Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31917
Learning Objects Content Presentation Adaptation Model Considering Students' Learning Styles

Authors: Zenaide Carvalho da Silva, Andrey Ricardo Pimentel, Leandro Rodrigues Ferreira


Learning styles (LSs) correspond to the individual preferences of a person regarding the modes and forms in which he/she prefers to learn throughout the teaching/learning process. The content presentation of learning objects (LOs) using knowledge about the students’ LSs offers them digital educational resources tailored to their individual learning preferences. In this context, the most relevant characteristics of the LSs along with the most appropriate forms of LOs' content presentation were mapped and associated. Such was performed in order to define the composition of an adaptive model of LO's content presentation considering the LSs, which was called Adaptation of Content Presentation of Learning Objects Considering Learning Styles (ACPLOLS). LO prototypes were created with interfaces that were adapted to students' LSs. These prototypes were based on a model created for validation of the approaches that were used, which were established through experiments with the students. The results of subjective measures of students' emotional responses demonstrated that the ACPLOLS has reached the desired results in relation to the adequacy of the LOs interface, in accordance with the Felder-Silverman LSs Model.

Keywords: Adaptation, interface, learning styles, learning objects, students.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 324


[1] Felder, R. M. and Silverman, L. K., Learning and Teaching Styles in Engineering Education. Journal of Engineering Education, 1988, 78(7):674–681.
[2] Wiley, D. A., Connecting learning objects to instructional design theory: A definition, a metaphor, and a taxonomy. Utah State Universit, 2001. Disponível em:
[3] Akbulut, Y. and Cardak, C. S., Adaptive educational hypermedia accommodating learning styles: A content analysis of publications from 2000 to 2011, Comput. Educ., 2012, vol. 58, no. 2, pp. 835–842.
[4] Felder, R. M and Soloman B., Index of Learning Style Questionnaire. North Carolina State University, 2006, Disponível em .
[5] Dunn, R., Learning styles: Theory, research, and practice. Em National Forum of Applied Educational Research Journal, 2000, volume 13, pp. 3–22.
[6] Kolb, D., Experiential learning: Experience as the Source of Learning and Development. Prentice-Hall Englewood Cliffs, 1984, NJ.
[7] Honey, P. and Mumford, A., The Learning Styles helper’s guide. Maldenhead Berks: Peter Honey Publications, 2000.
[8] Butler, K., Learning styles: personal exploration and practical applications. The learner’s dimension, 2003.
[9] Graf, S., Liu, T.-C. et al. , Supporting teachers in identifying students’ learning styles in learning management systems: an automatic student modelling approach. Journal of Educational Technology & Society, 2009, 12(4):3.
[10] Akbulut, Y. and Cardak, C. S., Adaptive educational hypermedia accommodating learning styles: A content analysis of publications from 2000 to 2011, Comput. Educ., vol. 58, no. 2, 2012, pp. 835–842.
[11] Feldman, J., Monteserin, A. and Amandi, A., Automatic detection of learning styles: state of the art. Artificial Intelligence Review, 2015, 1-30.
[12] Truong, H. M., Integrating learning styles and adaptive e-learning system: current developments, problems and opportunities. 2015, Computers in human behavior.
[13] Brusilovsky, P., Methods and techniques of adaptive hypermedia. In Adaptive hypertext and hypermedia, 2001, páginas 1–43. Springer.
[14] Silva, Z., Ferreira, L. e Pimentel, A., Modelo de apresentação adaptativa de objeto de aprendizagem baseada em estilos de aprendizagem. Em Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação-SBIE), 2016, vol. 27, pp. 717
[15] Mayer, R. E., Principles for managing essential processing in multimedia learning: segmenting, pretraining, and modality principles. In: MAYER, R. E., 2005, p. 169-182.
[16] García, P., Amandi, A., Schiaffino, S. e Campo, M., Evaluating bayesian networks’ precision for detecting students’ learning styles. Computers & Education, 2007, 49(3):794–808.
[17] Kinshuk, S. G., Providing adaptive courses in learning management systems with respect to learning styles. Em Proceedings of the world conference on e-learning in corporate, government, healthcare and higher education (e-Learn), 2007, pp. 2576–2583.
[18] Graf, S., Adaptivity in Learning Management Systems Focussing on Learning Styles. Vienna University of Technology, 2007.
[19] Graf, S. et al., Analysing the behaviour of students in learning management systems with respect to learning styles. Advances in Semantic Media Adaptation and Personalization, 2008, p.p 53–73.
[20] Sanders, D. A. e Bergasa-Suso, J., Inferring learning style from the way students interact with a computer user interface and the www. IEEE Transactions on Education, 2010, 53(4):613–620.
[21] Simsek, Ö., Atman, N., Inceoglu, M. M. e Arikan, Y. D., Diagnosis of learning styles based on active/reflective dimension of felder and silverman’s learning style model in a learning management system. International Conference on Computational Science and Its Applications, 2010, pp. 544–555.
[22] Ahmad, N. B. H. e Shamsuddin, S. M., A comparative analysis of mining techniques for automatic detection of student’s learning style. Em Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on, 2010, pp. 877–882. IEEE.
[23] Hamada, A. K., Rashad, M. Z. e Darwesh, M. G., Behavior analysis in a learning environment to identify the suitable learning style. International Journal of Computer Science & Information Technology (IJCSIT), 2011, 3(2):48–59.
[24] Dung, P. Q. e Florea, A. M., A literature-based method to automatically detect learning styles in learning management systems. Em Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, 2012, pp. 46. ACM.
[25] Saberi, N. e Montazer, G. A., A new approach for learners’ modeling in e-learning environment using lms logs analysis. Em 6th National and 3rd International Conference of E-Learning and E-Teaching, 2012, pp. 25–33. IEEE.
[26] Tidwell, J., Designing interfaces: Patterns for effective interaction design. O’Reilly Media, Inc, 2010.
[27] Silva, Z., Ferreira, L. e Pimentel, A., Learning Object Interface Adapted to the Learner's Learning Style. International Journal of Educational and Pedagogical Sciences, 2017, Vol:11, No:10.
[28] Zhang, P. e Li, N., The importance of affective quality. Communications of the ACM, 2005, 48(9):105–108.
[29] Bradley, M. M. e Lang, P. J., Measuring emotion: the self-assessment manikin and the semantic differential. Journal of behavior therapy and experimental psychiatry, 1994, 25(1):49–59.
[30] Lang, P. J., The cognitive psychophysiology of emotion: Fear and anxiety, 1985, pp. 131–170.
[31] Felder, R. M and B. Soloman, Index of Learning Style Questionnaire. North Carolina State University, 2006, Disponível em .