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Knowledge-Based Adaptative Hypermedia with HAries

  • Yira MuñozEmail author
  • María de los Angeles Alonso
  • Iliana Castillo
  • Verónica Martínez
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1069)

Abstract

The theory developed for the construction of an adaptive hypermedia is presented, which has the ability to make decisions and be adjusted to the user’s needs. It is considered that besides the elements conforming any Hypermedia (nodes, links, multimedia, etc.), the specialized knowledge on how to handle information is included and too a working memory for each user which allows remember all the interaction that this one executes with the system. This type of knowledge is included in the knowledge representation scheme of hybrid language HAries, by means of three structures: Hypermedia HAries, Execution Variable and State Variable of the Hypermedia which were created for such purpose. The first stores all the hypermedia information related to the data and the knowledge of themselves in a database. This information is then used during the execution of the hypermedia to decide what to show to the user to see in every single moment. The last two structures have the function to start the execution of the hypermedia and the navigation control of the user through itself. All of them are then stored in a knowledge base created with the HAries language.

Keywords

Adaptative Hypermedia Knowledge representation Knowledge base Dynamic links 

References

  1. 1.
    Nielsen, J.: Hypertext and Hypermedia. Academic Press Professional, California (1993)Google Scholar
  2. 2.
    Amaya, G., Gualdrón, E., Fernández, C.: Hipertexto, Influencia en la estructuración del conocimiento. Horizontes Pedagógicos 19(1), 1–46 (2017)Google Scholar
  3. 3.
    Barbero, M.: Jóvenes entre el Palimpsesto y el Hipertexto. Nuevos Emprendimientos Editoriales, Barcelona (2017)Google Scholar
  4. 4.
    Gligora, M., Kadoić, N., Kovačić, B.: Selection and prioritization of adaptivity criteria in intelligent and adaptive hypermedia e-Learning systems. TEM J. Technol. Educ. Manage. Inform. 7(4), 137–146 (2018)Google Scholar
  5. 5.
    Sfenrianto, S., Hartarto, Y., Akbar, H., Mukhtar, M., Efriadi, E., Wahyudi, M.: An adaptive learning system based on knowledge level for english learning. Int. J. Emerg. Technol. Learn. (iJET) 13(12), 191–200 (2019)CrossRefGoogle Scholar
  6. 6.
    Zhao, X.: Mobile english teaching system based on adaptive algorithm. Int. J. Emerg. Technol. Learn. (iJET) 13(8), 64–77 (2018)CrossRefGoogle Scholar
  7. 7.
    Tosheva, S., Stojkovikj, N., Stojanova, A., Zlatanovska, B., Martinovski Bande, C.: Implementation of adaptative “E-School” system. TEM J. Technol. Educ. Manag. Inform. 6(2), 349–357 (2017)Google Scholar
  8. 8.
    Prado, T.R., Moro, M.M.: “Review recommendation for points of interest’s owners” de In: HT ‘17 Proceedings of the 28th ACM Conference on Hypertext and Social Media (2017)Google Scholar
  9. 9.
    Zataraín, R., Barrón, M.L., González, F., Oramas, R.: Ambiente inteligente de aprendizaje con manejo afectivo para Java. Res. Comput. Sci. 92, 111–121 (2015)Google Scholar
  10. 10.
    Mohd, J.K., Khurram, M.: Modelling adaptive hypermedia instructional system: a framework. Multimed. Tools Appl. 78, 14397–14424 (2018)Google Scholar
  11. 11.
    Isaias, P., Lima, S.: Collaborative design of case studies applying an adaptive digital learning tool. In: Proceedings of EdMedia: World Conference on Educational Media and Technology, pp. 1473–1482 (2018)Google Scholar
  12. 12.
    El Guabassi, M., Al Achhab, I., Jellouli, B., Mohajir, E.L.: Personalized ubiquitous learning via an adaptive engine. Int. J. Emerg. Technol. Learn. (iJET) 13(12), 177–190 (2018)CrossRefGoogle Scholar
  13. 13.
    Hamza, L., Tlili, G.: The optimization by using the learning styles in the adaptive hypermedia applications. Int. J. Web-Based Learn. Teach. Technol. 13(2), 16–31 (2018)CrossRefGoogle Scholar
  14. 14.
    Mutlu, B., Veas, E., Trattnero, T.: Tags, titles or Q&As? choosing content descriptors for visual recommender systems. In: HT ‘17 Proceedings of the 28th ACM Conference on Hypertext and Social Media, pp. 262–274 (2017)Google Scholar
  15. 15.
    Tadlaoui, M.A., Carvalho, R.N., Khaldi, M.: A learner model based on multi-entity Bayesian networks and artificial intelligence in adaptive hypermedia educational systems. Int. J. Adv. Comput. Res. 8(37), 148–160 (2018)CrossRefGoogle Scholar
  16. 16.
    Hou, M., Fidopiastis, C.: A generic framework of intelligent adaptive learning systems: from learning effectiveness to training transfer. Theor. Issues Ergon. Sci. 18, 167–183 (2017)CrossRefGoogle Scholar
  17. 17.
    Benigni, G., Marcano, I.: Qué herramientas utilizar para diseñar sistemas hipermedia educativos adaptativos? Revista Espacios 35(6), 13 (2014)Google Scholar
  18. 18.
    Yang, T.-C., Hwang, G.-J., Yang, S.J.-H.: Development of an adaptive learning system with multiple perspectives based on students’ learning styles and cognitive styles. Educ. Technol. Soc. 16(4), 185–200 (2013)Google Scholar
  19. 19.
    Messina, M., Di Montagnuolo, R., Massa, R.: Borgotallo: hyper Media News: a fully automated platform for large scale analysis, production and distribution of multimodal news content. Multimed. Tools Appl. 63(2), 427–460 (2013)CrossRefGoogle Scholar
  20. 20.
    Tsortanidou, X., Karagiannidis, C., Koumpis, A.: Adaptive educational hypermedia systems based on learning styles: the case of adaptation rules. iJET Int. J. Emerg. Technol. Learn. 12(5), 150 (2017)CrossRefGoogle Scholar
  21. 21.
    de los Angeles Alonso Lavernia, M., De la Cruz Rivera, A.V., Gutiérrez, A.: Knowledge representation language: HAries. In: Memorias de la 8th World Multiconference on Systemics, Cybernetics and Informatics (SCI 2004), Orlando, Florida (2004)Google Scholar
  22. 22.
    de los Angeles Alonso Lavernia, M., De la Cruz Rivera, A.V., Gutierrez, A.: HAries: Un lenguaje para la programación del conocimiento con facilidades para la construcción de material educativo. In: Memorias de la 3ª Conferencia Iberoamericana en Sistemas, Cibernética e Informática (CISCI 2004), Orlando (2004)Google Scholar
  23. 23.
    de los Angeles Alonso Lavernia, M.: Representación y manejo de información semática y heterogénea en interacción hombre-máquina. Tesis (Doctorado en Ciencias de la Computación) (2006). https://tesis.ipn.mx/handle/123456789/21037?show=full. Último acceso: 8 01 2019

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yira Muñoz
    • 1
    Email author
  • María de los Angeles Alonso
    • 2
  • Iliana Castillo
    • 2
  • Verónica Martínez
    • 2
  1. 1.Higher Education School Ciudad SahagunAutonomous University of Hidalgo StateSahagunMexico
  2. 2.Computing and Electronic Academic AreaAutonomous University of Hidalgo StatePachucaMexico

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