Conditional IMS learning design generation using User modeling and planning techniques
Active modeling is required in learning settings to cope with the dynamic evolution of the knowledge, since learners competences evolves over time as they participate in the course activities. Moreover, one of the main issues in a competence based eLearning process is to deliver personalized instruc...
- Autores:
-
Hernández, Jorge
Baldiris, Silvia
C. Santos, Olga
Fabregat, Ramón
G. Boticario, Jesus
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2009
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/8581
- Acceso en línea:
- https://hdl.handle.net/11323/8581
https://doi.org/10.1109/ICALT.2009.185
https://repositorio.cuc.edu.co/
- Palabra clave:
- IMS Learning
Design Generation
User Modeling
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
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Conditional IMS learning design generation using User modeling and planning techniques |
| title |
Conditional IMS learning design generation using User modeling and planning techniques |
| spellingShingle |
Conditional IMS learning design generation using User modeling and planning techniques IMS Learning Design Generation User Modeling |
| title_short |
Conditional IMS learning design generation using User modeling and planning techniques |
| title_full |
Conditional IMS learning design generation using User modeling and planning techniques |
| title_fullStr |
Conditional IMS learning design generation using User modeling and planning techniques |
| title_full_unstemmed |
Conditional IMS learning design generation using User modeling and planning techniques |
| title_sort |
Conditional IMS learning design generation using User modeling and planning techniques |
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Hernández, Jorge Baldiris, Silvia C. Santos, Olga Fabregat, Ramón G. Boticario, Jesus |
| dc.contributor.author.spa.fl_str_mv |
Hernández, Jorge Baldiris, Silvia C. Santos, Olga Fabregat, Ramón G. Boticario, Jesus |
| dc.subject.spa.fl_str_mv |
IMS Learning Design Generation User Modeling |
| topic |
IMS Learning Design Generation User Modeling |
| description |
Active modeling is required in learning settings to cope with the dynamic evolution of the knowledge, since learners competences evolves over time as they participate in the course activities. Moreover, one of the main issues in a competence based eLearning process is to deliver personalized instructional designs adjusted to both 1) intrinsic characteristics of users (i.e. learning styles) and 2) the desired and achieved competences in the learning process (i.e. specific and generic competences). This delivery includes the adaptation of the content and the activities in a learning scenario based on a dynamic user model that evolves according to user interactions. In this paper, an approach to support Conditional Plans Generation (IMS Learning Designs) in the context of a virtual learning environment is presented. The process is supported by a pervasive usage of standards and specifications (IMS family of specifications) in conjunction with an integral user modeling. |
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2021-08-23T18:02:46Z |
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2021-08-23T18:02:46Z |
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Artículo de revista |
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Corporación Universidad de la Costa |
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Baldiris, S., Santos, O. C., Barrera, C., Boticario J. G., Velez, J., Fabregat, R.: Integration of educational specifications and standards to support adaptive learning scenarios in ADAPTAPlan. International Journal of Computer Science and Applications (IJCSA). Special Issue on New Trends on AI techniques for Educational Technologies. Vol 5, 1, 2008. Baldiris, S., Santos, O. C., Huerva, D, Fabregat, R.Boticario J. G.: Multidimensional Adaptations for Open Learning Management Systems. Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference. Vol 3, pag 352-356, 2008. Rintanen Jussi. Introduction to Automated Planning. Lecture notes of the AI planning course at the AlbertLudwigs-University. Feb 2005. K. Erol, J. Hendler, and D. S. Nau. HTN planning: Complexity and expressivity. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), volume 2, pages 1123–1128, Seattle, Washington, USA, 1994. AAAI Press/MIT Press. Kuter, U., Nau, D., Reisner, E. and Goldman, R. Conditionalization: Adapting Forward-Chaining Planners to Partially Observable Environments. Proceedings of the ICAPS-07 Workshop on Planning and Plan Execution for Real-World Systems -- Principles & Practices for Planning in Execution, 2007. Kuter, U and Nau, D. Forward-Chaining Planning in Nondeterministic Domains. Proceedings of the AAAI04, 2004 Bouguerra, A:, Karlsson, L.. PC-SHOP: A ProbabilisticConditional Hierarchical Task Planner. Intelligenza Artificiale, 2(4):44--50, 2005. Ilghami, O and Nau, D. A general approach to synthesize problem-specific planners. Technical Report CS-TR-4597, Department of Computer Science, University of Maryland, October, 2003. Petrick, R.P.A., Bacchus, F. A knowledge-based approach to planning with incomplete information and sensing, in: M. Ghallab, J. Hertzberg, P. Traverso (Eds.), Proceedings of the Sixth International Conference on Artificial Intelligence Planning and Scheduling (AIPS'02), AAAI Press, Menlo Park, CA, 2002, pp. 212-221, 2002. Levesque, H. J. What is planning in the presence of sensing? In Proceedings of the AAAI National Conference, 1139–1146. AAAI Press/MIT Press, 1996. Cuartero, A., Santos, O.C., Granado, J., Raffenne, E. and Boticario, J.G. Mangement of standard-based User Model and Device Profile in OpenACS. Proceedings of the International Conference and Workshops on Community based environments, 2008. Baldiris, S., Santos, O., Boticario J., Fabregat R., Los estándares educativos como herramienta de modelado de cursos que proveen adaptaciones dinámicas a los usuarios, Revista Iberoamericana de Informática Educativa, 2008. Mejía, C., Baldiris, S., Gómez, S., and Fabregat, R. Adaptation process to deliver content based on user learning styles, International Conference of Education, Research and Innovation (IBSN: 978-84-612-5091-2), 2008, International Association of Technology, Education and Development, Madrid (Spain), 2008. Mancera, L., Baldiris, N., Fabregat, R.: Modelling Collaborative Competence Level using Machine Learning Techniques Huerva, D., Velez, J., Baldiris, S., Fabregat, R., Merida, D: Adoption of courses and learning environment to the user context in dotLRN. International Conference on Innovation in Software Engineering. Vienna – Austria. 10-12 December, 2008. Merida, D., Cannataro, M., Fabregat, R. and Arteaga, C.: MAS-SHAAD a Multiagent System an Adaptive Hypermedia System. Proceedings of IJCEELL journal Special issue: Adaptivity in Web and Mobile Learning Services, 2004. |
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Hernández, JorgeBaldiris, SilviaC. Santos, OlgaFabregat, RamónG. Boticario, Jesus2021-08-23T18:02:46Z2021-08-23T18:02:46Z2009https://hdl.handle.net/11323/8581https://doi.org/10.1109/ICALT.2009.185Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Active modeling is required in learning settings to cope with the dynamic evolution of the knowledge, since learners competences evolves over time as they participate in the course activities. Moreover, one of the main issues in a competence based eLearning process is to deliver personalized instructional designs adjusted to both 1) intrinsic characteristics of users (i.e. learning styles) and 2) the desired and achieved competences in the learning process (i.e. specific and generic competences). This delivery includes the adaptation of the content and the activities in a learning scenario based on a dynamic user model that evolves according to user interactions. In this paper, an approach to support Conditional Plans Generation (IMS Learning Designs) in the context of a virtual learning environment is presented. The process is supported by a pervasive usage of standards and specifications (IMS family of specifications) in conjunction with an integral user modeling.Hernández, JorgeBaldiris, SilviaC. Santos, OlgaFabregat, RamónG. Boticario, Jesusapplication/pdfengCorporación Universidad de la CostaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2IEEE International Conference on Advanced Learning Technologieshttps://www.computer.org/csdl/proceedings-article/icalt/2009/3711a228/12OmNxUMHnoIMS LearningDesign GenerationUser ModelingConditional IMS learning design generation using User modeling and planning techniquesArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionBaldiris, S., Santos, O. C., Barrera, C., Boticario J. G., Velez, J., Fabregat, R.: Integration of educational specifications and standards to support adaptive learning scenarios in ADAPTAPlan. International Journal of Computer Science and Applications (IJCSA). Special Issue on New Trends on AI techniques for Educational Technologies. Vol 5, 1, 2008.Baldiris, S., Santos, O. C., Huerva, D, Fabregat, R.Boticario J. G.: Multidimensional Adaptations for Open Learning Management Systems. Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference. Vol 3, pag 352-356, 2008.Rintanen Jussi. Introduction to Automated Planning. Lecture notes of the AI planning course at the AlbertLudwigs-University. Feb 2005.K. Erol, J. Hendler, and D. S. Nau. HTN planning: Complexity and expressivity. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), volume 2, pages 1123–1128, Seattle, Washington, USA, 1994. AAAI Press/MIT Press.Kuter, U., Nau, D., Reisner, E. and Goldman, R. Conditionalization: Adapting Forward-Chaining Planners to Partially Observable Environments. Proceedings of the ICAPS-07 Workshop on Planning and Plan Execution for Real-World Systems -- Principles & Practices for Planning in Execution, 2007.Kuter, U and Nau, D. Forward-Chaining Planning in Nondeterministic Domains. Proceedings of the AAAI04, 2004Bouguerra, A:, Karlsson, L.. PC-SHOP: A ProbabilisticConditional Hierarchical Task Planner. Intelligenza Artificiale, 2(4):44--50, 2005.Ilghami, O and Nau, D. A general approach to synthesize problem-specific planners. Technical Report CS-TR-4597, Department of Computer Science, University of Maryland, October, 2003.Petrick, R.P.A., Bacchus, F. A knowledge-based approach to planning with incomplete information and sensing, in: M. Ghallab, J. Hertzberg, P. Traverso (Eds.), Proceedings of the Sixth International Conference on Artificial Intelligence Planning and Scheduling (AIPS'02), AAAI Press, Menlo Park, CA, 2002, pp. 212-221, 2002.Levesque, H. J. What is planning in the presence of sensing? In Proceedings of the AAAI National Conference, 1139–1146. AAAI Press/MIT Press, 1996.Cuartero, A., Santos, O.C., Granado, J., Raffenne, E. and Boticario, J.G. Mangement of standard-based User Model and Device Profile in OpenACS. Proceedings of the International Conference and Workshops on Community based environments, 2008.Baldiris, S., Santos, O., Boticario J., Fabregat R., Los estándares educativos como herramienta de modelado de cursos que proveen adaptaciones dinámicas a los usuarios, Revista Iberoamericana de Informática Educativa, 2008.Mejía, C., Baldiris, S., Gómez, S., and Fabregat, R. Adaptation process to deliver content based on user learning styles, International Conference of Education, Research and Innovation (IBSN: 978-84-612-5091-2), 2008, International Association of Technology, Education and Development, Madrid (Spain), 2008.Mancera, L., Baldiris, N., Fabregat, R.: Modelling Collaborative Competence Level using Machine Learning TechniquesHuerva, D., Velez, J., Baldiris, S., Fabregat, R., Merida, D: Adoption of courses and learning environment to the user context in dotLRN. International Conference on Innovation in Software Engineering. Vienna – Austria. 10-12 December, 2008.Merida, D., Cannataro, M., Fabregat, R. and Arteaga, C.: MAS-SHAAD a Multiagent System an Adaptive Hypermedia System. 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