Naïve Bayes for Detecting Student’s Learning Style Using Felder-Silverman Index
This paper focuses on detecting student learning styles using the Felder-Silverman Index Learning Style (FSLM). Providing Adaptivity based on learning styles can support students and make the learning process easier for them. However, the student learning styles need to be identified and understood to provide the appropriate adaptability. In this case, we use a questionnaire instrument to detect student’s learning styles. This paper analyses of students from Professional Education Teacher (PPG) at the Ministry of Research, Technology, and Higher Education (Kemenristek DIKTI). The results show that 1998 students who filled out the questionnaire obtained the following conclusions for each zone with a balanced learning style about 29.9% for dimension processing, 34.78% for input dimension, and 36.98% for understanding dimension. However, most students have a moderate sensing learning style with 31.13% for each zone for the dimension of perception. This research contributes to some areas, such as providing FSLSM learning style with a large dataset and capturing students' learning styles based on four dimensions.
 S. Graf, “Analysis of learners ’ navigational behaviour and their learning styles in an online course,” pp. 116–131, 2010.
 Kefee, “Learning Style Theory and Practice,” p. 53, 1987.
 D. R. Shockley, “Learning Styles and Students’ Perceptions of Satisfaction in Community Collage Web-based Learning Environments,” p. 53, 1987.
 N. Ahmad, Z. Tasir, J. Kasim, and H. Sahat, “Automatic Detection of Learning Styles in Learning Management Systems by Using Literature-based Method,” Procedia - Soc. Behav. Sci., vol. 103, pp. 181–189, 2013.
 H. D. Surjono, “The Design of Adaptive E-Learning System based on Student ’ s Learning Styles,” Int. J. Comput. Sci. Inf. Technol., vol. 2, no. 5, pp. 2350–2353, 2011.
 et al. Klasnja-Milicevic, Aleksandra, “Computers & Education E-Learning personalization based on hybrid recommendation strategy and learning style identi fi cation,” vol. 56, pp. 885–899, 2011.
 C. Limongelli, F. Sciarrone, G. Vaste, D. I. A. Università, and R. Tre, “Personalized e-learning in Moodle : the Moodle _ LS System,” vol. 7, no. 2011, pp. 49–58.
 F. Ricci, “Context-aware music recommender systems : Workshop keynote abstract Context-Aware Music Recommender Systems [ Workshop Keynote Abstract ],” no. April 2012, pp. 10–12, 2014.
 M. A. J. C. A. Carver, “Enhancing student learning through hypermedia courseware and incorporation of student learning styles Enhancing Student Learning by Incorporating Learning Styles into Adaptive Hypermedia,” no. August, 2015.
 J. Lo, Y. Chan, and S. Yeh, “Computers & Education Designing an adaptive web-based learning system based on students ’ cognitive styles identi fi ed online,” Comput. Educ., vol. 58, no. 1, pp. 209–222, 2012.
 K. A. Papanikolaou, M. Grigoriadou, H. Kornilakis, and G. D. Magoulas, “Personalizing the Interaction in a Web-based Educational Hypermedia System : the case of INSPIRE,” pp. 213–267, 2003.
 and K. B.-B. Bostwick, Keiko, “Adaptive Quizzing As- sociated with an Increase in Overall Learning.” 2014.
 C. A. Carver, R. A. Howard, and W. D. Lane, “Enhancing Student Learning Through Hypermedia Courseware and Incorporation of Student Learning Styles,” vol. 42, no. 1, pp. 33–38, 1999.
 C. Wolf, “iWeaver : Towards Learning Style -based e-Learning in Computer Science Education,” vol. 20, 2002.
 E. Juan and J. E. Gilbert, “Arthur : Adapting Instruction to Accommodate Learning Style,” 1999.
 and R. B. R. M. Felder, “Understanding Student Differences,” no. January, 2005.
 E. Kanninen, “Learning Style and E-Learning,” 2008.
 F. Xhafa, T. Daradoumis, and A. A. Juan, Architectures for Distributed and Complex M-Learning Systems : 2009.
 F. A. Khan, S. Graf, E. R. Weippl, and A. M. Tjoa, “Integrated Approach for the Detection of Learning Styles & Affective States Integrated Approach for the Detection of Learning Styles & Affective States,” no. May 2014, 2009.
 W. L. Silverman and L. Forum, “LEARNING AND TEACHING STYLES,” vol. 78, no. June, pp. 674–681, 1988.
 D. H. Silva and F. A. Dorça, “An Automatic Approach for Customization of Teaching Process Based on Learning Styles in Adaptive and Intelligent Learning Systems,” vol. 22, 2014.
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