. In ACII, pages 14–24. Springer.
Baker, R. S., Rodrigo, M. M. T., and Xolocotzin, U. E. (2007). The dynamics of affective transitions in simulation problem-solving environments. In ACII, pages 666–677.
D’Mello, S., Graesser, A., and Taylor, R. S. (2007). Monitoring affective trajectories during complex learning. In Annu. Meet. Cogn. Sci. Soc., volume 29.
D’Mello, S. K. (2020). Big data in the science of learning. In Big data in psychological research, pages 203–225. APA.
D’Mello, S. and Graesser, A. (2012). Dynamics of affective states during complex learning. Learning and Instruction, 22(2):145–157.
Fancsali, S. (2014). Causal discovery with models: behavior, affect, and learning in cognitive tutor algebra. In Educational Data Mining 2014. EDMS.
Fredrickson, B. L. (1998). What good are positive emotions? Review of General Psychology, 2(3):300–319.
Frenzel, A. C., Pekrun, R., and Goetz, T. (2007). Girls and mathematics—a “hopeless” issue? a control-value approach to gender differences in emotions towards mathematics. European Journal of Psychology of Education, 22(4):497–514.
Graesser, A. and D’Mello, S. K. (2011). Theoretical perspectives on affect and deep learning. In New Perspectives on Affect and Learning Tec., pages 11–21. Springer, NY.
Graesser, A. C., D’Mello, S. K., and Strain, A. C. (2014). Emotions in advanced learning technologies. In International handbook of emotions in education, pages 483–503. Routledge, New York.
Hembree, R. (1988). Correlates, causes, effects, and treatment of test anxiety. Review of Educational Research, 58(1):47–77.
Jaques, P. A., Seffrin, H., Rubi, G., Morais, F., Ghilardi, C., Bittencourt, I. I., and Isotani, S. (2013). Rule-based expert systems to support step-by-step guidance in algebraic problem solving: The case of the tutor PAT2math. Expert Systems with Applications, 40(14):5456–5465.
Karumbaiah, S., Baker, R. B., Ocumpaugh, J., and Andres, A. (2021). A re-analysis and synthesis of data on affect dynamics in learning. IEEE TAC.
Kostyuk, V., Almeda, M. V., and Baker, R. S. (2018). Correlating affect and behavior in reasoning mind with state test achievement. In LAK, pages 26–30.
Matayoshi, J., Karumbaiah, S., et al. (2020). Adjusting the l statistic when self-transitions are excluded in affect dynamics. J. of EDM, 12(4):1–23.
Morais, F. and Jaques, P. A. (2023). The dynamics of brazilian students’ emotions in digital learning systems. IJAIED.
Morais, F., Kautzmann, T. R., Bittencourt, I. I., and Jaques, P. A. (2019). EmAP-ML: A protocol of Emotions and behaviors Annotation for Machine Learning labels. In EC-TEL, pages 495–509, Netherlands. Springer.
Pardos, Z. A., Baker, R. S., San Pedro, M. O., Gowda, S. M., and Gowda, S. M. (2014). Affective states and state tests: Investigating how affect and engagement during the school year predict end-of-year learning outcomes. JLA, 1(1):107–128.
Pekrun, R. (2014). Emotions and learning. Technical Report Educational Practices Series24, UNESCO International Bureau of Education.
Perkins, H. V. (1965). Classroom behavior and underachievement. American Educational Research Journal, 2(1):1–12.
Rodrigo, M. M. T., Baker, R. S., Jadud, M. C., Amarra, A. C. M., Dy, T., Espejo-Lahoz, M. B. V., Lim, S. A. L., Pascua, S. A., Sugay, J. O., and Tabanao, E. S. (2009). Affective and behavioral predictors of novice programmer achievement. In ACM SIGCSE Conf. on Innovation and technology in CSE, pages 156–160.
Sabourin, J., Rowe, J. P., Mott, B. W., and Lester, J. C. (2011). When off-task is on-task: The affective role of off-task behavior in narrative-centered learning environments. In AIED, pages 534–536. Springer.
Zeidner, M. (1998). Test Anxiety: The State of the Art. Springer, New York.
Publicado
04/11/2024
Como Citar
JAQUES, Patricia A.; MORAIS, Felipe de; KAUTZMANN, Tiago R..
Affect Dynamics and Behavioral Patterns in Intelligent Learning Environments. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 35. , 2024, Rio de Janeiro/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 1452-1465.
DOI: https://doi.org/10.5753/sbie.2024.241613.
