Metrika članka

  • citati u SCindeksu: 0
  • citati u CrossRef-u:[1]
  • citati u Google Scholaru:[=>]
  • posete u poslednjih 30 dana:6
  • preuzimanja u poslednjih 30 dana:6
članak: 1 od 1  
Back povratak na rezultate
International Journal of Cognitive Research in Science, Engineering and Education
2017, vol. 5, br. 2, str. 83-97
jezik rada: engleski
vrsta rada: izvorni naučni članak
objavljeno: 08/01/2018
doi: 10.5937/ijcrsee1702083K
Creative Commons License 4.0
Learning styles based adaptive intelligent tutoring systems: Document analysis of articles published between 2001. and 2016.
(naslov ne postoji na srpskom)
University of Petroleum and Energy Studies, School of Computer Science and Engineering, Dehradun, Uttarakhand, India



(ne postoji na srpskom)
Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learn- ing styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS) while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and citations were discussed.

Ključne reči

learning styles; adaptive intelligent tutoring system; adaptivity; learner characteristics; cognitive skills


Adetunji, A., Ademola, A. (2014) A Proposed Architectural Model for an Automatic Adaptive E-Learning System Based on Users Learning Style. International Journal of Advanced Computer Science and Applications, 5(4):
Akkoyunlu, B., Yilmaz-Soylu, M. (2008) A study of student's perceptions in a blended learning environment based on different learning styles. Educational Technology & Society, 11(1), 183-193,
Alepis, E., Virvou, M., Kabassi, K. (2008) Mobile education: Towards affective bi-modal interaction for adaptivity. u: 2008 Third International Conference on Digital Information Management, Institute of Electrical and Electronics Engineers (IEEE), str. 51-56
Aleven, V., Mclaren, B., Roll, I., Koedinger, K. (2006) Toward meta-cognitive tutoring: A model of help seeking with a Cognitive Tutor. International Journal of Artificial Intelligence in Education, 16(2), 101-128.
Alfonseca, E., Carro, R.M., Martín, E., Ortigosa, A., Paredes, P. (2006) The impact of learning styles on student grouping for collaborative learning: a case study. User Modeling and User-Adapted Interaction, 16(3-4): 377-401
Alkhuraiji, S., Cheetham, B., Bamasak, O. (2011) Dynamic Adaptive Mechanism in Learning Management System Based on Learning Styles. u: 2011 IEEE 11th International Conference on Advanced Learning Technologies, Institute of Electrical and Electronics Engineers (IEEE), str. 215-217
Anthony, P., Joseph, N.E., Ligadu, C. (2013) Learning How to Program in C Using Adaptive Hypermedia System. International Journal of Information and Education Technology, str. 151-155
Ary, D., Jacobs, L.C., Irvine, C.K.S., Walker, D. (2013) Introduction to research in education. Cengage Learning, https//
Aslan, B.G., Öztürk, Ö., İnceoğlu, M.M. (2014) İnternet Üzerinden Yabancı Dil Öğretiminde Bayes Öğrenci Modellemesi Yaklaşımının Akademik Başarıya Etkisi (Üniversite İngilizce Hazırlık Örneği). Educational Sciences: Theory & Practice, 14(3), 1160-1168
Bachari, E.E., Abelwahed, E.H., el Adnani, M. (2011) E-Learning personalization based on Dynamic learners' preference. International Journal of Computer Science and Information Technology, 3(3): 200-216
Balasubramanian, V., Margret, A.S. (2016) Learning style detection based on cognitive skills to support adaptive learning environment - A reinforcement approach. Ain Shams Engineering Journal
Baldiris, S., Santos, O.C., Barrera, C., Boticario, J., Velez, J., Fabregat, R. (2008) Integration of educational specifications and standards to support adaptive learning scenarios in ADAPTA-Plan. IJCSA, 5(1), 88-107.
Beal, C., Lee, H. (2005) Creating a pedagogical model that uses student self-reports of motivation and mood to adapt ITS. u: Workshop on Motivation and Affect in Educational Software, in conjunction with the 12th International Conference on Artificial Intelligence in Education, July, Vol. 574).
Botsios, S., Georgiou, D., Safouris, N. (2008) Con- tributions to adaptive educational hypermedia systems via on-line learning style estimation. Journal of Educational Technology & Society, 11(2):
Bozkurt, O., Aydoğdu, M. (2009) A comparative analysis of the effect of dunn and dunn learning styles model and traditional teaching method on 6th grade students' achievement levels and attitudes in science education lesson. Elementary Education Online, 8(3): 741-754
Cabada, R., Estrada, M., Sanchez, L., Sandoval, G., Velazquez, J., Barrientos, J. (2009) Modeling student's learning styles in web 2.O learning systems. World Journal on Educational Technology, 1(2), 75-88.
Cabada, R.Z., Barrón, E.M.L., Reyes, G.C.A. (2011) EDUCA: A web 2.0 authoring tool for developing adaptive and intelligent tutoring systems using a Kohonen network. Expert Systems with Applications, 38(8): 9522-9529
Carmona, C., Castillo, G., Millán, E. (2008) Designing a Dynamic Bayesian Network for Modeling Students' Learning Styles. u: 2008 Eighth IEEE International Conference on Advanced Learning Technologies, Institute of Electrical and Electronics Engineers (IEEE), str. 346-350
Cha, H.J., Kim, Y.S., Park, S.H., Yoon, T.B., Jung, Y.M., Lee, J. (2006) Learning Styles Diagnosis Based on User Interface Behaviors for the Customization of Learning Interfaces in an Intelligent Tutoring System. Berlin, Heidelberg: Springer Nature, str. 513-524
Chang, Y., Kao, W., Chu, C., Chiu, C. (2009) A learning style classification mechanism for e-learning. Computers & Education, 53(2): 273-285
Chrysafiadi, K., Virvou, M. (2012) Evaluating the integration of fuzzy logic into the student model of a web-based learning environment. Expert Systems with Applications, 39(18): 13127-13134
Conati, C., Gertner, A., Vanlehn, K. (2002) Using Bayesian networks to manage uncertainty in student modeling. User Modeling and User-Adapted Interaction, 12(4): 371-417
Dagger, D., Wade, V., Conlan, O. (2002) Towards a standards-based approach to e-learning personalization using reusable learning objects. u: E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Association for the Advancement of Computing in Education (AACE), pp. 210-217).
de Moura, F.F., Franco, L.M., de Melo, S.L., Fernandes, M.A. (2013) Development of Learning Styles and Multiple Intelligences through Particle Swarm Optimization. u: 2013 IEEE International Conference on Systems, Man, and Cybernetics, Institute of Electrical and Electronics Engineers (IEEE), str. 835-840
DelCorso, D., Ovcin, E., Morrone, G. (2005) A Teacher Friendly Environment to Foster Learner-Centered Customization in the Development of Interactive Educational Packages. IEEE Transactions on Education, 48(4): 574-579
Demirbaş, O., Demirkan, H. (2003) Focus on architectural design process through learning styles. Design Studies, 24(5): 437-456
Dorça, F.A., Lima, L.V., Fernandes, M.A., Lopes, C.R. (2013) Automatic student modeling in adaptive educational systems through probabilistic learning style combinations: a qualitative comparison between two innovative stochastic approaches. Journal of the Brazilian Computer Society, 19(1): 43-58
Dwivedi, P., Bharadwaj, K.K. (2013) Effective trust- aware e-learning recommender system based on learning styles and knowledge levels. Journal of Educational Technology & Society, 16(4): 201;
Essalmi, F., Ayed, L.J.B., Jemni, M., Kinshuk,, Graf, S. (2010) A fully personalization strategy of E-learning scenarios. Computers in Human Behavior, 26(4): 581-591
Fazlollahtabar, H., Mahdavi, I. (2009) User/tutor optimal learning path in e-learning using comprehensive neuro-fuzzy approach. Educational Research Review, 4(2): 142-155
Felder, R.M., Silverman, L.K. (1988) Learning and teaching styles in engineering education. Engineering education, 78(7), 674-681. http://
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.
Feldman, J., Monteserin, A., Amandi, A. (2014) Detecting students' perception style by using games. Computers & Education, 71: 14-22
Filippidis, S.K., Tsoukalas, I.A. (2009) On the use of adaptive instructional images based on the sequential-global dimension of the Felder-Silverman learning style theory. Interactive Learning Environments, 17(2): 135-150
Franzoni, A.L., Assar, S., Defude, B., Rojas, J. (2008) Student Learning Styles Adaptation Method Based on Teaching Strategies and Electronic Media. u: 2008 Eighth IEEE International Conference on Advanced Learning Technologies, Institute of Electrical and Electronics Engineers (IEEE), str. 778-782
García, 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(4): 305-315
García, P., Amandi, A., Schiaffino, S., Campo, M. (2007) Evaluating Bayesian networks' precision for detecting students' learning styles. Computers & Education, 49(3): 794-808
Germanakos, P., Tsianos, N., Lekkas, Z., Mourlas, C., Samaras, G. (2008) Capturing essential intrinsic user behaviour values for the design of comprehensive web-based personalized environments. Computers in Human Behavior, 24(4): 1434-1451
Graf, S., Liu, T.-C., Kinshuk (2010) Analysis of learners' navigational behaviour and their learning styles in an online course. Journal of Computer Assisted Learning, 26(2): 116-131
Graf, S., Kinshuk,, Liu, T. (2008) Identifying Learning Styles in Learning Management Systems by Using Indications from Students' Behaviour. u: 2008 Eighth IEEE International Conference on Advanced Learning Technologies, Institute of Electrical and Electronics Engineers (IEEE), str. 482-486
Graf, S., Liu, T., Kinshuk,, Chen, N., Yang, S.J.H. (2009) Learning styles and cognitive traits - Their relationship and its benefits in web-based educational systems. Computers in Human Behavior, 25(6): 1280-1289
Hong, H. (2004) Adaptation to student learning styles in web based educational systems. u: EdMedia: World Conference on Educational Media and Technology, Association for the Advancement of Computing in Education (AACE), pp. 491-496,
Huang, E.Y., Lin, S.W., Huang, T.K. (2012) What type of learning style leads to online participation in the mixed-mode e-learning environment? A study of software usage instruction. Computers & Education, 58(1): 338-349
Hwang, G.J., Sung, H.Y., Hung, C.M., Huang, I. (2013) A learning style perspective to investigate the necessity of developing adaptive learning systems. Educational Technology & Society, 16(2), 188-197.
Hwang, G., Tsai, C. (2011) Research trends in mobile and ubiquitous learning: a review of publications in selected journals from 2001 to 2010. British Journal of Educational Technology, 42(4): E65-E70
James, W.B., Blank, W.E. (1993) Review and critique of available learning-style instruments for adults. New Directions for Adult and Continuing Education, 1993(59): 47-57
Jonassen, D.H., Grabowski, B.L. (2012) Handbook of individual differences, learning, and instruction. Routledge,
Jovanovic, J., Gašević, D., Devedžić, V. (2009) TANGRAM for Personalized Learning Using the Semantic Web Technologies. Journal of Emerging Technologies in Web Intelligence, 1(1):
Kelly, D., Tangney, B. (2005) First aid for you: Getting to know your learning style using machine learning. u: Advanced Learning Technologies, 2005: ICALT 2005, Fifth IEEE International Conference on, IEEE, July, (pp. 1-3). DOI: 10.1109/ICALT.2005.1
Kelly, D. (2008) Adaptive versus learner control in a multiple intelligence learning environment. Journal of Educational Multimedia and Hypermedia, 17(3), 307.
Ketamo, H. (2003) An adaptive geometry game for handheld devices. Educational Technology & Society, 6(1): 83-95;
Kim, J., Lee, A., Ryu, H. (2013) Personality and its effects on learning performance: Design guidelines for an adaptive e-learning system based on a user model. International Journal of Industrial Ergonomics, 43(5): 450-461
Klašnja-Milićević, A., Vesin, B., Ivanović, M., Budimac, Z. (2011) E-Learning personalization based on hybrid recommendation strategy and learning style identification. Computers & Education, 56(3): 885-899
Koutsojannis, C., Prentzas, J., Hatzilygeroudis, I. (2001) A web-based intelligent tutoring system teaching nursing students fundamental aspects of biomedical technology. u: 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Institute of Electrical and Electronics Engineers (IEEE), str. 4024-4027
Kuljis, J., Liu, F. (2005) A comparison of learning style theories on the suitability for e-learning. Web Technologies, Applications, and Services, 191-197,
Kurilovas, E., Kubilinskiene, S., Dagiene, V. (2014) Web 3.0 - Based personalisation of learning objects in virtual learning environments. Computers in Human Behavior, 30: 654-662
Latham, A., Crockett, K., McLean, D., Edmonds, B. (2012) A conversational intelligent tutoring system to automatically predict learning styles. Computers & Education, 59(1): 95-109
Latham, A., Crockett, K., McLean, D. (2014) An adaptation algorithm for an intelligent natural language tutoring system. Computers & Education, 71: 97-110
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(5): 885-898
Limongelli, C., Sciarrone, F., Temperini, M., Vaste, G. (2011) The Lecomps5 framework for personalized web-based learning: A teacher's satisfaction perspective. Computers in Human Behavior, 27(4): 1310-1320
Lin, C.F., Yeh, Y., Hung, Y.H., Chang, R.I. (2013) Data mining for providing a personalized learning path in creativity: An application of decision trees. Computers & Education, 68: 199-210
Litzinger, T.A., Wise, J.C., Lee, S.H. (2013) Self-directed Learning Readiness Among Engineering Undergraduate Students. Journal of Engineering Education, 94(2): 215-221
Lu, H., Jia, L., Gong, S.H., Clark, B. (2007) The re- lationship of Kolb learning styles, online learn- ing behaviors and learning outcomes. Journal of Educational Technology & Society, 10(4): http://
Mahnane, L., Laskri, M.T., Trigano, P. (2013) A model of adaptive e-learning hypermedia system based on thinking and learning styles. International Journal of Multimedia and Ubiquitous Engineering, 8(3), 339-350,
Manochehr, N.N. (2006) The influence of learning styles on learners in e-learning environments: An empirical study. Computers in Higher Education Economics Review, 18(1): 10-14;
McQuiggan, S.W., Mott, B.W., Lester, J.C. (2008) Modeling self-efficacy in intelligent tutoring systems: An inductive approach. User Modeling and User-Adapted Interaction, 18(1-2): 81-123
Melis, E., Siekmann, J. (2004) ActiveMath: An Intelligent Tutoring System for Mathematics. Berlin, Heidelberg: Springer Nature, str. 91-101
Mitrovic, A., Martin, B., Mayo, M. (2002) Using evaluation to shape ITS design: Results and experiences with SQL-Tutor. User Modeling and User-Adapted Interaction, 12(2/3): 243-279
Mitrović, A., Koedinger, K., Martin, B. (2003) A comparative analysis of cognitive tutoring and constraint-based modeling. User Modeling, 147-147,
Mödritscher, F. (2008) Adaptive e-learning environments: Theory, practice, and experience. VDM Müller
Mustafa, Y.E.A., Sharif, S.M. (2011) An approach to adaptive e-learning hypermedia system based on learning styles (AEHS-LS): Implementation and evaluation. International Journal of Library and Information Science, 3(1), 15-28,
Özpolat, E., Akar, G.B. (2009) Automatic detection of learning styles for an e-learning system. Computers & Education, 53(2): 355-367
Özyurt, Ö., Özyurt, H., Baki, A., Güven, B. (2013) Integration into mathematics classrooms of an adaptive and intelligent individualized e-learning environment: Implementation and evaluation of UZWEBMAT. Computers in Human Behavior, 29(3): 726-738
Özyurt, Ö., Özyurt, H. (2015) Learning style based individualized adaptive e-learning environments: Content analysis of the articles published from 2005 to 2014. Computers in Human Behavior, 52: 349-358
Papanikolaou, K.A., Grigoriadou, M., Kornilakis, H., Magoulas, G.D. (2003) Personalizing the Interaction in a Web-based Educational Hyper- media System: the case of INSPIRE. User Modeling and User-Adapted Interaction, 13(3): 213-267
Park, O.C., Lee, J. (2003) Adaptive instructional systems. Educational Technology Research and Development, 25, 651-684;
Ray, R.D., Belden, N. (2007) Teaching College Level Content and Reading Comprehension Skills Simultaneously via an Artificially Intelligent Adaptive Computerized Instructional System. Psychological Record, 57(2): 201-218
Read, T., Barros, B., Bárcena, E., Pancorbo, J. (2006) Coalescing individual and collaborative learning to model user linguistic competences. User Modeling and User-Adapted Interaction, 16(3-4): 349-376
Reategui, E., Boff, E., Campbell, J.A. (2008) Personalization in an interactive learning environment through a virtual character. Computers & Education, 51(2): 530-544
Romero, C., Ventura, S., Gibaja, E.L., Hervás, C., Romero, F. (2006) Web-based adaptive training simulator system for cardiac life support. Artificial Intelligence in Medicine, 38(1): 67-78
Sancho, P., Martínez, I., Fernández-Manjón, B. (2005) Semantic Web Technologies Applied to e-learning Personalization in< e-aula>. Journal of Universal Computer Science, 11(9): 1470-1481; 1470;
Sanders, D.A., Bergasa-Suso, J. (2010) Inferring Learning Style From the Way Students Interact With a Computer User Interface and the WWW. IEEE Transactions on Education, 53(4): 613-620
Sangineto, E., Capuano, N., Gaeta, M., Micarelli, A. (2008) Adaptive course generation through learning styles representation. Universal Access in the Information Society, 7(1-2): 1-23
Schiaffino, S., Garcia, P., Amandi, A. (2008) eTeacher: Providing personalized assistance to e-learning students. Computers & Education, 51(4): 1744-1754
Scott, E., Rodríguez, G., Soria, Á., Campo, M. (2014) Are learning styles useful indicators to discover how students use Scrum for the first time?. Computers in Human Behavior, 36: 56-64
Shih, M., Feng, J., Tsai, C. (2008) Research and trends in the field of e-learning from 2001 to 2005: A content analysis of cognitive studies in selected journals. Computers & Education, 51(2): 955-967
Shute, V., Towle, B. (2003) Adaptive E-Learning. Educational Psychologist, 38(2): 105-114
Stash, N. (2007) Incorporating cognitive/learning styles in a general-purpose adaptive hypermedia system. ACM SIGWEB Newsletter, 2007(Winter): 3-es
Sun, S., Joy, M., Griffiths, N. (2007) The use of learning objects and learning styles in a multi-agent education system. Journal of Interactive Learning Research, 18(3): 381;
Tseng, J.C.R., Chu, H., Hwang, G., Tsai, C. (2008) Development of an adaptive learning system with two sources of personalization information. Computers & Education, 51(2): 776-786
van Zwanenberg, N., Wilkinson, L. J., Anderson, A. (2000) Felder and Silverman's Index of Learning Styles and Honey and Mumford's Learning Styles Questionnaire: How do they compare and do they predict academic performance?. Educational Psychology, 20(3): 365-380
Vassileva, D., Bontchev, B. (2006) Self-adaptive hypermedia navigation based on learner model characters.
Vermunt, J.D. (2011) The regulation of constructive learning processes. British Journal of Educational Psychology, 68(2): 149-171
Villaverde, J. E., Godoy, D., Amandi, A. (2006) Learning styles' recognition in e-learning environments with feed-forward neural networks. Journal of Computer Assisted Learning, 22(3): 197-206
Wang, T., Wang, K., Huang, Y. (2008) Using a style-based ant colony system for adaptive learning. Expert Systems with Applications, 34(4): 2449-2464
Wen, D., Graf, S., Lan, C.H., Anderson, T., Dickson, K. (2007) Supporting web-based learning through adaptive assessment. FormaMente Journal, 2(1-2), 45-79,
Xu, D., Wang, H., Su, K. (2002) Intelligent student profiling with fuzzy models. u: System Sciences 2002: HICSS, 35th Annual Hawaii International Conference, Proceedings, IEEE, January, pp. 8,
Xu, D., Wang, H. (2006) Intelligent agent supported personalization for virtual learning environments. Decision Support Systems, 42(2): 825-843
Yang, T.C., Hwang, G.J., Yang, S.J.H. (2013) Development of an adaptive learning system with multiple perspectives based on students' learning styles and cognitive styles. Journal of Educational Technology & Society, 16(4): 185;
Zakrzewska, D. (2010) Building Group Recommendations in E-Learning Systems. Berlin, Heidelberg: Springer Nature, str. 391-400