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Assembling Learning Objects for Personalized Learning. An AI Planning Perspective
PrePrint
ISSN: 1541-1672
| ASCII Text | x | ||
| Antonio Garrido, Eva Onaindia, "Assembling Learning Objects for Personalized Learning. An AI Planning Perspective," IEEE Intelligent Systems, vol. 99, no. 1, pp. , , 5555. | |||
| BibTex | x | ||
| @article{ 10.1109/MIS.2011.36, author = {Antonio Garrido and Eva Onaindia}, title = {Assembling Learning Objects for Personalized Learning. An AI Planning Perspective}, journal ={IEEE Intelligent Systems}, volume = {99}, number = {1}, issn = {1541-1672}, year = {5555}, doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2011.36}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - MGZN JO - IEEE Intelligent Systems TI - Assembling Learning Objects for Personalized Learning. An AI Planning Perspective IS - 1 SN - 1541-1672 SP EP EPD - A1 - Antonio Garrido, A1 - Eva Onaindia, PY - 5555 KW - I.2.8.g Plan execution KW - formation KW - and generation KW - I.2.8.f Heuristic methods KW - I.2.8 Problem Solving KW - Control Methods KW - and Search KW - Intelligent Control KW - Social Computing KW - data mining KW - Recognition KW - Manifold KW - machine learning KW - I.2.8.g Plan execution KW - formation KW - and generation KW - education KW - e-learning KW - I.2 Artificial Intelligence KW - I Computing Methodologies KW - I.2.8 Problem Solving KW - Control Methods KW - and Search KW - VL - 99 JA - IEEE Intelligent Systems ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2011.36
The aim of educational systems is to assemble learning objects on a set of topics tailored to the goals and individual students' styles. Given the amount of available learning objects, the challenge of e-learning is to select the proper objects, define their relationships, and adapt their sequencing (i.e. course composition) to the specific needs, objectives and background of the student. This paper describes the general requirements for this course adaptation, the full potential of applying planning techniques on the construction of personalized e-learning routes, and how to accommodate the temporal and resource constraints to make the course applicable in a real scenario.
Index Terms:
I.2.8.g Plan execution, formation, and generation, I.2.8.f Heuristic methods, I.2.8 Problem Solving, Control Methods, and Search, Intelligent Control , Social Computing, data mining, Recognition, Manifold, machine learning, I.2.8.g Plan execution, formation, and generation, education, e-learning, I.2 Artificial Intelligence, I Computing Methodologies, I.2.8 Problem Solving, Control Methods, and Search,
Citation:
Antonio Garrido, Eva Onaindia, "Assembling Learning Objects for Personalized Learning. An AI Planning Perspective," IEEE Intelligent Systems, 06 April 2011. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/MIS.2011.36>
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