Perspectives on the Design and Evaluation of Adaptive Web Based Learning Environments

Perspectives on the Design and Evaluation of Adaptive Web Based Learning Environments

Adaptive Web-Based Learning Environments (A-WBLEs) provide mechanisms to individualize instruction (e.g., content, interface, strategies, and assessment) for learners based on their individual differences. In this paper, various adaptive methods influencing the design of AWBLEs are explained and how these methods aim to address individual differences is discussed. Empirical evaluations of adaptive systems are synthesized and four levels for categorizing AWBLEs are created to provide a guideline for future design and development of A-WBLEs .

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  • Allen, I. E. & Seman, J. (2004). Entering the mainstream: The quality and extend of online education in the United States, 2003 and 2004. Nedham, MA: The Sloan Consortium.
  • Allen, I. E. & Seman, J. (2008). Online notion: Five years of growth in online learning. Nedham, MA: The Sloan Consortium.
  • Aroyo, L., De Bra, P., Houben, G., & Vdovjak, R. (2004). Embedding information retrieval in adaptive hypermedia: IR meets AHA New Review of Hypermedia and Multimedia, 10(1), 53-76.
  • Azevedo, R., Cromley, J. G., & Seibert, D. (2004). Does adaptive scaffolding facilitate students' ability to regulate their learning with hypermedia? Contemporary Educational Psychology, 29(3), 344-370.
  • Azevedo, R., Moos, D. C., Greene, J. A., Winters, F. A., & Cromley, J. G. (2008). Why is externally-facilitated regulated learning more effective than self-regulated learning with hypermedia? Educational Technology Research and Development, 56(1), 45-72.
  • Berge, Z. L. (2002). Active, interactive, and reflective eLearning. Quarterly Review of Distance Education, 3(2), 181-190.
  • Bajraktarevic, N., Hall, W., & Fullick, P. (2003). Incorporating learning styles in hypermedia environment: Empirical evaluation. Paper presented at the Adaptive Hypermedia and Adaptive Web-Based Systems Workshop, Budapest, Hungary.
  • Brusilovsky, P. (1998). Adaptive educational systems on the World-Wide-Web: A Review of available technologies. Paper presented at the International Conference in Intelligent Tutoring Systems, San Antonio, TX.
  • Brusilovsky, P. (1999). Adaptive and intelligent technologies for Web-based education. Künstliche Intelligenz, 4, 19-25.
  • Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-Adapted Interaction, 11(1/2), 87-110.
  • Brusilovsky, P. (2003). Adaptive navigation support in educational hypermedia: The role of student knowledge level and the case for meta-adaptation. British Journal of Educational Technology, 34(4), 487-497.
  • Brusilovsky, P., Sosnovsky, S., & Shcherbinina, O. (2004). QuizGuide: Increasing the educational value of individualized self-assessment quizzes with adaptive navigation support. Proceeding of the World Conference on E-Learning in Corp., Govt., Health., & Higher Ed., 2004(1), 1806-1813.
  • Chen, S. Y. & Paul, R. J. (2003). Editorial: Individual differences in web-based instruction-an overview. British Journal of Educational Technology, 34(4), 385-392.
  • Dabbagh, N., & Bannan-Ritland, B. (2005). Online learning: Concept, strategies, and applications. Upper Saddle River, NJ: Pearson Education.
  • Danielson, R. L. (1997, June). Work in progress: Learning styles, media preferences, and adaptive education. Paper presented at the Adaptive Systems and User Modeling on the World Wide Web Workshop, Chia Laguna, Sardinia.
  • De Bra, P. (2000). Pros and cons of adaptive hypermedia in Web-based education. CyberPsychology and Behavior, 3(1), 71-77.
  • De Bra, P., Brusilovsky, P., & Houben, G. (1999). Adaptive hypermedia: From system to framework. ACM Computing Survey, 31(4).
  • Dutton, J., Dutton, M., & Perry, J. (2002), How Do Online Students Differ From Lecture Students? Journal of Asynchronous Learning Networks, 6(1).
  • Far, B. H. & Hashimoto, A. H. (2000). A Computational model for learner's motivation states in individualized tutoring system. Paper presented at the International Conference on Computer Assisted Instruction, Taipei, Taiwan.
  • Ford, N. & Chen, S. Y. (2000). Individual differences, hypermedia navigation, and learning: An empirical study. Journal of Educational Multimedia and Hypermedia, 9(4), 281-311.
  • Ford, N. & Chen, S. Y. (2001). Matching/mismatching revisited: An empirical study of learning and teaching styles. British Journal of Educational Technology, 32(1), 5-22.
  • Gauss, B. & Urbas, L. (2003). Individual differences in navigation between sharable content objects-an evaluation study of a learning module prototype. British Journal of Educational Technology, 34(4), 499-509.
  • Gouli, E., Gogoulou, A., Papanikolaou, K., & Grigoriadou, M. (2004). Designing an adaptive feedback scheme to support reflection in concept mapping. Paper presented at the Proceedings of the Adaptive Hypermedia 2004 Workshop, The Nederlands.
  • Graff, M. (2003). Learning from Web-based instructional systems and cognitive style. British Journal of Educational Technology, 34(4), 407-418.
  • Gunawardena, C.N. & McIsaac, M. S. (2003). Distance education. In D.H. Jonassen (Ed.), Handbook of Research on Educational Communications and Technology, 2nd Edition. (pp. 113-142). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
  • Hannafin, M. J., Hill, J. R., & Land, S. M. (1997). Student-centered learning and interactive multimedia: Status, issues, and implications. Contemporary Education, 68(2), 94-97.
  • Hill, J. R. & Hannafin, M. J. (2001). Teaching and learning in digital environments: The resurgence of resource-based learning. Educational Technology Research & Development, 49(3), 37-52.
  • Inan, F. A. & Grant, M. M. (2004). Applications of adaptive technologies in online learning. Proceeding of the World Conference on E-Learning in Corp., Govt., Health., & Higher Ed., 2004(1), 2701-2706.
  • Inan, F. A. & Grant, M. M (2006, October). Adaptive Web Based Learning Environment (A- WBLE): Synthesis of Empirical Evaluations and Conditions for Successful Adaptive Web Based System Implementation. Paper presented at the Annual Convention of the Association for Educational Communications and Technology, Dallas, TX.
  • Inan, F. A. & Grant, M.M. (2008). Individualized web-based instructional design. In Kidd, T. T., & Song, H. (Eds). Handbook of Research on Instructional Systems and Technology. Harrisburg, PA: Idea Group Publishing.
  • Inan, F. A. & Lowther, D. L. (2007). Comparative analysis of computer-supported learning models and guidelines. In H. F. M. Neto & F. V. Brasileiro (Eds.), Advances in computer- supported learning. Harrisburg, PA: Idea Group Publishing.
  • Inan, F. A. Yildirim, S., & Kiraz, E. (2004). A design and development of an online learning support system (OLSS) for preservice teachers: A discussion of attitudes and utilization. Journal of Interactive Instruction Development, 17(4), 1-15.
  • Khan, B. H. (1997). Web-based instruction. Englewood Cliffs, NJ: Educational Technology Publications.
  • Kelly, D. & Tangney, B. (2004). Evaluating presentation strategy and choice in an adaptive multiple intelligence based tutoring system. Paper presented at the Adaptive Hypermedia 2004 Workshop, The Nederlands.
  • McGrath, B. (1998). Partners in learning: twelve ways technology changes the teacher-student relationship. T.H.E. Journal, 25(9), 58-61.
  • Mitchell, T., Chen, S. Y., & Macredie, R. (2004). Adapting hypermedia to cognitive styles: Is it necessary? Paper presented at the Adaptive Hypermedia 2004 Workshop, The Nederlands.
  • Moore, M. G. & Kearsley, G. (1996). Distance education: A systems view: Wadsworth Publishing Company.
  • Muir, D. J. (2001). Adapting online education to different learning styles. Paper presented at the National Educational Computing Conference, Chicago, IL.
  • O'Brien, B. & Renner, A.L. (2002). Online Student Retention: Can It Be Done? World Conference on Educational Multimedia, Hypermedia and Telecommunications, 2002(1), 1479-1483.
  • Papanikolaou, K. A. & Grigoriadou, M. (2004). Accomodating learning style characteristics in adaptive educational hypermedia systems. Paper presented at the Proceedings of the Adaptive Hypermedia 2004 Workshop, The Nederlands.
  • Papanikolaou, K. A., Grigoriadou, M., Kornilakis, H., & Magoulas, G. D. (2003). Personalizing the interaction in a Web-based educational hypermedia system: The case of INSPIRE. User Modeling and User-Adapted Interaction, 13(3), 213-267.
  • Park, O. & Lee, J. (2003). Adaptive instructional system. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 403-437). Mahwah, NJ: Lawrence Erbaum Associates.
  • Parker, A. (1995). Distance education attrition. International Journal of Educational Telecommunications, 1(4), 389-406.
  • Picciano, A. G. (2001). Distance learning: Making connections across virtual space and time. Upper Saddle River, NJ: Prentice-Hall.
  • Reategui, E., Boff, E., & Campbell, J. A. (2008). Personalization in an interactive learning environment through a virtual character. Computers & Education 51, 530-544.
  • Saba, F. (2002). Student attritions: How to keep your online learner focused. Distance Education Report, 14(4), 1-2.
  • Sabry, K. & Baldwin, L. (2003). Web-based learning interaction and learning styles. British Journal of Educational Technology, 34(4), 443-454.
  • Schrum, L. & Benson, A. (2001). Establishing successful online distance learning environment: Distinguishing factors that contribute to online courses and programs. In R. Discenza, C. Howard & K. Schenk (Eds.), The design and management of effective distance learning programs. Hershey Pa.: Idea Group Publishing.
  • Setzer, J. C. & Lewis, L. (2005). Distance education courses for public elementary and secondary school students: 2002–03 (NCES 2005–010). U.S. Department of Education. Washington, DC: National Center for Education Statistics.
  • Sikora, A. C. & Carroll, C. D. (2003). A profile of participation in distance education: 1999-2000 (No. NCES 2003-154). Washington, DC: National Center for Educational Statistics.
  • Song, L., Singleton, S. E., Hill, J. R. & Koh, M. H. (2004). Improving online learning: Student perceptions of useful and challenging characteristics. Internet and Higher Education, 7(1), 59-70.
  • Terry, N. (2001). Assessing enrollment and attrition rates for the online MBA. T.H.E. Journal, 28(7), 64-68.
  • Triantafillou, E., Pomportsis, A., & Demetriadis, S. (2003). The design and the formative evaluation of an adaptive educational system based on cognitive styles. Computers & Education, 41(1), 87- 103.
  • Triantafillou, E., Pomportsis, A., Demetriadis, S., & Georgiadou, E. (2004). The value of adaptivity based on cognitive style: an empirical study. British Journal of Educational Technology, 35(1), 95-106.
  • Vergidis, D. & Panagiotakopoulos, C. (2002). Student dropout at the Hellenic Open University: Evaluation of the graduate program, “Studies in Education”. International Review of Research in Open and Distance Learning, 3(2).
  • Vonderwell, S. (2003). An examination of asynchronous communication experiences and perspectives of students in an online course: A case study. Internet and Higher Education, 6, 77–90.
  • Xenos, M., Pierrakeas, C., & Pintelas, P. (2002). A survey on student dropout rates and dropout causes concerning the students in the course of informatics of the Hellenic Open University. Computers & Education, 39(4), 361-377.
  • Yukselturk, E. & Inan, F. A. (2006). Examining the factors affecting student dropout in an online learning environment. Turkish Online Journal of Distance Education, 7(2).
  • Zheng, L. & Smaldino, S. (2003). Key instructional design elements for distance education. Quarterly Review of Distance Education, 4(2), 153-166.
  • Correspondence: Fethi A. Inan, Assistant Professor, College of Education, Room #267, Box
  • , Texas Tech University, Lubbock, TX 79409, United States