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Issue No.03 - July-September (2009 vol.2)
pp: 203-215
Carla Limongelli , University RomaTre, Rome
Filippo Sciarrone , University RomaTre, Rome
Marco Temperini , Sapienza University, Rome
Giulia Vaste , University RomaTre, Rome
ABSTRACT
LS-Plan is a framework for personalization and adaptation in e-learning. In such framework an Adaptation Engine plays a main role, managing the generation of personalized courses from suitable repositories of learning nodes and ensuring the maintenance of such courses, for continuous adaptation of the learning material proposed to the learner. Adaptation is meant, in this case, with respect to the knowledge possessed by the learner and her learning styles, both evaluated prior to the course and maintained while attending the course. Knowledge and Learning styles are the components of the student model managed by the framework. Both the static, precourse, and dynamic, in-course, generation of personalized learning paths are managed through an adaptation algorithm and performed by a planner, based on Linear Temporal Logic. A first Learning Objects Sequence is produced based on the initial learner's Cognitive State and Learning Styles, as assessed through prenavigation tests. During the student's navigation, and on the basis of learning assessments, the adaptation algorithm can output a new Learning Objects Sequence to respond to changes in the student model. We report here on an extensive experimental evaluation, performed by integrating LS-Plan in an educational hypermedia, the LecompS web application, and using it to produce and deliver several personalized courses in an educational environment dedicated to Italian Neorealist Cinema. The evaluation is performed by mainly following two standard procedures: the As a Whole and the Layered approaches. The results are encouraging both for the system on the whole and for the adaptive components.
INDEX TERMS
Personalized learning, adaptive web-based system, learning styles.
CITATION
Carla Limongelli, Filippo Sciarrone, Marco Temperini, Giulia Vaste, "Adaptive Learning with the LS-Plan System: A Field Evaluation", IEEE Transactions on Learning Technologies, vol.2, no. 3, pp. 203-215, July-September 2009, doi:10.1109/TLT.2009.25
REFERENCES
[1] E. Alfonseca, R.M. Carro, E. Martín, A. Ortigosa, and P. Paredes, “The Impact of Learning Styles on Student Grouping for Collaborative Learning: A Case Study,” User Modeling and User-Adapted Interaction, vol. 16, nos. 3/4, pp. 377-401, 2006.
[2] N. Bajraktarevic, W. Hall, and P. Fullick, “Incorporating Learning Styles in Hypermedia Environment: Empirical Evaluation,” Proc. 14th Conf. Hypertext and Hypermedia, pp. 41-52, 2003.
[3] M. Baldoni, C. Baroglio, I. Brunkhorst, E. Marengo, and V. Patti, “Reasoning-Based Curriculum Sequencing and Validation: Integration in a Service-Oriented Architecture,” Proc. Second European Conf. Technology Enhanced Learning (EC-TEL), pp. 426-431, 2007.
[4] M. Baldoni, C. Baroglio, V. Patti, and L. Torasso, “Reasoning About Learning Object Metadata for Adapting SCORM Courseware,” Proc. Int'l Workshop Eng. the Adaptive Web: Methods and Technologies for Personalization and Adaptation (EAW '04), 2004.
[5] E. Brown, T. Fisher, and T. Brailsford, “Real Users, Real Results: Examining the Limitations of Learning Styles within AEH,” Proc. 18th Conf. Hypertext and Hypermedia, pp. 57-66, 2007.
[6] P. Brusilowsky, “Adaptive Hypermedia,” User Modeling and User-Adapted Interaction, vol. 11, pp. 87-110, 2001.
[7] P. Brusilovsky, C. Karagiannidis, and D. Sampson, “Layered Evaluation of Adaptive Learning Systems,” Int'l J. Continuing Eng. Education and Life-Long Learning, vol. 14, nos. 4/5, pp. 402-421, 2004.
[8] P. Brusilovsky and E. Millan, “User Models for Adaptive Hypermedia and Adaptive Educational Systems,” The Adaptive Web: Methods and Strategies of Web Personalization, P. Brusilovsky, A. Kobsa, and W. Nejdl, eds., Springer-Verlag, 2007.
[9] P. Brusilowsky and J. Vassileva, “Course Sequencing Techniques for Large-Scale Web-Based Education,” Int'l J. Continuing Eng. Education and Life-Long Learning, vol. 13, pp. 75-94, 2003.
[10] T. Bylander, “The Computational; Complexity of Propositional Strips Planning,” Artifical Intelligence, vol. 69, nos. 1/2, pp. 165-204, 1994.
[11] C.A. Carver, R.A. Howard, and W.D. Lane, “Enhancing Student Learning Through Hypermedia Courseware and Incorporation of Student Learning Styles,” IEEE Trans. Education, vol. 42, no. 1, pp.33-38, Feb. 1999.
[12] D.N. Chin, “Empirical Evaluation of User Models and User-Adapted Systems,” User Modeling and User-Adapted Interaction, vol. 11, no. 1, pp. 181-194, Mar. 2001.
[13] M. Cialdea Mayer, C. Limongelli, A. Orlandini, and V. Poggioni, “Linear Temporal Logic As an Executable Semantics for Planning Languages,” J. Logic, Language, and Information, vol. 1, no. 16, pp.63-89, Jan. 2007.
[14] F. Coffield, D. Moseley, E. Hall, and K. Ecclestone, Should We be Using Learning Styles? What Research Has to Say to Practice. Learning & Skills Research Centre, 2004.
[15] Learning Technology Standards Committee, “Draft Standard for Learning Object Metadata,” Technical Report 1484.12.1-2002, 2002.
[16] A. Cristea and L. Calvi, “The Three Layers of Adaptation Granularity,” Proc. Int'l Conf. User Modeling (UM '03), pp. 4-14, 2003.
[17] A. Cristea and A. De Mooij, “Adaptive Course Authoring: My Online Teacher,” Proc. 10th Int'l Conf. Telecomm. (ICT '03), vol. 2, pp. 1762-1769, 2003.
[18] A. Cristea and A. De Mooij, “LAOS: Layered WWW AHS Authoring Model and Its Corresponding Algebraic Operators,” Proc. Int'l World Wide Web Conf. (WWW '03), Alternate Education Track, 2003.
[19] P. De Bra, A. Aerts, and B. Rousseau, “Concept Relationship Types for AHA! 2.0,” Proc. World Conf. E-Learning in Corporate, Govt., Healthcare, and Higher Education (E-Learn '02), Assoc. for the Advancement of Computing in Education (AACE '02), M. Driscoll and T.C. Reeves, eds., pp. 1386-1389, 2002.
[20] P. De Bra, D. Smits, and N. Stash, “Creating and Delivering Adaptive Courses with AHA!” Proc. European Conf. Technology Enhanced Learning (EC-TEL '06), pp. 21-33, 2006.
[21] R.M. Felder and L.K. Silverman, “Learning and Teaching Styles in Engineering Education,” Eng. Education, vol. 78, no. 7, pp. 674-681, 1988.
[22] R.M. Felder and J. Spurlin, “Application, Reliability and Validity of the Index of Learning Styles,” Int'l J. Eng. Education, vol. 21, no. 1, pp. 103-112, 2005.
[23] C. Gena, “Methods and Techniques for the Evaluation of User-Adaptive Systems,” Knowledge Eng. Rev., vol. 20, no. 1, pp. 1-37, 2005.
[24] S. Graf and Kinshuk, “Providing Adaptive Courses in Learning Management Systems with Respect to Learning Styles,” Proc. World Conf. E-Learning in Corporate, Govt., Healthcare, and Higher Education (E-Learn '07), pp. 2576-2583, 2007.
[25] J. Hodges and E. Lehmann, “The Efficiency of Some Non Parametric Competitors of the t-Test,” Annals of Math. Statistics, vol. 35, pp. 324-335, 1956.
[26] J. Hodges and E. Lehmann, “Estimates of Location Based on Rank Tests,” Annals of Math. Statistics, vol. 34, pp. 598-611, 1963.
[27] M. Hollander, D. Wolfe, and R. Cohen, Nonparametric Statistical Methods. John Wiley and Sons, 1973.
[28] K. Höök, “Evaluating the Utility and Usability of an Adaptive Hypermedia System,” Proc. Second Int'l Conf. Intelligent User Interfaces (IUI '97), pp. 179-186, 1997, doi:10.1145/238218.238320.
[29] D.A. Kolb, Experiential Learning: Experience As the Source of Learning and Development. Prentice-Hall, 1984.
[30] C. Limongelli, F. Sciarrone, and G. Vaste, “Ls-Plan: An Effective Combination of Dynamic Courseware Generation and Learning Styles in Web-Based Education,” Proc. Fifth Int'l Conf. Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 133-142, 2008.
[31] C. Limongelli, F. Sciarrone, and G. Vaste, “An Application of the LS-Plan System to an Educational Hypermedia,” Int'l J. Web-Based Learning and Teaching Technologies, vol. 4, no. 1, pp.16-34, 2009.
[32] T.A. Litzinger, S.H. Lee, J.C. Wise, and R.M. Felder, “A Study of the Reliability and Validity of the Felder Soloman Index of Learning Styles,” Proc. Am. Soc. for Eng. Education Ann. Conf. and Exposition, 2005.
[33] N. Manouselis and D. Sampson, “Agent-Based E-Learning Course Discovery and Recommendation: Matching Learner Characteristics with Content Attributes,” Int'l J. Computers and Applications (IJCA '03), special issue on intelligence and technology in educational applications, vol. 25, no. 1, pp. 50-64, July 2003.
[34] J. Masthoff, The Evaluation of Adaptive Systems, pp.329-347. IGI Publishing, 2003.
[35] G. Pask, “Styles and Strategies of Learning,” British J. Educational Psychology, vol. 46, pp. 128-148, 1976.
[36] J. Rubin, Handbook of Usability Testing. John Wiley & Sons, Inc., 1994.
[37] E. Sangineto, N. Capuano, M. Gaeta, and A. Micarelli, “Adaptive Course Generation through Learning Styles Representation,” Universal Access in the Information Soc. (UAIS '08), vol. 7, nos. 1/2, pp. 1-23, 2008.
[38] S. Siegel and N.J. Castellan, Nonparametric Statistics for the Behavioral Sciences. McGraw-Hill Book Company, 1988.
[39] M. Temperini and U. Vitti, “A Web Application for Automated Course Configuration,” Proc. Eighth Int'l Conf. Information Technology Based Higher Education and Training (ITHET '07), July 2007.
[40] G. Weber and P. Brusilovsky, “Elm-Art: An Adaptive Versatile System for Web-Based Instruction,” Int'l J. Artificial Intelligence in Education, vol. 12, pp. 351-384, 2001.
[41] G. Weber, H.-C. Kuhl, and S. Weibelzahl, “Developing Adaptive Internet Based Courses with the Authoring System NetCoach,” Proc. Third Workshop Adaptive Hypertext and Hypermedia, P.D. Bra, P. Brusilovsky, and A. Kobsa, eds., pp. 35-48, http://wwwis.win. tue.nl/ah2001/papersGWeber-UM01.pdf , July 2001.
[42] F. Wilcoxon, “Probability Tables for Individual Comparisons by Ranking Methods,” Biometrics, vol. 3, pp. 119-122, 1947.
[43] H. Wu, “A Reference Architecture for Adaptive Hypermedia Applications,” PhD thesis, Eindhoven Univ. of Tech nology, 2002.
[44] M.S. Zywno and J.K. Waalen, “The Effect of Hypermedia Instruction on Achievement and Attitudes of Students with Different Learning Styles,” Proc. Ann. Am. Soc. for Eng. Education (ASEE '01) Conf., 2001.
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