Ais standards, 2018 An ontological model for learning objects and pedagogical identifier repository
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An ontological model for learning objects and pedagogical identifier repository Jeanine A. DeFalco, PhD Amy Sommer, PhD ABSTRACT: In the effort to standardize tools and methods for authoring content for generalizable tutoring systems, this paper will build on Koutsomitropoulos and Solomou’s (2017) design for implementing a learning ontology repository linking learning objects with thesauri datasets and sources, and propose a more comprehensive ontological model that would include a pedagogical repository of scenarios with pedagogical identifier codes (PIC) (Hadji, Choi, & Jemnim, 2012). These PICs would facilitate the search and retrieval of pedagogical scenarios that more closely align with Bloom’s Revised Taxonomy, allowing for learning designs that move beyond traditional objectivist theory of learning. This ontological model would streamline authoring of courses in tutoring systems by way of including machine-understandable semantic annotations assigned to Learning Objects in order to increase interoperability with other repositories, aid in the use of discovery and search tools for authoring courses, as well as provide a more flexible approach to activity sequencing and pedagogical designs that more fully capture the complexity of learning, reflected in a broader range of learning theories. This ontological model could also be used for more effective authoring of adaptable tutoring courses, allowing an adaptive system to be reflexive not merely on learner traits and prior knowledge, but to adaptively scaffold increasingly complex discriminate intelligence, or higher order thinking skills. References Brawner, K. (2015, August). Authoring Tools for Adaptive Training–An Overview of System Types and Taxonomy for Classification. In International Conference on Augmented Cognition (pp. 562-569). Springer, Cham. Goldberg, B. (2015, August). Augmenting Instructional Practice in GIFT Using the Engine for Management of Adaptive Pedagogy (EMAP). In International Conference on Augmented Cognition (pp. 595-604). Springer, Cham. Hadji, H. B., Choi, H. J., & Jemni, M. (2012). Pedagogically-Driven Courseware Content Generation for Intelligent Tutoring Systems. International Journal of Fuzzy Logic and Intelligent Systems, 12(1), 77-85. Koutsomitropoulos, D. A., & Solomou, G. D. (2017). A learning object ontology repository to support annotation and discovery of educational resources using semantic thesauri. IFLA Journal, 0340035217737559. Marjanovic, O. (2007). Using process-oriented, sequencing educational technologies: some important pedagogical issues. Computers in Human Behavior, 23(6), 2742-2759. Ochoa, X., Carrillo, G., & Cechinel, C. (2014, September). Use of a Semantic Learning Repository to Facilitate the Creation of Modern e-Learning Systems. In Proceedings of the XV International Conference on Human Computer Interaction (p. 92). ACM. Ososky, S., Sottilare, R., Brawner, K., Long, R., & Graesser, A. (2015). Authoring Tools and Methods for Adaptive Training and Education in Support of the US Army Learning Model: Research Outline (No. ARL-SR-0339). US Army Research Laboratory Aberdeen Proving Ground, United States. Sánchez-Alonso, S., & Sicilia, M. A. (2005). Normative specifications of learning objects and learning processes: towards higher levels of automation in standardized e-learning. International journal of instructional technology and distance learning, 2(3), 3-12. Sicilia, M. Á., Lytras, M. D., Sánchez-Alonso, S., García-Barriocanal, E., & Zapata-Ros, M. (2011). Modeling instructional-design theories with ontologies: Using methods to check, generate and search learning designs. Computers in Human Behavior, 27(4), 1389-1398. Sinatra, A., Brawner, K., & Goodwin, G. (2015). Considerations for learner modeling in a domain-independent intelligent tutoring system framework. Retrieved on 1/4/18 at https://gifttutoring.org/attachments/download/1458/SinatraBrawnerGoodwin_DHSS2015 _CameraReady_071515_FINAL.pdf Sottilare, R. A., Long, R. A., & Goldberg, B. S. (2017, April). Enhancing the Experience Application Program Interface (xAPI) to Improve Domain Competency Modeling for Adaptive Instruction. In Proceedings of the Fourth (2017) ACM Conference on Learning@ Scale (pp. 265-268). ACM.Adaptive Instruction. In Proceedings of the Fourth (2017) ACM Conference on Learning@ Scale (pp. 265-268). ACM. Directory: attachments -> download attachments -> A unified Modeling Approach to Climate System Prediction James Hurrell* 1, Gerald A. Meehl 1, David Bader 2 download -> Code Item Android download -> On the design and implementation of the Open eCard App download -> High Resolution Model Intercomparison Project (HighResmip) R. J. Haarsma Download 12.13 Kb. Share with your friends:
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