گروه‌بندی یادگیرندگان در سامانه‌های تطبیق یادگیری به کمک روش خوشه‌بندی پیوندی فازی
الموضوعات :
محمدصادق رضایی
1
(دانشگاه تربیت مدرس)
غلامعلی منتظر
2
(دانشگاه تربیت مدرس)
الکلمات المفتاحية: خوشه‌بندی پیوندی سبک یادگیری گروه‌بندی یادگیرندگان مجموعه فازی یادگیری الکترونیکی یادگیری تطبیقی,
ملخص المقالة :
کیفیت سامانه‌های یادگیری تطبیقی و مشارکتی به نحوه توصیف مناسب یادگیرندگان و نیز دقت و صحت تفکیک یادگیرندگان در گروه‌های همگن و غیر همگن وابسته است. در روش‌های ارائه‌شده برای گروه‌بندی یادگیرندگان در محیط یادگیری الکترونیکی، محققان اغلب به دنبال بهبود روش‌های پایه از طریق ترکیب آنها با روش‌های بهینه‌سازی هستند. این امر موجب پیچیده‌تر شدن روش‌های گروه‌بندی می‌شود و کیفیت نه چندان مناسب گروه‌های حاصل را به دنبال دارد. در این مقاله روشی مبتنی بر نظریه فازی برای انتخاب خوشه‌های مناسب در روش خوشه‌بندی پیوندی معرفی شده است. در این روش هر خوشه به صورت مجموعه‌ای فازی مدل‌سازی شده و خوشه‌های متناظر تعیین گردیده و بهترین آنها به عنوان خوشه مناسب انتخاب شده است. این روش موجب افزایش دقت روش خوشه‌بندی پیوندی می‌شود. نتایج ارزیابی تجربی روش پیشنهادی بر اساس دو شاخص "Davies-Bouldin" و "خلوص و تجمع" نشان می‌دهد این روش دقت بیشتری نسبت به سایر روش‌های خوشه‌بندی در شناسایی گروه‌ها داشته است.
[1] D. Zhang, J. L. Zhao, L. Zhou, and J. F. Nunamaker Jr., "Can e-learning replace classroom learning?" Commun. ACM, vol. 47, no. 5, pp. 75-79, May 2004.
[2] D. R. Garrison, E-learning in the 21st Century: A Framework for Research and Practice, Second Ed., USA: Taylor & Francis, pp. 57-58, 2011.
[3] M. Driscoll, "Blended learning: let's get beyond the hype," E-Learn., vol. 3, no. 3, p. 35, 2002.
[4] B. D. Nye, "Intelligent tutoring systems by and for the developing world: a review of trends and approaches for educational technology in a global context," Int. J. Artif. Intell. Educ., vol. 25, no. 2, pp. 177-203, 2014.
[5] Y. Akbulut and C. S. Cardak, "Adaptive educational hypermedia accommodating learning styles: a content analysis of publications from 2000 to 2011," Comput. Educ., vol. 58, no. 2, pp. 835-842, Feb. 2012.
[6] E. H. A. Essaid El Bachari and M. El Adnani, "E-learning personalization based on dynamic learners' preference," International J. of Computer Science & Information Technology, IJCSIT, vol. 3, no. 3, pp. 200-216, 2011.
[7] V. Shute and B. Towle, "Adaptive e-learning," Educ. Psychol., vol. 38, no. 2, pp. 105-114, 2003.
[8] B. Beldagli and T. Adiguzel, "Illustrating an ideal adaptive e-learning: a conceptual framework," Procedia-Soc. Behav. Sci., vol. 2, no. 2, pp. 5755-5761, 2010.
[9] 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," User Model. User-Adapt. Interact., vol. 13, no. 3, pp. 213-267, Aug. 2003.
[10] E. H. A. Essaid El Bachari and M. El Adnani, "E-learning personalization based on dynamic learners' preference," International J. of Computer Science & Information Technology, IJCSIT, vol. 3, no. 3, pp. 200-216, Jun. 2011.
[11] A. Kardan and Y. Einavypour, "Classification based on learner's ability and emotionality for selecting a suitable teaching method," in Proc. 3rd Int. Conf. on Virtual Learning, ICVL'08, pp. 231-6 , 2008.
[12] D. Zakrzewska, "Cluster analysis in personalized e-learning systems," Intelligent Systems for Knowledge Management, Springer, vol. 252, pp. 229-250, 2009.
[13] D. Zakrzewska and A. Wojciechowski, "Identifying students usability needs in collaborative learning environments," in Human System Interactions, Conf. on, pp. 862-867, 25-27 May 2008.
[14] K. Zhang, L. Cui, H. Wang, and Q. Sui, "An improvement of matrix-based clustering method for grouping learners in e-learning," in Proc. 11th Int. Conf. on Computer Supported Cooperative Work in Design, CSCWD'07, pp. 1010-1015, 26-28 Apr. 2007.
[15] Q. Zheng, J. Ding, J. Du, and F. Tian, "Assessing method for e-learner clustering," in Proc. 11th Int. Conf. on Computer Supported Cooperative Work in Design, CSCWD'07, pp. 979-983, 26-28 Apr. 2007.
[16] D. Zakrzewska, "Using clustering technique for students' grouping in intelligent e-learning systems," Springer, Lecture Notes in Computer Science, vol. 5298, pp. 403-410, 2008.
[17] F. Ghorbani and G. A. Montazer, "Learners grouping in e-learning environment using evolutionary clustering approach," Iran. J. Inf. Commun. Technol. IJICT, vol. 3, no. 3, pp. 9-19, 2011.
[18] X. Wu, Q. Zheng, Y. Fu, and H. Wang, "Grouping e-learners based on clustering," in Proc. Int. Conf. on Electrical and Control Engineering, ICECE, pp. 206-209, 16-18 Sep. 2011.
[19] R. Z. Cabada, M. L. Barron Estrada, and C. A. Reyes Garcia, "EDUCA: a web 2.0 authoring tool for developing adaptive and intelligent tutoring systems using a kohonen network," Expert Syst. Appl., vol. 38, no. 8, pp. 9522-9529, 2011.
[20] S. E. Peter, E. Bacon, and M. Dastbaz, "Adaptable, personalised e-learning incorporating learning styles," Campus-Wide Inf. Syst., vol. 27, no. 2, pp. 91-100, 1-3 Jul. 2010.
[21] R. Zatarain-Cabada, et al., "Authoring neuro-fuzzy tutoring systems for M and E-learning," MICAI 2008: Advances in Artificial Intelligence, Springer, vol. 5317, pp. 789-796, 2008.
[22] F. Tian, S. Wang, C. Zheng, and Q. Zheng, "Research on e-learner personality grouping based on fuzzy clustering analysis," in Proc.12th Int. Conf. on Computer Supported Cooperative Work in Design, CSCWD'08., pp. 1035-1040, 16-18 Apr. 2008.
[23] C. A. Bruce, Using Cattell's 16PF to Identify a Student Leader Profile, Ph.D. Diss, Roosevelt University, 2013.
[24] V. Tsiriga and M. Virvou, "Initializing the student model using stereotypes and machine learning," in Proc. IEEE Int. Conf. on Systems, Man, and Cybernetics, vol. 2, pp. 404-409, Oct. 2002.
[25] Q. Yang, X. Wang, Z. Huang, and S. Zheng, "Research of student model based on bayesian network," in Proc. 1st IEEE Int. Symp. on Information Technologies and Applications in Education, ISITAE'07, pp. 514-519, 23-25 Nov. 2007.
[26] C. A. Carver Jr, R. A. Howard, and W. D. Lane, "Enhancing student learning through hypermedia courseware and incorporation of student learning styles," IEEE Trans. on Educ., vol. 42, no. 1, pp. 33-38, Feb. 1999.
[27] N. Bajraktarevic, W. Hall, and P. Fullick, "Incorporating learning styles in hypermedia environment: empirical evaluation," in Proc. 14th Conf. on Hypertext and Hypermedia, pp. 41-53, Nottingham, UK, Aug. 2003.
[28] E. Triantafillou, A. Pomportsis, S. Demetriadis, and E. Georgiadou, "The value of adaptivity based on cognitive style: an empirical study," Br. J. Educ. Technol., vol. 35, no. 1, pp. 95-106, 2004.
[29] E. Sangineto, N. Capuano, M. Gaeta, and A. Micarelli, "Adaptive course generation through learning styles representation," Univers. Access Inf. Soc., vol. 7, no. 1-2, pp. 1-23, 2008.
[30] S. Graf and K. Kinshuk, "Providing adaptive courses in learning management systems with respect to learning styles," in Proc. World Conf. on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 2576-2583, 2007.
[31] K. Chrysafiadi and M. Virvou, "Student modeling approaches: a literature review for the last decade," Expert Syst. Appl., vol. 40, no. 11, pp. 4715-4729, 2013.
[32] F. Coffield, et al., Learning Styles and Pedagogy in Post16 Learning, Available: http://www.leerbeleving.nl/wp-content/uploads/2011/09/learning-styles.pdf, Retrived on 9 Aug. 2014
[33] S. Graf, Adaptivity in Learning Management Systems Focussing on Learning Styles, Ph.D. Diss., Vienna University of Technology, 2007.
[34] G. A. Montazer and M. S. Rezaei, "A new approach in e-learners grouping using hybrid clustering method," in Proc Int. Conf. on. Education and E-Learning Innovations, ICEELI'12, 5 pp., 1-3 Jul. 2012.
[35] D. L. Davies and D. W. Bouldin, "A cluster separation measure," Pattern Anal. Mach. Intell. IEEE Trans. on, vol. 1, no. 2, pp. 224-227, Feb. 1979.
[36] Y. Lai and C. Hwang, Fuzzy Mathematical Programming: Methods and Applications, New York: Springer Verlag, 1995.
[37] E. Kanninent, Learning Styles in Virtual Learning Environments, Master of Science, Electrical engineering, Tamper University of Technology, Suopellonkatu, 2009.
