İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği)
Yıl: 2014 Cilt: 14 Sayı: 3 Sayfa Aralığı: 1143 - 1168 Metin Dili: Türkçe İndeks Tarihi: 29-07-2022
İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği)
Öz: E-öğrenme sistemlerinde kendini uyarlayabilen yaklaşımların kullanımının günümüzde giderek artan önemi doğrultusunda, bu çalışmada e-öğrenme sistemleri için Bayes ağı odaklı ve makine öğrenmesine dayalı bir öğrenci modelleme orta katmanı ortaya konulmuş ve deneysel uygulamaları yapılmıştır. Öğrenci modelleme sisteminin dayandığı öğrenme biçemleri yaklaşımı olarak Felder ve Silvermanın öğrenme biçemleri modeli ile Felder ve Solomanın öğrenme biçemleri ölçeğinin görsel/sözel ve etkin/yansıtıcı boyutları esas alınmıştır. Felder ve Soloman tarafından hazırlanmış öğrenme biçemleri ölçeği Türkçeye uyarlanmış ve İngilizcenin yabancı dil öğreniminde bir konu bütününü kapsayan bir öğrenme içeriği tasarlanmıştır. İçerik, farklı öğrenme biçemlerine hitap edecek şekilde öğrenme sahnelerine bölünerek sayısallaştırılmış ve deneysel uygulama boyunca tüm araçların birlikte çalışabileceği bir yazılım geliştirilmiştir. Çalışmada ön-test son-test yarı-deneysel deseni kullanılmış ve toplam 46 gönüllü öğrenciyle çalışılmıştır. 23er kişilik deney ve kontrol gruplarının kullanımıyla öğrenci modelleme sistemi bazlı öğrenme ile geleneksel bilgisayar destekli öğrenme arasındaki akademik başarı artışları değerlendirilmiştir. Bulgular üzerinde tekrarlayan ölçümler arasında varyans çözümlemesi yapılmış ve %95 güven aralığında (p< 0,05) deney ve kontrol gruplarına öğrenme süreci boyunca verilen eğitimlerin akademik başarıda neden oldukları artışlar arasında anlamlı bir fark olmadığı gözlenmiştir. Ayrıca öğrenci modelleme sisteminin ürettiği öğrenci profillerinin başarımı ölçülerek alanyazındaki benzer çalışmalarla karşılaştırılmıştır. Bu çalışma kapsamında öne sürülen öğrenci modelleme sistemi uygulamaya katılan öğrencilerin öğrenme biçemlerinin görsel/sözel boyutta %41ini etkin/yansıtıcı boyutta ise %54ünü doğru teşhis etmiştir.
Anahtar Kelime: Konular:
Effect of bayesian student modeling on academic achievement in foreign language teaching (University level English preparatory school example)
Öz: Considering the increasing importance of adaptive approaches in CALL systems, this study implemented a machine learning based student modeling middleware with Bayesian networks. The profiling approach of the student modeling system is based on Felder and Silverman s Learning Styles Model and Felder and Soloman s Index of Learning Styles Questionnaire. The questionnaire was adapted to Turkish for this experimental study conducted with respect to the visual/verbal and active/reflective dimensions of the model. A topic in EFL was chosen for the learning content design, which was also carried into the digital domain and remastered as separate learning scenes for different learning styles. Computer software was also implemented to carry out the experimental learning processes. A quasi-experimental pre-test, post-test design was conducted with 46 volunteers, with 23 students assigned each to a control and an experimental group to compare academic achievement between student-based learning and conventional computer-based learning. No significant difference was found in academic achievement between the control and experimental groups after the experimental treatment. The diagnostic performance of the proposed student modeling system was also compared with performances from similar studies. This student modeling system had a successful prediction rate of 41% on the visual/verbal dimension and 54% on the active/reflective dimension, respectively.
Anahtar Kelime: Konular:
Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Bibliyografik
- Aiken, R. M., & Epstein, R. G. (2000). Ethical guidelines for AI in education: Starting a conversation. International Journal of Artificial Intelligence in Education, 11, 163-176. Alonso, F., Manrique, D., & Vines, J. M. (2009). A moderate constructivist e-learning instructional model evaluated on computer specialists. Computers and Education, 53(1), 57- 65.
- Aslan, B. G., & İnceoğlu, M. M. (2007). Machine learning based learner modeling for adaptive web-based learning, international conference on computational science and its applications, Malaysia. Lecture Notes in Computer Science, 4705, 1133-1145.
- Aslan, B. G. ve İnceoğlu, M. M. (2008). Bayesian öğrenci modellemesi. II. Uluslararası Bilgisayar ve Öğretim Teknolojileri Sempozyumu Bildiriler Kitabı içinde (s. 120- 126). Ankara: PegemA Yayınevi.
- Atman, N., İnceoğlu, M. M., Öğretmen, T. ve Aslan, B. G. (2009, Mayıs). Felder ve Soloman Öğrenme Biçemi Ölçeği etkin-yansıtıcı ve görsel-sözel boyutlarının geçerlik- güvenirlik çalışması. I. Uluslararası Türkiye Eğitim Araştırmaları Kongresinde sunulan bildiri, Çanakkale 18 Mart Üniversitesi.
- Baldwin, L., & Sabry, K. (2003). Learning styles for interactive learning systems. Innovations in Education and Teaching International, 40(4), 325-340.
- Beck, J. E., & Woolf, B. P. (2000). High-level student modeling with machine learning, 5th international conference on intelligent tutoring systems. Lecture Notes in Computer Science, 1839, 584-593.
- Best, J. W., & Kahn, J. V. (2006). Research in education. Boston: Allyn and Bacon.
- Brna, P., Cox, R. (1998). Adding intelligence to a learning environment: Learner-centered design? Journal of Computer Assisted Learning, 14, 268-277.
- Brown, E. J., Brailsford, T. J., Fisher, T., & Moore, A. (2009). Evaluating learning style personalization in adaptive systems: Quantitative methods and approaches. IEEE Transactions on Learning Technologies, 2(1), 10-22.
- Brown, E. J., Brailsford, T. J., Fisher, T., Moore, A., & Ashman, H. (2006). Reappraising cognitive styles in adaptive web applications. In Proceedings of the 15th International ACM International World Wide Web Conference (pp. 327-335).
- Brown, E., Cristea, A., Stewart, C., & Brailsford, T. (2005). Patterns in authoring of adaptive educational hypermedia: A taxonomy of learning styles. Educational Technology and Society, 8(3), 77-90.
- Brusilovsky, P. (1996). Methods and techniques of adaptive hypermedia. User Modeling and User-Adapted Interaction, 6(2-3), 87-129.
- Brusilovsky, P. (1999). Adaptive and intelligent technologies for web-based education. Künstliche Intelligenz [Special Issue on Intelligent Systems and Teleteaching], 4, 19-25. Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-Adapted Interaction, 11, 87-110.
- Brusilovsky, P. (2004). KnowledgeTree: A distributed architecture for e-learning. In Proceedings of the 13th International World Wide Web Conference [Session: Adaptive E-learning Systems] (pp. 104-113). New York.
- Cantoni, V., Cellario, M., & Porta, M. (2004). Perspectives and challenges in e-Learning: Towards natural interaction paradigms. Journal of Visual Languages and Computing, 15, 333-345.
- Carver, C. A., Howard, R. A., & Lane, W. D. (1999). Enhancing student learning through hypermedia courseware and incorporation of student learning styles. IEEE Transactions on Education, 42(1), 33-38.
- Charles, C. M., & Mertler, C. A. (2002). Introduction to educational research. Boston: Allyn and Bacon.
- Conati, C., Gertner A., & Vanlehn, K. (2002). Using Bayesian networks to manage uncertainty in student modeling. User Modeling and User-Adapted Interaction, 12, 371-417.
- Cook, D. A., & Smith, A. J. (2006). Validity of index of learning styles scores: Multitrait-multimethod comparison with three cognitive/learning style instruments. Medical Education, 40, 900-907.
- Creswell, J. W. (2002). Educational research. New Jersey: Merrill and Prentice-Hall.
- Cumming, G. (1998). Artificial intelligence in education: An exploration. Journal of Computer Assisted Learning, 14, 251-259.
- Edmonds, E. A. (1981). Adaptive man-computer interfaces. Computing Skills and the User Interface, 122, 389-426. Esposito, F., Lichelli, O., & Semeraro, G. (2004).
- Discovering student models in e-learning systems. Journal of Universal Computer Science, 10(1), 47-57.
- Felder, R. M. (1993). Reaching the second tier: Learning and teaching styles in college science education. Journal of College Science Teaching, 23(5), 286-290.
- Felder, R. M., & Henriques, E. R. (1995). Learning and teaching styles in foreign and second language education. Foreign Language Annals, 28(1), 21-31.
- Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles in engineering education. Journal of Engineering Education, 78(7), 674-681.
- Felder, R. M., & Soloman, B. A. (1991). Index of learning styles questionnaire. Retrieved from http://www4.ncsu. edu/unity/lockers/users/f/felder/public/ILSdir/ILS-a.htm
- Felder, R. M., & Spurlin, J. (2005). Applications, reliability and validity of the index of learning styles. International Journal of Engineering Education, 21(1), 103-112.
- Frank, M., Reich, N., & Humphreys, K. (2003). Respecting the human needs of students in the development of e-learning. Computers and Education, 40, 57-70.
- Garcia, P., Amandi, A., Schiaffino, S., & Campo, M. (2007). Evaluating Bayesian networks precision for detecting students learning styles. Computers and Education, 49, 794-808.
- Garcia, P., Schiaffino, S., & Amandi, A. (2008). An enhanced Bayesian model to detect students learning styles in Web-based courses. Journal of Computer Assisted Learning, 24, 305-315.
- Gonzalez, C., Burguillo, J. C., & Llamas, M. (2006). A qualitative comparison of techniques for student modeling in intelligent tutoring systems. In 36th ASEE/IEEE Frontiers in Education Conference (pp. 13-18). San Diego.
- Graf, S. (2007). Adaptivity in learning management systems focusing on learning styles (Doctoral dissertation, Vienna University of Technology-Faculty of Informatics). Retrieved from http://sgraf.athabascau.ca/publications/ PhDthesis_SabineGraf.pdf
- Graf, S., & Kinshuk. (2008). Analysing the behavior of students in learning management systems with respect to learning styles. Studies in Computational Intelligence, 93, 53-73.
- Hamalainen, W., & Vinni, M. (2006). Comparison of machine learning methods for intelligent tutoring systems. 8th International Conference on Intelligent Tutoring Systems, 4053, 525-534.
- Hambleton, R. K., & Patsula, L. (1999). Increasing the validity of adapted tests: Myths to be avoided and guidelines for improving test adaptation practices. Journal of Applied Testing Technology, 1, 1-30.
- Hamid, A. A. (2002). E-learning: Is it the e or the learning that matters? Internet and Higher Education, 4, 311-316.
- Heckerman, D., Horvitz, E., & Nathwani, B. (1989). Update on the pathfinder project. Proceedings of the 13th Symposium on Computer Applications in Medical Care (pp. 203-207). Washington: IEEE Computer Society Press.
- Horvitz, E., Breese, J., Heckerman, D., Hovel, D., & Rommelse, K. (1998). The Lumiere project: Bayesian user modeling for inferring the goals and needs of software users. Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (pp. 256-266). Wisconsin.
- Huang, C., Liu, M., Chu, S., & Cheng, C. (2007). An intelligent learning diagnosis system for Web-based thematic learning platform. Computers and Education, 48(4), 658-679.
- Jameson, A. (1996). Numerical uncertainty management in user and student modeling: An overview of systems and issues. User Modeling and User-Adapted Interaction, 5, 193-251.
- Jonassen, D. H. (1991). Objectivism versus constructivism: Do we need a new philosophical paradigm? Educational Technology Research and Development, 39(3), 5-14.
- Karagiorgi, Y., & Symeou, L. (2005). Translating constructivism into instructional design: Potential and limitations. Educational Technology and Society, 8(1), 17- 27.
- Katz, Y. J. (2002). Attitudes affecting college students preferences for distance learning. Journal of Computer Assisted Learning, 18, 2-9.
- Kennedy, G. (2002). Intellectual property issues in e-learning. Computer Law and Security Report, 18(2), 91- 98.
- Kotsiantis, S. B., Pierrakeas, C. J., & Pintelas, P. E. (2003). Preventing student dropout in distance learning using machine learning techniques. Proceedings of the 7th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (pp. 267-274). UK: University of Oxford.
- Kuljis, J., & Liu, F. (2005). A comparison of learning style theories on the suitability for e-learning. Proceedings of the Conference on Web Technologies, Applications and Services (pp. 191-197). Canada: ACTA Press.
- Lester, J. C., Stone, B. A., & Stelling, G. D. (1999). Lifelike pedagogical agents for mixed-initiative problem solving in constructivist learning environments. User Modeling and User-Adapted Interaction, 9, 1-44.
- Levy, Y. (2007). Comparing Dropouts and Persistence in e-Learning Courses, Computers & Education, 48(2): 185 204.
- Liegle, J. O., & Janicki, T. N. (2006). The effect of learning styles on the navigation needs of Web-based learners. Computers in Human Behavior, 22, 885-898.
- Litzinger, T. A., Lee, S. H., Wise, J. C., & Felder, R. M. (2005). A study of the reliability and validity of the Felder-Soloman Index of Learning Styles. Proceedings of the ASEEE Annual Conference and Exposition (pp. 1-13). Oregon.
- Litzinger, T. A., Lee, S. H., Wise, J. C., & Felder, R. M. (2007). A psychometric study of the index of learning styles. Journal of Engineering Education, 96(4), 309-319.
- Liu, C. (2006). Learning students learning patterns with neural computing. IEEE International Conference on Systems, Man and Cybernetics (pp. 2434-2439). Taipei.
- Martens, R. L., Gulikers, J., & Bastiaens, T. (2004). The impact of intrinsic motivation on e-learning in authentic computer tasks. Journal of Computer Assisted Learning, 20, 368-376.
- McMillan, J. H. (2004). Educational research. Boston: Pearson Education.
- Mertz, J. S. (1997). Using a simulated student for instructional design. International Journal of Artificial Intelligence in Education, 8, 116-141.
- Millan, E., Agosta, J. M., & Perez de la Cruz, J. L. (2001). Bayesian student modeling and the problem of parameter specification. British Journal of Educational Technology, 32(2), 171-181.
- Minaeli-Bigdoli, B., Kashy, D. A., Kortemeyer, G., & Punch, W. P. (2003). Predicting student performance: An application of data mining methods with an educational Web-based system. Proceedings of the 33rd ASEE/IEEE Frontiers in Education Conference (pp. 13-18). Colorado.
- Oppermann, R., Rashev, R., & Kinshuk (1997). Adaptability and adaptivity in learning systems. Proceedings on Knowledge Transfer, 2, 173-179.
- Özpolat, E., & Akar, G. B. (2009). Automatic detection of learning styles for an e-learning system. Computers and Education, 53, 355-367.
- Papanikolau, K. A., Grigoriadou, M., Magoulas, G. D., & Kornilakis, H. (2002). Towards new forms of knowledge communication: The adaptive dimension of a Web-based learning environment. Computers and Education, 39(4), 333-360.
- Parades, P., & Rodriguez, P. (2004). A mixed approach to modelling learning styles in adaptive educational hypermedia. Advanced Technology for Learning, 1(4), 210- 215.
- Parvez, S. M., & Blank, G. D. (2007). A pedagogical framework to integrate learning style into intelligent tutoring systems. Journal of Computing Sciences in Colleges, 22(3), 183-189.
- Pear, J. J., & Crone-Todd, D. E. (2002). A social constructivist approach to computer-mediated instruction. Computers and Education, 38(1-3), 221-231.
- Piaget, J. (1977). The development of thought: Equilibration of cognitive structures. New York: Viking Press.
- Popescu, E., Trigano, P., & Badica, C. (2007). Evaluation of a learning management system for adaptivity purposes. Proceedings of the International Multi-Conference on Computing in the Global Information Technology (ICCGI07) (pp. 9). Guadeloupe.
- Ragnemalm, E. L. (1996). Student diagnosis in practice; Bridging a gap. User Modeling and User-Adapted Interaction, 5(2), 93-116.
- Samancı, M. K. ve Keskin, M. Ö. (2006, Eylül). Felder ve Soloman Öğrenme Stili İndeksi: Türkçeye uyarlanması ve geçerlik güvenirlik çalışması. 7. Ulusal Fen Bilimleri ve Matematik Kongresinde sunulan bildiri, Gazi Üniversitesi, Ankara.
- Self, J. (1988). Bypassing the intractable problem of student modeling. In First International Conference on Intelligent Tutoring Systems (pp. 18-24). Montreal.
- Sharp, J. E. (2004). A resource for teaching a learningstyles/teamwork module with the Soloman-Felder Index of learning styles. IEEE Antennas and Propagation Magazine, 46(6), 138-143.
- Stash, N, Cristea, A., & De Bra, P. (2004). Authoring of learning styles in adaptive hypermedia: Problems and solutions. Proceedings of the 13th International Conference on World Wide Web, ACM (pp. 114-123). New York.
- Sun, L., Ousmanou, K., & Williams, S. (2004). Articulation of learners requirements for personalized instructional design in e-learning services. The 3rd International Conference on Web-based Learning, Hong Kong. Lecture Notes in Computer Science-Springer, 3413, 424-431.
- Triantafillou, E., Pomportsis, A., & Demetriadis, S. (2003). The design and the formative evaluation of an adaptive educational system based on cognitive styles. Computers and Education, 41(1), 87-103.
- Tsiriga, V., & Virvou, M. (2004). A framework for the initialization of student models in Web-based intelligent tutoring systems. User Modeling and User-Adapted Interaction, 14(4), 289-316.
- van Zwanenberg, N., Wilkinson, L. J., & Anderson, A. (2000). Felder and Silvermans Index of Learning Styles and Honey and Mumfords Learning Styles Questionnaire: How do they compare and do they predict academic performance? Educational Psychology, 20(3), 365-380.
- Vanlehn, K., & Niu, Z. (2001). Bayesian student modeling, user interfaces and feedback: A sensitivity analysis. International Journal of Artificial Intelligence in Education, 12, 154-184.
- Vegas, F. J. D. (1995). Sistema Experta Bayesiano para Ecocardiografi (Doctoral dissertation, National University of Distance Education, Madrid). Retrieved from http:// www.ia.uned.es/~fjdiez/tesis/tesis.zip
- von Davier, A. A., Holland, P. W., & Thayer, D. T. (2004). The Kernel method of test equating. New York: Springer- Verlag.
- Webb, G. I., Pazzani, M. J., & Billsus, D. (2001). Machine learning for user modeling. User Modeling and User- Adapted Interaction, 11, 19-29.
- Yudelson, M., Medvedeva, O. P., & Crowley, R. S. (2008). A multifactor approach to student model evaluation. User Modeling and User-Adapted Interaction, 18, 349-382.
- Zualkernan, I. A. (2007). Using Soloman-Felder Learning Style Index to evaluate pedagogical resources for introductory programming classes. 29th International IEEE Conference on Software Engineering (pp. 723-726). Minneapolis.
- Zywno, M. S. (2003). A contribution to validation of score meaning for Felder-Solomans Index of Learning Styles. Proceedings of the ASEE Annual Conference and Exposition, Session 2351, 67-83, Tennessee.
| APA | ASLAN B, ÖZTÜRK Ö, INCEOGLU M (2014). İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). , 1143 - 1168. |
| Chicago | ASLAN BURAK GALİP,ÖZTÜRK Özlem,INCEOGLU MUSTAFA MURAT İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). (2014): 1143 - 1168. |
| MLA | ASLAN BURAK GALİP,ÖZTÜRK Özlem,INCEOGLU MUSTAFA MURAT İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). , 2014, ss.1143 - 1168. |
| AMA | ASLAN B,ÖZTÜRK Ö,INCEOGLU M İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). . 2014; 1143 - 1168. |
| Vancouver | ASLAN B,ÖZTÜRK Ö,INCEOGLU M İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). . 2014; 1143 - 1168. |
| IEEE | ASLAN B,ÖZTÜRK Ö,INCEOGLU M "İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği)." , ss.1143 - 1168, 2014. |
| ISNAD | ASLAN, BURAK GALİP vd. "İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği)". (2014), 1143-1168. |
| APA | ASLAN B, ÖZTÜRK Ö, INCEOGLU M (2014). İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). Kuram ve Uygulamada Eğitim Bilimleri, 14(3), 1143 - 1168. |
| Chicago | ASLAN BURAK GALİP,ÖZTÜRK Özlem,INCEOGLU MUSTAFA MURAT İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). Kuram ve Uygulamada Eğitim Bilimleri 14, no.3 (2014): 1143 - 1168. |
| MLA | ASLAN BURAK GALİP,ÖZTÜRK Özlem,INCEOGLU MUSTAFA MURAT İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). Kuram ve Uygulamada Eğitim Bilimleri, vol.14, no.3, 2014, ss.1143 - 1168. |
| AMA | ASLAN B,ÖZTÜRK Ö,INCEOGLU M İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). Kuram ve Uygulamada Eğitim Bilimleri. 2014; 14(3): 1143 - 1168. |
| Vancouver | ASLAN B,ÖZTÜRK Ö,INCEOGLU M İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği). Kuram ve Uygulamada Eğitim Bilimleri. 2014; 14(3): 1143 - 1168. |
| IEEE | ASLAN B,ÖZTÜRK Ö,INCEOGLU M "İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği)." Kuram ve Uygulamada Eğitim Bilimleri, 14, ss.1143 - 1168, 2014. |
| ISNAD | ASLAN, BURAK GALİP vd. "İnternet üzerinden yabancı dil öğretiminde bayes öğrenci modellemesi yaklaşımının akademik başarıya etkisi (Üniversite İngilizce hazırlık örneği)". Kuram ve Uygulamada Eğitim Bilimleri 14/3 (2014), 1143-1168. |
