Dynamic Adaptive Activity Planning in Education: Implementation and Case Study

  • Jaime Pavlich-Mariscal
  • Mery Yolima Uribe-Rios
  • Luisa Fernanda Barrera-León
  • Nadia Alejandra Mejia-Molina
  • Angela Carrillo-Ramos
  • Alexandra Pomares
  • Juan Camilo González-Vargas
  • Monica Brijaldo
  • Martha Sabogal
  • Rosa Vicari
  • Ramon Fabregat
  • Hervé Martin
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 583)

Abstract

Dynamic Adaptive Activity Planning is a technique to create plans in which activities are the best suited for particular users and their context. This paper presents an architecture, called ASHYI, for dynamic adaptive activity planning, and ASHYI-EDU, an application of ASHYI for the educational domain. ASHYI-EDU can automatically create a learning plan for students, according to their specific characteristics, assign remedial activities if students need to reinforce some concepts, and it can update those plans if the student profile or its context change. ASHYI-EDU was implemented as a virtual learning environment (VLE) prototype, and was utilized during two semesters to teach an online course. The results suggest that, although teachers need to invest more time to create learning activities for heterogeneous students, ASHYI-EDU effectively assigns the most alike activities to each student and it also addresses student shortcomings through remedial activities.

References

  1. 1.
    Brijaldo, M.I.: Los estilos de aprendizajes como fundamento para la personalización y adaptación de procesos de evaluación en estudiantes universitarios: Desarrollo de una plataforma de análisis multicriterio, Buenos Aires, Argentina (2015)Google Scholar
  2. 2.
    Carrillo-Ramos, A., Rios, M.Y.U., Rodríguez, M.I.B., León, L.F.B., Modera, M.L.S., Mejía, N.A., Pavlich-Mariscal, J.A., Quimbaya, A.P., Vargas, J.E.C.: ASHYI: Plataforma basada en agentes para la planificación dinámica, inteligente y adaptativa de actividades aplicada a la educación personalizada. Editorial Javeriana (2015)Google Scholar
  3. 3.
    Sangineto, E., Capuano, N., Gaeta, M., Micarelli, A.: Adaptive course generation through learning styles representation. Univ. Access Inf. Soc. 7, 1–23 (2008)CrossRefGoogle Scholar
  4. 4.
    Ott, M., Dagnino, F.M., Pozzi, F.: Intangible cultural heritage: towards collaborative planning of educational interventions. Comput. Hum. Behav. 51, 1314–1319 (2014)CrossRefGoogle Scholar
  5. 5.
    Hwang, G.J., Kuo, F.R., Yin, P.Y., Chuang, K.H.: A heuristic algorithm for planning personalized learning paths for context-aware ubiquitous learning. Comput. Educ. 54, 404–415 (2010)CrossRefGoogle Scholar
  6. 6.
    Yin, P.Y., Chuang, K.H., Hwang, G.J.: Developing a context-aware ubiquitous learning system based on a hyper-heuristic approach by taking real-world constraints into account. Univ. Access Inf. Soc., 1–14 (2014). doi:10.1007/s10209-014-0390-z
  7. 7.
    Almulla, M.: School e-Guide: a personalized recommender system for e-learning environments. In: Proceedings of the First Kuwait Conference on e-Services and e-Systems, eConf 2009, pp. 2:1–2:5. ACM, New York (2009)Google Scholar
  8. 8.
    Rytikova, I., Boicu, M.: A methodology for personalized competency-based learning in undergraduate courses. In: Proceedings of the 15th Annual Conference on Information Technology Education, SIGITE 2014, pp. 81–86. ACM, New York (2014)Google Scholar
  9. 9.
    Schiaffino, S., Garcia, P., Amandi, A.: eTeacher: providing personalized assistance to e-learning students. Comput. Educ. 51, 1744–1754 (2008)CrossRefGoogle Scholar
  10. 10.
    Hong, C.M., Chen, C.M., Chang, M.H., Chen, S.C.: Intelligent web-based tutoring system with personalized learning path guidance. In: 2007 Seventh IEEE International Conference on Advanced Learning Technologies, ICALT 2007, pp. 512–516 (2007)Google Scholar
  11. 11.
    Baldoni, M., Baroglio, C., Brunkhorst, I., Henze, N., Marengo, E., Patti, V.: Constraint modeling for curriculum planning and validation. Interact. Learn. Environ. 19, 81–123 (2011)CrossRefGoogle Scholar
  12. 12.
    Jamuna, R., Ashok, M., Palanivel, K.: Adaptive content for personalized E-learning using web service and semantic web. In: 2009 International Conference on Intelligent Agent Multi-agent Systems, IAMA 2009, pp. 1–4 (2009)Google Scholar
  13. 13.
    Pavlich-Mariscal, J.A., Uribe, Y., Barrera, L., Pomares, A., Mejía, N., Carrillo-Ramos, A., Fabregat, R., Baldiris, S.M.: An architecture for dynamic and adaptive user activity planning systems, Lisbon, Portugal (2015)Google Scholar
  14. 14.
    Blum, A.L., Furst, M.L.: Fast planning through planning graph analysis. Artif. Intell. 90, 281–300 (1997)CrossRefMATHGoogle Scholar
  15. 15.
    Pavlich-Mariscal, J.A., Uribe, Y., Barrera, L., Mejía, N., Carrillo-Ramos, A., Pomares, A., Brijaldo, M., Sabogal, M., Vicari, R.M., Martin, H.: ASHYI-EDU: applying dynamic adaptive planning in a virtual learning environment, Lisbon, Portugal (2015)Google Scholar
  16. 16.
    Alonso, C., Gallego, D., Garcia, J.: CHAEA - Estilos de aprendizaje (2009)Google Scholar
  17. 17.
    Honey, P., Mumford, A.: The Manual of Learning Styles, 3rev edition edn. Peter Honey Publications, Maidenhead (1992)Google Scholar
  18. 18.
    Myers, I.B., McCaulley, M.H., Quenk, N.L., Hammer, A.L.: MBTI Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator, 3rd edn. Consulting Psychologists Press, Palo Alto (1998)Google Scholar
  19. 19.
    Carrillo-Ramos, A., Villanova-Oliver, M., Gensel, J., Martin, H.: Knowledge management for adapted information retrieval in ubiquitous environments. In: Filipe, J., Cordeiro, J., Pedrosa, V. (eds.) Web Information Systems and Technologies. LNBIP, vol. 1, pp. 84–96. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  20. 20.
    Candillier, L., Fessant, F., Meyer, F.: Designing specific weighted similarity measures to improve collaborative filtering systems. In: Perner, P. (ed.) ICDM 2008. LNCS (LNAI), vol. 5077, pp. 242–255. Springer, Heidelberg (2008)Google Scholar
  21. 21.
    Apereo-Foundation: Sakai (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jaime Pavlich-Mariscal
    • 1
    • 5
  • Mery Yolima Uribe-Rios
    • 1
  • Luisa Fernanda Barrera-León
    • 1
  • Nadia Alejandra Mejia-Molina
    • 1
  • Angela Carrillo-Ramos
    • 1
  • Alexandra Pomares
    • 1
  • Juan Camilo González-Vargas
    • 1
  • Monica Brijaldo
    • 1
  • Martha Sabogal
    • 1
  • Rosa Vicari
    • 2
  • Ramon Fabregat
    • 3
  • Hervé Martin
    • 4
  1. 1.Departamento de Ingeniería de SistemasPontificia Universidad JaverianaBogotáColombia
  2. 2.Universidade Federal do Rio Grande do SulPorto AlegreBrazil
  3. 3.University of GironaGironaSpain
  4. 4.Laboratoire d’Informatique de GrenobleGrenobleFrance
  5. 5.Departamento de Ingeniería de Sistemas y ComputaciónUniversidad Catolica del NorteAntofagastaChile

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