網路的普及帶動了數位學習發展，以求提升在數位學習環境中的學習效果。研究指出依據學生之學習風格提供適性的學習教材、學習策略或課程是為提升學生學習效果的關鍵方法之一。因此，為了達到適性學習，首要辨識學生的學習風格，然而，目前相關研究中，可以顯示出行為屬性和學習風格之間的關係卻少有學者關注，且大多相關研究只能顯示學習者屬於單一種學習風格。但每一位學習者都並非絕對屬於哪一種學習風格，絕大多數也存在其他學習風格的特性或潛在性。因而，本論文提出一個方法，可以分類並識別學生的學習風格，進一步可讓學習者了解其在各個學習風格中的可能性，並可自動分析行為屬性和各個學習風格的關係。本研究應用先驗演算法 (Apriori algorithm)並提出一種新的選擇法以找出各個學習風格有關的行為屬性。為了驗證本研究所提出的方法，本研究使用了三種資料庫來驗證，並且和用k個最鄰近點 (k-Nearest Neighbor)分類法結合基因演算法的分類機制來做比較。實驗結果指出本研究所提出的方法不僅可以有效的分類和識別學生的學習風格並且可以分析出學習風格和行為屬性之間的關係。

With the growing demand in e-learning, numerous researches have been proposed to enhance learning performance of students in e-learning environments. Numerous studies have indicated that providing adaptive learning materials, learning strategies or courses according to a student’s learning style is a critical issues to improve the learning performance of students. Hence, the first step for achieving adaptive learning environments is to identify students’ learning styles. However, so far the classification mechanisms proposed are rare to show the relation between the behavioral features and learning styles, but simply show which one learning style a student appears to have. This thesis proposes an approach to classify and identify students’ learning styles, and to know the potential a student has for different learning styles and automatically analyze the relation between the behavioral features and learning styles. The proposed approach uses Apriori algorithm with a new method to select the set that can identify the learning style. To verify the proposed approach, this thesis uses three datasets for experiment and compares with enhanced k-nearest neighbor (k-NN) classification combined with Genetic algorithms (GA). The experimental results indicate that the proposed approach can not only effectively classify and identify students’ learning styles but also analyze the relation between the value of behavioral feature and learning styles.

[1] Agrawal, R. and Srikant, R., "Fast algorithms for mining association rules," Proc. 20th int. conf. very large data bases, VLDB, vol. 1215, pp. 487-499, 1994.
[2] Alfonseca, E., Carro, R. M., Martín, E., Ortigosa, A., and Paredes, P., "The impact of learning styles on student grouping for collaborative learning: a case study," User Modeling and User-Adapted Interaction, vol. 16, pp. 377-401, 2006.
[3] Alkhuraiji, S., Cheetham, B., and Bamasak, O., "Dynamic adaptive mechanism in learning management system based on learning styles," in Advanced Learning Technologies (ICALT), 2011 11th IEEE International Conference on, 2011, pp. 215-217.
[4] Berglund, A., Blackne, J., and Jansson, N., "Proposing a Feedback System to Enhance Learning Based on Key Performance Indicators," International Journal of Quality Assurance in Engineering and Technology Education (IJQAETE), vol. 3, pp. 1-14, 2014.
[5] Brusilovsky, P., "Adaptive and intelligent technologies for web-based eduction," KI, vol. 13, pp. 19-25, 1999.
[6] Carver Jr, C. A., Howard, R. A., and Lane, W. D., "Enhancing student learning through hypermedia courseware and incorporation of student learning styles," Education, IEEE Transactions on, vol. 42, pp. 33-38, 1999.
[7] Castillo-Merino, D. and Serradell-López, E., "An analysis of the determinants of students’ performance in e-learning," Computers in Human Behavior, vol. 30, pp. 476-484, 2014.
[8] Chang, Y.-C., Kao, W.-Y., Chu, C.-P., and Chiu, C.-H., "A learning style classification mechanism for e-learning," Computers & Education, vol. 53, pp. 273-285, 2009.
[9] Chen, C.-M., Lee, H.-M., and Chen, Y.-H., "Personalized e-learning system using item response theory," Computers & Education, vol. 44, pp. 237-255, 2005.
[10] Coffield, F., Moseley, D., Hall, E., and Ecclestone, K., "Learning styles and pedagogy in post-16 learning: A systematic and critical review," 2004.
[11] El-Bishouty, M. M., Chang, T.-W., Graf, S., and Chen, N.-S., "Smart e-course recommender based on learning styles," Journal of Computers in Education, vol. 1, pp. 99-111, 2014.
[12] Felder, R. M. and Silverman, L. K., "Learning and teaching styles in engineering education," Engineering education, vol. 78, pp. 674-681, 1988.
[13] Felder, R. M., Silverman, L. K., and Solomon, B. A., Index of learning styles (ILS): North Carolina State University, 1996.
[14] Feldman, J., Monteserin, A., and Amandi, A., "Detecting students' perception style by using games," Computers & Education, vol. 71, pp. 14-22, 2014.
[15] Fleming, N., "VARK–Multimodal study strategies," Retrieved August, vol. 3, p. 2002, 2001.
[16] García, P., Amandi, A., Schiaffino, S., and Campo, M., "Evaluating Bayesian networks’ precision for detecting students’ learning styles," Computers & Education, vol. 49, pp. 794-808, 2007.
[17] Giesbers, B., Rienties, B., Tempelaar, D., and Gijselaers, W., "Investigating the relations between motivation, tool use, participation, and performance in an e-learning course using web-videoconferencing," Computers in Human Behavior, vol. 29, pp. 285-292, 2013.
[18] Graf, S., "An approach for detecting learning styles in learning management systems," in In, 2006.
[19] Graf, S., "Using cognitive traits for improving the detection of learning styles," in Database and Expert Systems Applications (DEXA), 2010 Workshop on, 2010, pp. 74-78.
[20] Gregorc, A. F. and Ward, H. B., "A new definition for individual," Nassp Bulletin, vol. 61, pp. 20-26, 1977.
[21] Huang, J., Wang, Y., Tan, T., and Cui, J., "A new iris segmentation method for recognition," in Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, 2004, pp. 554-557.
[22] Jeong, H.-Y. and Yeo, S.-S., "The quality model for e-learning system with multimedia contents: a pairwise comparison approach," Multimedia Tools and Applications, pp. 1-14, 2013.
[23] Joshi, M., Vaidya, R., and Lingras, P., "Automatic determination of learning styles," in Proc. 2nd international Conference on Education and Management Technology, IACSIT Press, Singapore, 2011.
[24] Keefe, J. W., Learning Style Theory and Practice: ERIC, 1987.
[25] Klašnja-Milićević, A., Vesin, B., Ivanović, M., and Budimac, Z., "E-Learning personalization based on hybrid recommendation strategy and learning style identification," Computers & Education, vol. 56, pp. 885-899, 2011.
[26] Kolb, D. A., Experiential learning: Experience as the source of learning and development vol. 1: Prentice-Hall Englewood Cliffs, NJ, 1984.
[27] Latham, A., Crockett, K., and McLean, D., "An adaptation algorithm for an intelligent natural language tutoring system," Computers & Education, vol. 71, pp. 97-110, 2014.
[28] Li, F. W., Lau, R. W., and Dharmendran, P., "An adaptive course generation framework," International Journal of Distance Education Technologies (IJDET), vol. 8, pp. 47-64, 2010.
[29] Lin, C. F., Hung, Y. H., Chang, R. I., and Hung, S. H., "Developing a problem-solving learning system to assess the effects of different materials on learning performance and attitudes," Computers & Education, vol. 77, pp. 50-66, 2014.
[30] Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., and Davis, T. J., "Effectiveness of virtual reality-based instruction on students' learning outcomes in K-12 and higher education: A meta-analysis," Computers & Education, vol. 70, pp. 29-40, 2014.
[31] Mumford, A. and Honey, P., "Questions and answers on learning styles questionnaire," Industrial and Commercial Training, vol. 24, 1992.
[32] Özpolat, E. and Akar, G. B., "Automatic detection of learning styles for an e-learning system," Computers & Education, vol. 53, pp. 355-367, 2009.
[33] Powers, D. M., "Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation," 2011.
[34] Reiff, J. C., "Learning Styles. What Research Says to the Teacher Series," 1992.
[35] Riding, R. and Rayner, S., Cognitive styles and learning strategies: Understanding style differences in learning and behavior: Routledge, 2013.
[36] Schiaffino, S., Garcia, P., and Amandi, A., "eTeacher: Providing personalized assistance to e-learning students," Computers & Education, vol. 51, pp. 1744-1754, 2008.
[37] Schnotz, W. and Kürschner, C., "A reconsideration of cognitive load theory," Educational Psychology Review, vol. 19, pp. 469-508, 2007.
[38] Sessink, O., Beeftink, R., Tramper, J., and Hartog, R., "Author-defined storage in the next generation learning management systems," in Advanced Learning Technologies, 2003. Proceedings. The 3rd IEEE International Conference on, 2003, pp. 57-61.
[39] Srikant, R., Vu, Q., and Agrawal, R., "Mining Association Rules with Item Constraints," in KDD, 1997, pp. 67-73.
[40] Stangl, W., "Der HALB-Test [The HALB test]," Retrieved April, vol. 24, p. 2006, 2002.
[41] Stash, N., Cristea, A., and De Bra, P., "Adaptation to learning styles in e-learning: Approach evaluation," 2006.
[42] Sternberg, R. J. and Grigorenko, E. L., "Are cognitive styles still in style?," American psychologist, vol. 52, p. 700, 1997.
[43] Surjono, H. D., "The Evaluation of a Moodle Based Adaptive e-Learning System," International Journal of Information & Education Technology, vol. 4, 2014.
[44] Sweller, J., Van Merrienboer, J. J., and Paas, F. G., "Cognitive architecture and instructional design," Educational psychology review, vol. 10, pp. 251-296, 1998.
[45] Triantafillou, E., Pomportsis, A., and Demetriadis, S., "The design and the formative evaluation of an adaptive educational system based on cognitive styles," Computers & Education, vol. 41, pp. 87-103, 2003.
[46] Tseng, J. C., Chu, H.-C., Hwang, G.-J., and Tsai, C.-C., "Development of an adaptive learning system with two sources of personalization information," Computers & Education, vol. 51, pp. 776-786, 2008.
[47] Wang, D., "Fast constructive-covering algorithm for neural networks and its implement in classification," Applied Soft Computing, vol. 8, pp. 166-173, 2008.
[48] Wirt, J., Choy, S., Rooney, P., Provasnik, S., Sen, A., and Tobin, R., "The Condition of Education 2004. NCES 2004-077," US Department of Education, 2004.
[49] Xenos, M., "Prediction and assessment of student behaviour in open and distance education in computers using Bayesian networks," Computers & Education, vol. 43, pp. 345-359, 2004.
[50] Yang, T.-C., Hwang, G.-J., and Yang, S. J.-H., "Development of an Adaptive Learning System with Multiple Perspectives based on Students? Learning Styles and Cognitive Styles," Educational Technology & Society, vol. 16, pp. 185-200, 2013.
[51] Yannibelli, V. and Amandi, A., "A deterministic crowding evolutionary algorithm to form learning teams in a collaborative learning context," Expert Systems with Applications, vol. 39, pp. 8584-8592, 2012.