Personalization of Foreign Language Education in the LMS Moodle Environment
The paper deals with new processes in e-learning to achieve the most effective path through a course for each student. In order to achieve such an ideal path through an e-learning course (here a course of the English language), a new methodology has been developed and special components have been introduced, which enabled to create an individual study plan for each student individually. New components consist of two blocks. A block consisting in finding out student’s language knowledge and a block of sensory preferences. These blocks provided input values and information for creating a verification e-course. A great benefit is that the proposed methodology used existing possibilities of a conditional progress through a course while introducing the new components enabled to create individual study plans in an automated way. This comprehensive system has been verified on a sample set of students of the bachelor study program Applied Informatics at the Department of Informatics and Computers, Faculty of Science, University of Ostrava, in winter term 2014.
Keywordse-learning Language learning LMS Personalized education
The research described here has been financially supported by University of Ostrava grant SGS15/PřF/2015.
- 1.Bos, E., van de Plassche, J.: A knowledge-based, english verb-form tutor. J. Artif. Intell. Educ. 5(1), 107–129 (1994)Google Scholar
- 2.Rudak, L.: Susceptibility to e-teaching. In: Conference Proceedings: ICT for Competitiveness 2012, pp. 10–16, Karviná (2012)Google Scholar
- 3.Murphy, M., McTear, M.: Learner modelling for intelligent CALL. In: Jameson, A., Paris, C., Tasso, C. (eds.) Proceedings of the Sixth International Conference on User Modeling, pp. 301–312. Springer, Vienna (1997)Google Scholar
- 4.Kostolanyová, K.: Teorie adaptivního e-learningu. Ostravská univerzita, Ostrava (2012)Google Scholar
- 5.El-Hmoudová, D., Milková, E., Garant, G.: Computer-based testing in the field of foreign language assessment. In: Proceedings of Efficiency and Responsibility in Education, Czech University of life sciences, Prague (2012)Google Scholar
- 6.Samson, D., et al.: An architecture for web-based e-learning promoting re-usable adaptive educational e-content. Educ. Technol. Soc. 1, 5 (2002)Google Scholar
- 7.Bradáč, V.: Adaptive model to support decision-making in language e-learning. In: International Conference on Education and New Learning Technologies - Proceedings, pp. 4036–4045, Barcelona (2013)Google Scholar
- 8.Habiballa, H., et al.: Using software package LFLC 2000. In: 2nd International Conference Aplimat 2003, pp. 355–358, Bratislava (2003)Google Scholar
- 9.Bradáč, V.: Enhacing assessment of students’ knowledge using fuzzy logic in e-learning. In: 10th International Scientific Conference on Distance Learning in Applied Informatics, pp. 251–262. Wolters Kluwer, Štůrovo (2014)Google Scholar
- 10.VARK homepage. http://vark-learn.com/home/
- 11.LEITE, W.L., et al.: Attempted validation of the Scores of the VARK: Learning Styles Inventory with Multitrait-Multimethod Confirmatory Factor Analysis Models, p. 2. Sage publications, New York (2009)Google Scholar