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Intelligent tutoring system using expert knowledge and Kohonen maps with automated training

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Abstract

This paper presents an intelligent tutoring system (ITS) model that is capable of driving the didactic transposition of contents. Initially, the tutoring system reactions bases its behavior on rules defined by an expert teacher; after this, a neural network that learns from the student’s behavior when they are studying adjusts these rules. This way, the neural network improves the teacher’s rules and, consequently, defines a learning strategy that is more adaptive and reactive to the student’s profile. Thus, it is possible to offer the student a personalized and individualized education form. The model is able to guide the student throughout the didactic transposition of contents, aiding the consolidation of desired competencies established on educational propositions. This work shows the development process of the ITS, including the expert guidance system and the hybrid system, which improves the expert rules from SOM neural network use. The obtained results indicate that the application of hybrid technology in ITSs is feasible because, for defining the teaching strategies, it incorporates the teacher’s knowledge and by neural network use, it assimilates the students’ learning process behavior. The results show that proposed model has great agreement between the actions of the “ITS” and the students’ actions. The model showed satisfactory performance when compared to other systems proposed in the literature that use connectionist approach in its conception.

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References

  1. Alias UF, Ahmad NB, Hasan S (2015) Student behavior analysis using self-organizing map clustering technique. ARPN J Eng Appl Sci 10(23):17987–17995

    Google Scholar 

  2. Anderson JR, Boyle CF, Reiser BR (1995) Intelligent tutoring systems. Science 228(1):456–462

    Google Scholar 

  3. Cabada RZ, Barrón ML, Garcia AR (2011) EDUCA: a web 2.0 authoring tool for developing adaptive and inteligente tutoring systems using a Kohonen network. Expert Syst Appl 38:9522–9529

    Article  Google Scholar 

  4. Carvalho SD (2013) Modelo Híbrido de Sistema Tutor Inteligente Utilizando Conhecimento do Especialista e Mapas de Kohonen com Treinamento Automatizado. Universidade Federal de Uberlândia, Tese de Doutorado

    Google Scholar 

  5. Carvalho SD, Melo FR, Martins W, Nalini LEG, Flôres EL (2008) Sistemas Tutores inteligentes baseados em mapas auto-organizáveis. In: VI CEEL: Conferência de estudos em engenharia elétrica 2008, 2008, Uberlândia-MG. VI CEEL 2008. Uberlândia-MG, pp 21–26

  6. Chevallard Y (1998) La transposicio´n dida´ctica del saber sa´bio al saber ensen ~ ado. Tradução de Cláudia Gilman, 3rd edn. Buenos Aires, Aique, p 196

    Google Scholar 

  7. De Vaney A, Butler RP (2001) Voices of the founders: early discourses in educational technology. In: Em Jonassen DH (ed) The handbook of research for educational communications and technology. The Association for Educational Communications and Technology, Bloomington

    Google Scholar 

  8. Fontenla J, Caeiro M, Llamas M (2010) A SOA architecture to improve the tailorability and extensibility of e-learning systems. IEEE Latin Am Trans 8(2):135

    Article  Google Scholar 

  9. Forradellas MTS, Barberà-Mariné MG, Bariviera AF, Garbajosa-Cabello MJ (2012) Advantages of using self-organizing maps to analyse student evaluations of teaching. Fuzzy Econ Rev XVII(1):53–71

    Google Scholar 

  10. Giraffa LMM, Viccari RM (1998) The use of agents techniques on intelligent tutoring systems. In: Proceedings of 18th international conference of the Chilean computer science society, Antofagasta, Chile, 1998, pp 78–83

  11. Hafidi M, Bensebaa T (2013) Design and evaluation of an adaptive and intelligent tutoring system by expert system. Intel Decis Technol 7(253–264):253. https://doi.org/10.3233/IDT-130167

    Article  Google Scholar 

  12. Horton WK (2000) Designing web-based training: how to teach anyone anything anywhere anytime. Wiley, Hoboken

    Google Scholar 

  13. Jaques PA, Seffrin H, Rubi G, Morais F, Ghilardi C, Bittencourt AII, Isotani S (2013) Rule-based expert systems to support step-by-step guidance in algebraic problem solving: the case of the tutor PAT2Math. Expert Syst Appl 40:5456–5465

    Article  Google Scholar 

  14. Jevsikova T, Berniukevicius E, Kurilovas E (2017) Application of resource description framework to personalise learning systematica review and methodology. Inf Educ 16(1):61–82

    Google Scholar 

  15. Jonassen DH (2001) The handbook of research for educational communications and technology. The Association for Educational Communications and Technology, Bloomington

    Google Scholar 

  16. Kohonen T (1982) Analysis of a simple self-organizing process. Biol Cybern 44:135–140

    Article  MathSciNet  Google Scholar 

  17. Kohonen T (2001) Self-organizing maps. Springer, Berlim

    Book  Google Scholar 

  18. Kurilovas E (2016) Evaluation of quality and personalization of VR/AR/MR learning systems. Behav Inf Technol 35(11):998–1007

    Article  Google Scholar 

  19. Markowska-Kaczmar U, Kwasnicka H, Paradowski M (2010) Intelligent techniques in personalization of learning in e-learning systems. Stud Comput Intel 273(2010):1–23

    Google Scholar 

  20. Martins W, Fonseca UR, Nalini LEG, Gomes VM (2007) Tutoriais Inteligentes Baseados em Aprendizado por Reforço: Concepção, Implementação e Avaliação Empírica. Anais do SBIE. Workshop em Informática na Educação (SBIE) 2007 XVIII Simpósio Brasileiro de Informática na Educação-SBIE-Mackenzie

  21. Melo FR (2012) Modelo Neural por Padrões Proximais de Aprendizagem para Automação Personalizada de Conteúdos Didáticos. Ph.D. dissertation, FEELT, UFU, Uberlândia, MG, Brazil

  22. Melo FR, Flôres EL, Carvalho SD (2011) Multilevel content’s structure for personalization in conexionist intelligent tutor systems. In: 8th International conference on information systems and technology management, 2011, São Paulo. Proceedings of 8th CONTECSI. São Paulo, TECSI EAC FEA USP

  23. Nohuddin P, Zainol Z, Nordin A (2018) Monitoring students performance using self organizing map trend clustering. ZULFAQAR Int J Def Sci Eng Technol 1(1):50–56

    Google Scholar 

  24. Patten JV, Chao CI, Reigeluth CM (1986) A review of strategies for sequencing and synthesizing instruction. Rev Educ Res 56(4):437–471

    Article  Google Scholar 

  25. Phelan KC, Mendoza-Diaz NV, Mathews S (2002) An example of converting a traditional course into distance learning: an open discussion. In: 9th Annual international distance education conference, Austin, Texas, USA

  26. Pires DGF, Pires SR, Lopes CR (2016) Análise comparativa entre o uso de ambientes tradicionais de EAD e de sistemas tutores inteligentes: preparação, elaboração, aplicação e resultados, Atas CIAIQ2016: Investigação Qualitativa em Educação, Porto. CIAIQ 1:779–788

    Google Scholar 

  27. Raabe ALA, Giraffa LMM (2006) Uma Arquitetura de Tutor para Promover Experiências de Aprendizagem Mediadas. In: XVII SImpósio Brasileiro de Informática na Educação-SBIE2006, Brasília-DF. v. 1. pp 589–598

  28. Rosenberg MJ (2001) E-learning strategies for delivery knowledge in the digital age. McGraw-Hill, New York

    Google Scholar 

  29. Saxena K, Jaloree S, Thakur RS, Kamley S (2017) Self-organizing map (SOM) based modelling technique for student academic performance prediction. Int J Future Revol Comput Sci Commun Eng 3(9):115–120

    Google Scholar 

  30. Stewart C (2017) Learning analytics: shifiting from theory to practice. J Empower Teach Excell 1(1):10

    Google Scholar 

  31. Viccari RM, Giraffa LMM (1996) Intelligent tutoring systems: functional approach x agents approach. In: Proceedings of 13th Brazilian symposium on artificial intelligence, Curitiba, Brazil, p 235

  32. Wenting Ma OO, Adesope JC, Nesbit QL (2014) Intelligent tutoring systems and learning outcomes: a meta-analysis. J Educ Psychol 106(4):901–918

    Article  Google Scholar 

  33. Zarandi MHF, Khademian M, Minaei-Bidgoli B, Türkşen IB (2012) A Fuzzy expert system architecture for intelligent tutoring systems: a cognitive mapping approach. J Intell Learn Syst Appl 4:29–40

    Google Scholar 

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Acknowledgements

Funding was provided by Fundação de Amparo à Pesquisa do Estado de Goiás (Grant No. 12345).

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Authors and Affiliations

  1. Instituto Federal de Goiás, Goiânia, Anápolis, GO, Brazil

    Sirlon Diniz de Carvalho & Luiz Fernando Batista Loja

  2. Universidade Estadual de Goiás, Anápolis, GO, Brazil

    Francisco Ramos de Melo

  3. Universidade Federal de Uberlândia, Uberlândia, MG, Brazil

    Edna Lucia Flôres

  4. Universidade Federal de Goiás, Goiânia, GO, Brazil

    Sandrerley Ramos Pires

Authors
  1. Sirlon Diniz de Carvalho
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  2. Francisco Ramos de Melo
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  3. Edna Lucia Flôres
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  4. Sandrerley Ramos Pires
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  5. Luiz Fernando Batista Loja
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Correspondence to Francisco Ramos de Melo.

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de Carvalho, S.D., de Melo, F.R., Flôres, E.L. et al. Intelligent tutoring system using expert knowledge and Kohonen maps with automated training. Neural Comput & Applic 32, 13577–13589 (2020). https://doi.org/10.1007/s00521-020-04767-0

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