Learning Object Assembly Based on Learning Styles

The goal of this paper is to develop a system, referred to as the Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students’ learning styles and term-based queries and produces a new outcome. The first step ranks LOs using a unified learning style model and creates better LOs by merging the top-ranked LOs. The second step maps LOs onto a hierarchy of concepts to avoid including duplicated topics in the merged LO. Fifty-six students were randomly split into experimental and control groups. The experimental group browsed the LOs retrieved by the msMLO based on the students’ learning styles, term-based queries and merge functionality, whereas the control group browsed the LOs retrieved based on the students’ learning styles and term-based queries. The results demonstrated that the experimental group improves their learning performance, thus msMLO is a promising approach.

[1]  Rob Koper,et al.  Combining reusable learning resources and services to pedagogical purposeful units of learning , 2003 .

[2]  Otis Gospodnetic,et al.  Lucene in Action, Second Edition: Covers Apache Lucene 3.0 , 2010 .

[3]  Grigorios Tsoumakas,et al.  An adaptive personalized news dissemination system , 2009, Journal of Intelligent Information Systems.

[4]  D. Kolb Experiential Learning: Experience as the Source of Learning and Development , 1983 .

[5]  José Angel Olivas,et al.  Hiperion: A fuzzy approach for recommending educational activities based on the acquisition of competences , 2013, Inf. Sci..

[6]  Chien-Sing Lee,et al.  Learning Objects Reusability and Retrieval through Ontological Sharing: A Hybrid Unsupervised Data Mining Approach , 2007, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007).

[7]  José Fernando Rodrigues,et al.  An approach to design the student interaction based on the recommendation of e-learning objects , 2010, SIGDOC '10.

[8]  Adolfo Guzmán-Arenas,et al.  Automatic Building of an Ontology from a Corpus of Text Documents Using Data Mining Tools , 2012 .

[9]  Sebastián Ventura,et al.  Personalized Links Recommendation Based on Data Mining in Adaptive Educational Hypermedia Systems , 2007, EC-TEL.

[10]  Adolfo Guzmán-Arenas,et al.  Measuring the understanding between two agents through concept similarity , 2006, Expert Syst. Appl..

[11]  Ezra Kaahwa Mugisa,et al.  Improving Learning Object Reuse Through OOD: A Theory of Learning Objects , 2010, J. Object Technol..

[12]  Eugenijus Kurilovas,et al.  Web 3.0 - Based personalisation of learning objects in virtual learning environments , 2014, Comput. Hum. Behav..

[13]  Nian-Shing Chen,et al.  Learning styles and cognitive traits - Their relationship and its benefits in web-based educational systems , 2009, Comput. Hum. Behav..

[14]  Vincent P. Wade,et al.  Personalisation in the wild: providing personalisation across semantic, social and open-web resources , 2011, HT '11.

[15]  Stephen J. H. Yang,et al.  Enhancing learning resources reusability with a new learning design framework , 2005, Fifth IEEE International Conference on Advanced Learning Technologies (ICALT'05).

[16]  Mercedes Gómez-Albarrán,et al.  A Semantically Enriched Context-Aware OER Recommendation Strategy and Its Application to a Computer Science OER Repository , 2014, IEEE Transactions on Education.

[17]  Dong Zhou,et al.  Improving search via personalized query expansion using social media , 2012, Information Retrieval.

[18]  Milad Shokouhi,et al.  Query Expansion Using External Evidence , 2009, ECIR.

[19]  Gwo-Jen Hwang,et al.  Development of an Adaptive Learning System with Multiple Perspectives based on Students? Learning Styles and Cognitive Styles , 2013, J. Educ. Technol. Soc..

[20]  Paul-Alexandru Chirita,et al.  Personalized query expansion for the web , 2007, SIGIR.

[21]  R. Slaughter,et al.  Use of a unified learning style model in pharmacy curricula , 2014 .

[22]  Víctor Hugo Menéndez-Domínguez,et al.  A framework for recommendation in learning object repositories: An example of application in civil engineering , 2013, Adv. Eng. Softw..

[23]  Antonio R. Anaya,et al.  Recommender system in collaborative learning environment using an influence diagram , 2013, Expert Syst. Appl..

[24]  Joemon M. Jose,et al.  Personalizing Web Search with Folksonomy-Based User and Document Profiles , 2010, ECIR.

[25]  S. B. Aher,et al.  Combination of machine learning algorithms for recommendation of courses in E-Learning System based on historical data , 2013, Knowl. Based Syst..

[26]  R. Felder,et al.  Learning and Teaching Styles in Engineering Education. , 1988 .

[27]  Y. C. Huang,et al.  A system for the sharing and reuse of learning objects , 2014, 2014 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE).

[28]  Noor Azida Sahabudin,et al.  Personalized Learning and Learning Style among Upper Secondary School Students , 2013 .

[29]  Jong Hyuk Park,et al.  Personlized English reading sequencing based on learning portfolio analysis , 2014, Inf. Sci..

[30]  Ralf Steinmetz,et al.  Multigranularity reuse of learning resources , 2011, TOMCCAP.

[31]  Elvira Popescu A Unified Learning Style Model for Technology-Enhanced Learning: What, Why and How? , 2010, Int. J. Distance Educ. Technol..

[32]  Ana Casali,et al.  A Recommender System for Learning Objects Personalized Retrieval , 2012 .

[33]  Enrique Herrera-Viedma,et al.  A quality based recommender system to disseminate information in a university digital library , 2014, Inf. Sci..

[34]  Sofia Stamou,et al.  Search personalization through query and page topical analysis , 2009, User Modeling and User-Adapted Interaction.

[35]  Brandon Muramatsu,et al.  Draft Standard for Learning Object Metadata , 2002 .

[36]  Erik Duval,et al.  Context-Aware Recommender Systems for Learning: A Survey and Future Challenges , 2012, IEEE Transactions on Learning Technologies.

[37]  Hendrik Drachsler,et al.  Recommender Systems in Technology Enhanced Learning , 2011, Recommender Systems Handbook.

[38]  Mojtaba Salehi,et al.  Hybrid recommendation approach for learning material based on sequential pattern of the accessed material and the learner's preference tree , 2013, Knowl. Based Syst..