Abstract
Intelligent Tutoring Systems (ITS) environments have the ability to adapt to each learner’s individual needs and thus provide immediate and personalized instructions, both in content and in form. This personalization can consider several aspects, such as the interaction, the level of knowledge, the error, and the affective state of the learner aiming to improve the teaching strategies. One of the strategies is the possibility of presenting tutorial interventions when verifying an error made in solving an exercise, or when detecting that the learner is unmotivated or frustrated. These tutorial interventions can improve teaching methods in order to improve performance and the level of knowledge acquired by the learner. In this sense, this research presents a model that allows the automatic presentation of tutoring interventions based on identification of mathematical error kind committed by the learner, in addition to inferring his affective state. Experiments were carried out in a real learning environment, using the proposed model implemented in a fraction game. In general, the results presented indicate that personalized tutorial interventions favor greater engagement and motivation of learners and improvement in learning outcomes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arguedas, M., Xhafa, F., Casillas, L., Daradoumis, T., Peña, A., Caballé, S.: A model for providing emotion awareness and feedback using fuzzy logic in online learning. Soft. Comput. 22(3), 963–977 (2016). https://doi.org/10.1007/s00500-016-2399-0
Ascari, S.R., Gottardo, E., Pimentel, A.R.: Identificação de Intervenções Tutoriais para Ambientes Virtuais de Aprendizagem. In: Brazilian Symposium on Computers in Education, pp. 842–851. Anais do XXXI Simpósio Brasileiro de Informática na Educação - SBIE (2020). https://doi.org/10.5753/cbie.sbie.2020.842
Ascari, S.R., Gottardo, E., Pimentel, A.R.: MAfint: modelo afetivo de intervenção tutorial para Ambientes de Virtuais de Aprendizagem. In: Brazilian Symposium on Computers in Education, pp. 832–841. Anais do XXXI Simpósio Brasileiro de Informática na Educação - SBIE (2020). https://doi.org/10.5753/cbie.sbie.2020.832
Burns, H.L., Capps, C.G.: Foundations of intelligent tutoring systems: an introduction. In: Polson, M.C., Richardson, J.J. (eds.) Foundations of Intelligent Tutoring Systems. Lawrence Erlbaum Associates, Hillsdale (1988)
D’Mello, S., Picard, R.W., Graesser, A.: Toward an affect-sensitive autotutor. In: IEEE Intelligent Systems, vol. 22, pp. 53–61. IEEE (2007). https://doi.org/10.1109/MIS.2007.79
Economides, A.A.: Adaptive feedback evaluation. In: Proceedings of the 5th WSEAS international Conference on Distance Learning and Web Engineering, pp. 134–139 (2005)
Ekman, P.: An argument for basic emotions. Cogn. Emot. 6, 169–200 (1992). https://doi.org/10.1080/02699939208411068
Fiori, C., Zuccheri, L.: An experimental research on error patterns in written subtraction. Educ. Stud. Math. 60, 323–331 (2005). https://doi.org/10.1007/s10649-005-7530-6
Fleming, M.L., Levi, W.H.: Instructional message design: principles from the behavioral and cognitive sciences. In: Educational Technology Publications, Englewood Cliffs, NJ (1993)
Gottardo, E., Ricardo Pimentel, A.: Improving inference of learning related emotion by combining cognitive and physical information. In: Nkambou, R., Azevedo, R., Vassileva, J. (eds.) ITS 2018. LNCS, vol. 10858, pp. 313–318. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91464-0_33
Gottardo, E., Pimentel, A.R.: Reconhecimento e adaptação à dinâmica de estados afetivos relacionados à aprendizagem. In: Brazilian Computer Society - SBC, vol. 29, pp. 1223–1232. Anais do XXIX Simpósio Brasileiro de Informática na Educação (2018). https://doi.org/10.5753/cbie.sbie.2018.1223
Hannafin, M., Land, S., Oliver, K.: Open learning environments: foundations, methods, and models. In: Instructional-Design Theories and Models: A New Paradigm of Instructional Theory, vol. 2, pp. 115–140 (1999)
Hume, G., Michael, J., Rovick, A., Evens, M.: Hinting as a tactic in one-on-one tutoring. J. Learn. Sci. 5, 23–47 (1996). https://doi.org/10.1207/s15327809jls0501_2
Leite, M.D., Pimentel, A.R., Pietruchinski, M.H.: Remediação de erros baseada em múltiplas representações externas e classificação de erros aplicada a objetos de aprendizagem inteligentes. In: Brazilian Symposium on Computers in Education - SBIE, vol. 23, pp. 1–10. Anais do 23\(^{\circ }\) Simpósio Brasileiro de Informática na Educação (2012). https://doi.org/10.5753/cbie.sbie.2012.25p
Marczal, D., Direne, A., Pimentel, A.R., Krynski, E.M.: Farma: Uma Ferramenta de Autoria para Objetos de Aprendizagem de Conceitos Matemáticos. In: Brazilian Computer Society - SBC, vol. 4, pp. 23–32. Anais dos Workshops do IV Congresso Brasileiro de Informática na Educação - CBIE (2015). https://doi.org/10.5753/cbie.wcbie.2015.23
McKendree, J.: Effective feedback content for tutoring complex skills. Hum. Comput. Interact. 5, 381–413 (1990). https://doi.org/10.1207/s15327051hci0504_2
McLoughlin, C.: Achieving excellence in teaching through scaffolding learner competence. In: Seeking Educational Excellence (2004)
Morais, F., da Silva, J., Reis, H., Isotani, S., Jaques, P.: Computação Afetiva aplicada à Educação: uma revisão sistemática das pesquisas publicadas no Brasil. In: Brazilian Computer Society - SBC. Brazilian Symposium on Computers in Education - SBIE, vol. 28, pp. 163–172. (2017). https://doi.org/10.5753/cbie.sbie.2017.163
Movshovitz-Hadar, N., Zaslavsky, O., Inbar, S.: An empirical classification model for errors in high school mathematics. J. Res. Math. Educ. 18, 3–14 (1987). National Council of Teachers of Mathematics. https://doi.org/10.2307/749532
Narciss, S.: Designing and evaluating tutoring feedback strategies for digital learning environments on the basis of the interactive tutoring feedback model. In: Digital Education Review, vol. 23, pp. 7–26. Digital Education Observatory (OED) (2013). https://www.learntechlib.org/p/131614
Pekrun, R.: Emotions as drivers of learning and cognitive development. In: Calvo, R., D’Mello, S. (eds.) New Perspectives on Affect and Learning Technologies. Explorations in the Learning Sciences, Instructional Systems and Performance Technologies, vol. 3. Springer, New York (2011). https://doi.org/10.1007/978-1-4419-9625-1_3
Pekrun, R., Goetz, T., Titz, W., Perry, R.P.: Positive emotions in education. In: Frydenberg, E. (ed.) Beyond Coping: Meeting Goals, Visions, and Challenges, pp. 149–173. Oxford University Press (2002). https://nbn-resolving.org/html/urn:nbn:de:bsz:352--139080
Peng, A., Luo, Z.: A framework for examining mathematics teacher knowledge as used in error analysis. Learn. Math. 29, 22–25 (2009)
Picard, R.: Affective Computing. MIT Press, Cambridge (1997)
Radatz, H.: Error analysis in mathematics education. J. Res. Math. Educ. 10, 163–172 (1979). https://doi.org/10.2307/748804
dos Santos, D.C.V., Falcão, T.P.: Acompanhamento de alunos em ambientes virtuais de aprendizagem baseado em sistemas tutores inteligentes. In: Brazilian Symposium on Computers in Education - SBIE, vol. 28, pp. 1267–1276 (2017). https://doi.org/10.5753/cbie.sbie.2017.1267
Vanlehn, K.: The behavior of tutoring systems. Int. J. Artif. Intell. Educ. 16, 227–265 (2006)
Vergnaud, G.: A classification of cognitive tasks and operations of thought involved in addition and subtraction problems. In: Addition and Subtraction: A Cognitive Perspective, pp. 39–59. Lawrence Erlbaum Associate (1982)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Ascari, S.R., Pimentel, A.R., Gottardo, E. (2021). Tutorial Intervention’s Affective Model Based on Learner’s Error Identification in Intelligent Tutoring Systems. In: Cristea, A.I., Troussas, C. (eds) Intelligent Tutoring Systems. ITS 2021. Lecture Notes in Computer Science(), vol 12677. Springer, Cham. https://doi.org/10.1007/978-3-030-80421-3_50
Download citation
DOI: https://doi.org/10.1007/978-3-030-80421-3_50
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-80420-6
Online ISBN: 978-3-030-80421-3
eBook Packages: Computer ScienceComputer Science (R0)