Abstract
Adaptive learning technologies provide an environment that intelligently adjusts to a learner’s needs by presenting suitable information, instructional materials, feedback and recommendations based on one’s unique individual characteristics and situation. This chapter first focuses on the concept of adaptivity based on four types of learner differences that can be used by adaptive technologies: learning styles, cognitive abilities, affective states and the current learning context/situation. In order to provide adaptivity, the characteristics of learners need to be known first. Therefore, this chapter discusses methods for identifying learners’ individual differences as well as how the information about these individual differences can be used to provide learners with adaptive learning experiences. Furthermore, the chapter demonstrates how adaptivity can be provided in different settings, focusing on both desktop-based learning and mobile/pervasive/ubiquitous learning. Finally, open issues in adaptive technologies are discussed and future research directions are identified.
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References
Bajraktarevic, N., Hall, W., & Fullick, P. (2003). Incorporating learning styles in hypermedia environment: Empirical evaluation. In P. de Bra, H. C. Davis, J. Kay, & M. Schraefel (Eds.), Proceedings of the Workshop on Adaptive Hypermedia and Adaptive Web-Based Systems (pp. 41–52). Nottingham: Eindhoven University.
Blackboard. (2011). Retrieved 30 March, 2011, from http://www.blackboard.com.
*Brusilovsky, P. (1996). Methods and techniques of adaptive hypermedia. User Modeling and User-Adapted Interaction, 6(2–3), 87–129.
*Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-Adapted Interaction, 11, 87–110.
Brusilovsky, P., Eklund, J., & Schwarz, E. (1998). Web-based education for all: A tool for developing adaptive courseware. Computer Networks and ISDN Systems, 30(1–7), 291–300.
Cha, H. J., Kim, Y. S., Park, S. H., Yoon, T. B., Jung, Y. M., & Lee, J.-H. (2006). Learning style diagnosis based on user interface behavior for the customization of learning interfaces in an intelligent tutoring system. In M. Ikeda, K. D. Ashley, & T.-W. Chan (Eds.), Proceedings of the 8th International Conference on Intelligent Tutoring Systems (Lecture notes in computer science, Vol. 4053, pp. 513–524). Berlin: Springer.
Chang, A., & Chang, M. (2006). Creating an adaptive mobile navigation learning path for elementary school students’ remedy education. Proceedings of the International Conference on Interactive Computer Aided Learning. Villach, Austria.
Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Should we be using learning styles? What research has to say to practice. London: Learning and Skills Research Centre/University of Newcastle upon Tyne.
D’Mello, S., Craig, S., Fike, K., & Graesser, A. (2009). Responding to learners’ cognitive-affective states with supportive and shakeup dialogues. Proceedings of the International Conference on Human-Computer Interaction. Lecture notes in computer science (Vol. 5612, pp. 595–604). Berlin: Springer
Dagger, D., Wade, V., & Conlan, O. (2005). Personalisation for all: Making adaptive course composition easy. Educational Technology & Society, 8(3), 9–25.
de Bra, P., & Calvi, L. (1998). AHA! An open adaptive hypermedia architecture. The New Review of Hypermedia and Multimedia, 4(1), 115–139.
de Bra, P., Smits, D., van der Sluijs, K., Cristea, A., & Hendrix, M. (2010). GRAPPLE: Personalization and adaptation in learning management systems. Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications (ED-Media) (pp. 3029–3038). Chesapeake, VA: AACE.
Deary, I. J., Whiteman, M. C., Starr, J. M., Whalley, L. J., & Fox, H. C. (2004). The impact of childhood intelligence on later life: Following up the Scottish mental surveys of 1932 and 1947. Journal of Personality and Social Psychology, 86(1), 130–147.
Dey, A. K. (2001). Understanding and using context. Personal and Ubiquitous Computing, 5(1), 4–7.
El-Bishouty, M. M., Ogata, H., Ayala, G., & Yano, Y. (2010). Context-aware support for self-directed ubiquitous-learning. International Journal of Mobile Learning and Organisation, 4(3), 317–331.
El-Bishouty, M. M., Ogata, H., & Yano, Y. (2007). PERKAM: Personalized knowledge awareness map for computer supported ubiquitous learning. Educational Technology & Society, 10(3), 122–134.
Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles in engineering education. Engineering Education, 78(7), 674–681.
García, P., Amandi, A., Schiaffino, S., & Campo, M. (2007). Evaluating Bayesian networks’ precision for detecting students’ learning styles. Computers & Education, 49(3), 794–808.
Graf, S. (2007). Adaptivity in learning management systems focussing on learning styles. PhD thesis, Vienna University of Technology.
Graf, S., & Kinshuk. (2007). Providing adaptive courses in learning management systems with respect to learning styles. In G. Richards (Ed.), Proceedings of the World Conference on e-Learning in Corporate, Government, Healthcare, and Higher Education (e-Learn 2007) (pp. 2576–2583). Chesapeake, VA: AACE Press.
Graf, S., & Kinshuk. (2008). Adaptivity and personalization in ubiquitous learning systems. In A. Holzinger (Ed.), Proceedings of the Symposium on Usability and Human Computer Interaction for Education and Work (USAB 2008) (pp. 331–338). Berlin: Springer.
Graf, S., Kinshuk, & Ives, C. (2010). A flexible mechanism for providing adaptivity based on learning styles in learning management systems. Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT 2010) (pp. 30–34). Sousse, Tunisia: IEEE Computer Society.
*Graf, S., Kinshuk, & Liu, T. -C. (2009). Supporting teachers in identifying students’ learning styles in learning management systems: An automatic student modelling approach. Educational Technology & Society, 12(4), 3–14.
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., Liu, T. -C., Kinshuk, Chen, N. -S., & 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.
Graf, S., & Kinshuk. (2013). Dynamic student modelling of learning styles for advanced adaptivity in learning management systems. International Journal of Information Systems and Social Change, 4(1), 85–100.
Graf, S., Yang, G., Liu, T.-C., & Kinshuk. (2009). Automatic, global and dynamic student modeling in a ubiquitous learning environment. International Journal on Knowledge Management and E-Learning, 1(1), 18–35.
Greer, J., McCalla, G., Cooke, J., Collins, J., Kumar, V., Bishop, A., et al. (1998). The Intelligent Helpdesk: Supporting peer-help in a university course. Proceedings of the International Conference on Intelligent Tutoring Systems. Lecture notes in computer science (Vol. 1452, pp. 494–503). Berlin: Springer.
Honey, P., & Mumford, A. (1992). The manual of learning styles (3rd ed.). Maidenhead: Peter Honey.
*Hwang, G. -J., Tsai, C. -C., & Yang, S. J. H. (2008). Criteria, strategies and research issues of context-aware ubiquitous learning. Educational Technology & Society, 11(2), 81–91.
Hwang, G.-J., Yang, T.-C., Tsai, C.-C., & Yang, S. J. H. (2009). A context-aware ubiquitous learning environment for conducting complex science experiments. Computers & Education, 53(2), 402–413.
Jia, B., Zhong, S., Zheng, T., & Liu, Z. (2010). The study and design of adaptive learning system based on fuzzy set theory. In: Transactions on edutainment IV. Lecture notes in computer science (Vol. 6250, pp. 1–11). Berlin: Springer.
*Jonassen, D. H., & Grabowski, B. L. (1993). Handbook of individual differences, learning, and instruction, Hillsdale, NJ: Lawrence Erlbaum Associates.
Karampiperis, P., & Sampson, D. G. (2005). Adaptive learning resources sequencing in educational hypermedia systems. Educational Technology & Society, 8(4), 128–147.
Kashihara, A., Kinshuk, Oppermann, R., Rashev, R., & Simm, H. (2000). A cognitive load reduction approach to exploratory learning and its application to an interactive simulation-based learning system. Journal of Educational Multimedia and Hypermedia, 9(3), 253–276.
Khan, F. A., Graf, S., Weippl, E. R., & Tjoa, A. M. (2010). Identifying and incorporating affective states and learning styles in web-based learning management systems. International Journal of Interaction Design & Architectures, 9–10, 85–103.
Kinshuk, & Lin, T. (2003). User exploration based adaptation in adaptive learning systems. International Journal of Information Systems in Education, 1(1), 22–31.
*Kinshuk, & Lin, T. (2004). Cognitive profiling towards formal adaptive technologies in web-based learning communities. International Journal of WWW-based Communities, 1(1), 103–108.
Lin, T., & Kinshuk (2004). Dichotomic node network and cognitive trait model. Proceedings of IEEE International Conference on Advanced Learning Technologies (pp. 702–704). Los Alamitos, CA: IEEE Computer Science.
Lu, H., Jia, L., Gong, S.-H., & Clark, B. (2007). The relationship of kolb learning styles, online learning behaviors and learning outcomes. Journal of Educational Technology & Society, 10(4), 187–196.
Martín, S., Sancristobal, E., Gil, R., Castro, M., & Peire, J. (2008). Mobility through location-based services at university. International Journal of Interactive Mobile Technologies (iJIM), 2(3), 34–40.
Moodle. (2011). Retrieved 30 March, 2011, from http://www.moodle.org.
Ogata, H., Akamatsu, R., Mitsuhara, H., Yano, Y., Matsuura, K., Kanenishi, K., et al. (2004). TANGO: Supporting vocabulary learning with RFID tags. Electronic proceedings of International Workshop Series on RFID. Tokyo.
Özpolat, E., & Akar, G. B. (2009). Automatic detection of learning styles for an e-learning system. Computers & Education, 53(2), 355–367.
Paredes, P., & Rodríguez, P. (2004). A mixed approach to modelling learning styles in adaptive educational hypermedia. Advanced Technology for Learning, 1(4), 210–215.
Popescu, E. (2010). Adaptation provisioning with respect to learning styles in a web-based educational system: An experimental study. Journal of Computer Assisted Learning, 26(4), 243–257.
Sakai. (2011). Retrieved 30 March, 2011, from http://www.sakaiproject.org/portal.
Spada, D., Sánchez-Montañés, M., Paredes, P., & Carro, R. M. (2008). Towards inferring sequential-global dimension of learning styles from mouse movement patterns. Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems. Lecture notes in computer science (Vol. 5149, pp. 337–340). Berlin: Springer.
Tseng, J. C. R., Chu, H.-C., Hwang, G.-J., & Tsai, C.-C. (2008). Development of an adaptive learning system with two sources of personalization information. Computers & Education, 51(2), 776–786.
*Woolf, B. P., Burleson, W., Arroyo, I., Dragon, T., Cooper, D., & Picard, R. (2009). Affect-aware tutors: Recognising and responding to student affect. International Journal of Learning Technology, 4(3/4), 129–164.
Woolf, B. P., Shute, V., VanLehn, K., Burleson, W., King, J. L., Suthers, D., et al. (2010). A roadmap for education technology. Accessed June 24, 2012, from http://telearn.archives-ouvertes.fr/docs/00/58/82/91/PDF/groe_roadmap_for_education_technology_final_report_003036v1_.pdf.
Yang, Y. J., & Wu, C. (2009). An attribute-based ant colony system for adaptive learning object recommendation. Expert Systems with Applications, 26(2), 3034–3047.
Yin, C., Ogata, H., & Yano, Y. (2004). JAPELAS: Supporting Japanese polite expressions learning using PDA(s) towards ubiquitous learning. Journal of Information Systems Education, 3(1), 33–39.
Acknowledgements
The authors also acknowledge the support of NSERC, iCORE, Xerox, and the research-related gift funding by Mr. A. Markin.
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Graf, S., Kinshuk (2014). Adaptive Technologies. In: Spector, J., Merrill, M., Elen, J., Bishop, M. (eds) Handbook of Research on Educational Communications and Technology. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3185-5_62
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DOI: https://doi.org/10.1007/978-1-4614-3185-5_62
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