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User sensitive research in e-learning: exploring the role of individual user characteristics

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Abstract

The increasing need for active and accessible learning in the inclusive knowledge society drives the demand for e-learning that engages users much more effectively than ever before. In this context, it is crucial to conduct research that embraces innovation in user sensitive design, or else influential individual user differences may be overlooked. The objective of this paper is to explore the creation of successful e-learning systems that are able to increase users’ learning performance and enhance their personal learning experiences. The paper reports two converging and complimentary approaches, namely case studies and experimentation. First, case studies are used to explore the extent to which effective e-learning systems comply with eight specific factors. Of the eight, accessibility, individual differences and student modeling turn out to be the weakest points in current practice. Second, an empirical study investigates the influences of user individual user differences on users’ learning outcomes in an e-learning environment. The experiment found that individual differences in motivation to learn and expectations about e-learning significantly impacted users’ learning achievements. Third, based on these studies, improvements in research methodology are identified towards greater consideration of user sensitive research issues, thus enabling us to outline improved experimental procedures. Further experiment results should provide us with better insights into the arguments needed to carefully assess benefits of developing and involving a user model in an e-learning application. Consequently, evaluation and justification could now encompass both system performance as well as user performance.

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References

  1. A KnowledgeNet White Paper (2002) Exploding the e-Learning Myth: Next-Generation, Web-Based Training Is Here Today and It Delivers the “Wow” Experience. [Available On-line] http://www.knowledgenet.com/newsroom/whitepapers/elearningmyth.jsp

  2. Adams, R.: Decision and stress: cognition and e-accessibility in the information workplace. Univ. Access Inf. Soc. 5, 363–379 (2007)

    Article  Google Scholar 

  3. Adams, R.: User modeling for intelligent interfaces in e-learning. Lecture Notes in Computer Science: Universal Access in Human-Computer Interaction, Application and Services, vol. 4556, pp. 473–480 (2007)

  4. Adams, R.: Universal access through client-centred cognitive assessment and personality profiling. Lecture Notes in Computer Science, vol. 3196, pp. 3–15 (2004)

  5. Ahmad, A.-R., Basir, O., Hassanein, K.: Adaptive User Interfaces for Intelligent e-Learning: Issues and Trends. In: Proceedings of the Fourth International Conference on Electronic Business, ICEB2004, 925–934, Beijing, China, December 5–9, 2004 (2004)

  6. Aleven, V., McLaren, B.M., Sewall, J., Koedinger, K.R.: http://www.knowledgenet.com/newsroom/whitepapers/elearningmyth_pf.jsp. The Cognitive tutor authoring tools (CTAT): preliminary evaluation of efficiency gains. In: Ikeda M., Ashley K., Chan T.-W. (eds.) ITS 2006. Lecture Notes in Computer Science, vol. 4053, pp. 61–70 (2006)

  7. Anderson, J.R.: Rules of the Mind. Erlbaum, Hillsdale, NJ (1993)

    Google Scholar 

  8. Antona, A., Mourouzis, A., Stephanidis, C.: Towards a walkthrough method for universal access evaluation. Lecture Notes in Computer Science, vol. 4554, pp. 325–334 (2007)

  9. Ayersman, D.J., von Minden, A.: Individual differences, computers, and instruction. Comput. Hum. Behav. 11, 371–390 (1995)

    Google Scholar 

  10. Bell, D.S., Fonarow, G.C., Hays, R.D., Mangione, C.M.: Self-study from web-based and printed guideline materials. A randomized, controlled trial among resident physicians. Ann. Intern. Med. 132, 938–946 (2000)

    Google Scholar 

  11. Benyon, D., Murray, D.: Interacting with Computers. Special Issue Intell. Interface Technol. 12, 315–322 (2000)

    Google Scholar 

  12. Benyon, D., Murray, D.: Developing adaptive systems to fit individual aptitudes. In: Gray, W.D., Hefley, W., Murray, D. (eds.) International Workshop on Intelligent User Interfaces; 1993, January 4–7; Orlando, Florida, USA:115–121 (1993)

  13. Benyon, D., Crerar, A., Wilkinson, S.: Individual differences and inclusive design. In: Stephanidis, C. (ed.) User Interfaces for All—Concepts, Methods, and Tools, pp. 21–46. Lawrence Erlbaum Associates, Mahwah, NJ (2001)

    Google Scholar 

  14. Berkovsky, S., Kuflik, T., Ricci, F.: Mediation of user models for enhanced personalization in recommender systems”, accepted to User Modeling and User-Adapted Interaction (UMUAI). doi:10.1007/s11257-007-9042-9 [available on line] http://www.springerlink.com/content/jt48g17025r8v567/ (2008)

  15. Browne, D., Norman, M., Rithes, D.: Why build adaptive systems? In: Browne, D., Totterdell, P., Norman, M. (eds.) Adaptive User Interfaces, pp. 15–59. Academic Press, London (1990)

    Google Scholar 

  16. Brusilovsky, P.: KnowledgeTree: a distributed architecture for adaptive E-learning. In: Proceedings of the Thirteenth International World Wide Web Conference (WWW 2004) pp. 104–113. ACM Press, New York (2004)

  17. Brusilovsky, P., Milan, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A. & Nejdl, W. (eds.) The Adaptive Web. Methods and Strategies of Web Personalization. Lecture Notes in Computer Science, vol. 4321, pp. 3–53. Springer, Berlin Heidelberg (2007)

  18. Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.): The Adaptive Web. Methods and Strategies of Web Personalization, Lecture Notes in Computer Science, vol. 4321 (2007)

  19. Chen, C., Czerwinski, M., Macredie, R.: Individual differences in virtual environments—introduction and overview. J. Am. Soc. Inf. Sci. 51, 499–507 (2000)

    Article  Google Scholar 

  20. Chin, D.N.: Empirical evaluation of user models and user-adapted systems. User Model User Adapt Interact. 11, 181–194 (2001)

    Article  MATH  Google Scholar 

  21. Christensen, J., Sussman, J., Levy, S., Bennett, W.E., Wolf, T.V., Kellogg, W.A.: Too much information. The future of HCI. ACM Queue 4, 50–57 (2006)

    Article  Google Scholar 

  22. Cronbach, L.J., Snow, R.E.: Aptitudes and Instructional Methods: A Handbook for Research on Interactions. Irvington, New York (1977)

    Google Scholar 

  23. Ćukušić, M., Granić, A., Maršić, I.: Launching an E-learning system in a school. Cross-European e-/m-Learning System UNITE: a Case Study. In: Cordeiro, J., Filipe, J., Hammoudi, S. (eds.) Proceedings of the Fourth International Conference on Web Information Systems and Technologies—WEBIST 2008, Vol. 1. e-Learning, Internet Technology, pp. 380–387. INSTICC PRESS, Portugal (2008)

  24. Dewiyanti, S., Brand-Gruwela, S., Jochems, W., Broers, N.J.: Students’ experiences with collaborative learning in asynchronous computer-supported collaborative learning environments. Comput. Hum. Behav. 23, 496–514 (2007)

    Article  Google Scholar 

  25. Dillon, A., Watson, C.: User analysis in HCI—the historical lessons from individual differences research. Int. J. Hum.-Comput. Stud. 45, 619–637 (1996)

    Article  Google Scholar 

  26. Egan, D.: Individual differences in human-computer interaction. In: Helander, M. (ed.) Handbook of Human-Computer Interaction, pp. 543–568. Elsevier Science B. V. Publishers, North-Holland, Amsterdam (1988)

    Google Scholar 

  27. Fletcher, J.: Evidence for learning from technology—assisted instruction. In: O’Neil, H., Perez, P. (eds.) Technology Applications in Education: A Learning View, pp. 79–99. Lawrence Erlbaum Associates, New York (2003)

    Google Scholar 

  28. Ford, N., Chen, S.Y.: Individual differences, hypermedia navigation and learning: an empirical study. J. Educ. Multimed. Hypermed. 9, 281–311 (2000)

    Google Scholar 

  29. Granić, A.: Experience with usability evaluation of e-learning systems. Univ. Access Inf. Soc. 7, 209–221 (2008)

    Article  Google Scholar 

  30. Granić, A., Nakić, J.: Designing intelligent interfaces for e-learning systems: the role of user individual characteristics. Lecture Notes in Computer Science: Universal Access in Human-Computer Interaction, Application and Services, vol. 4556, pp. 627–636 (2007)

  31. Granić, A., Stankov, S., Nakić, J.: Designing intelligent tutors to adapt individual interaction. Lecture Notes in Computer Science: Universal Access in Ambient Intelligence Environments, vol. 4397, pp. 137–153 (2007)

  32. Gregor, P., Newell A.F., Zajicek, M.: Designing for dynamic diversity—interfaces for older people. In: Jacko, J.A. (ed.): ASSETS 2002. The Fifth International ACM Conference on Assistive Technologies, 8–10 July. Edinburgh, Scotland. 151–156 (2002)

  33. Healey, D.: Theory and research: autonomy in language learning. In: Egbert, J., Hanson-Smith, E. (eds.) CALL Environments: Research, Practice, and Critical Issues, pp. 391–402. Teachers of English to Speakers of Other Languages, Alexandria, VA (1999)

    Google Scholar 

  34. Hook, K.: Steps to take before intelligent user interfaces become real. J. Interact. Comput. 12, 409–426 (2000)

    Article  Google Scholar 

  35. Jennings, F., Benyon, D., Murray, D.: Adapting systems to differences between individuals. Acta Psychol. 78, 243–256 (1991)

    Article  Google Scholar 

  36. Juvina, I., van Oostendorp, H.: Individual differences and behavioral metrics involved in modeling web navigation. Univ. Access Inf. Soc. 4, 258–269 (2006)

    Article  Google Scholar 

  37. Karim, S., Tjoa, A.M.: Towards the use of ontologies for improving user interaction for people with special needs. In: Miesenberger, K. et al. (eds.): ICCHP 2006. Lecture Notes in Computer Science, vol. 4061, pp. 77–84 (2006)

  38. Kerscher, G.: The essential role of libraries serving persons who are blind and print disabled in the information age. In: Miesenberger, K. et al. (eds.): ICCHP 2006. Lecture Notes in Computer Science, vol. 4061, pp. 100–105 (2006)

  39. Kinshuk, K., Patel, A., Russell, D.: Intelligent and adaptive systems. In: Collis, B., Adelsberger, H., Pawlowski, J. (eds.) Handbook on Information Technologies for Education and Training, pp. 79–92. Springer, Heidelberg (2001)

    Google Scholar 

  40. Kobsa, A.: Supporting User Interfaces for All through User Modeling. 6th International Conference on Human-Computer Interaction HCI International 1995, Yokohama, Japan, 155–157. [Available On-line] http://www.ics.uci.edu/~kobsa/papers/1995-HCI95-kobsa.pdf (1995)

  41. Koedinger, K.R., Aleven, V., Heffernan, N.T.: Toward a rapid development environment for Cognitive Tutors. In: Proceedings of the 11th International Conference on Artificial Intelligence in Education, AI-ED 2003 (pp. 455–457). IOS Press, Amsterdam (2003)

  42. Koedinger, K.R., Anderson, J.R., Hadley, W.H., Mark, M.A.: Intelligent tutoring goes to school in the big city. Int. J. Artif. Intell. Educ. 8, 30–43 (1997)

    Google Scholar 

  43. Lieberman, H.: Introduction to intelligent interfaces. [Available On-line] http://web.media.mit.edu/~lieber/Teaching/Int-Int/Int-Int-Intro.html (1997)

  44. Liegle, J.O., Janicki, T.N.: The effect of learning styles on the navigation needs of web-based learners. Comput. Hum. Behav. 22, 885–898 (2006)

    Article  Google Scholar 

  45. Magoulas, G.D., Chen, S.Y., Papanikolaou, K.A.: Integrating layered and heuristic evaluation for adaptive learning environments. In: Weibelzahl, S., Paramythis, A. (eds.) Proceedings of the Second Workshop on Empirical Evaluation of Adaptive Systems, held at the 9th International Conference on User Modeling UM2003, Pittsburgh. pp. 5–14. (2003)

  46. McTear, M.F.: Intelligent interface technology: from theory to reality? Interact. Comput. 12, 323–336 (2000)

    Article  Google Scholar 

  47. Nash, S.S.: Learning objects, learning object repositories and learning theory: preliminary best practices for online courses. Interdiscip. J. Knowl. Learn. Objects 1, 217–228 (2005)

    MathSciNet  Google Scholar 

  48. Newell, A., Gregor, P.: User sensitive inclusive design in search of a new paradigm. In: Scholtz, J., Thomas J. (eds.) First ACM Conference on Universal Usability, pp. 39–44 (2000)

  49. Norman, D., Draper, S.W. (eds.): User Centred System Design. New Perspectives on Human-computer Interaction. Erlbaum, Hillsdale, NJ (1986)

    Google Scholar 

  50. Pantazis, C.: Executive summary: A vision of E-learning for America’s workforce. Report of the Commission on Technology and Adult Learning, ASTD. [Available On-line] http://www.learningcircuits.org/2001/aug2001/pantazis.html (2001)

  51. Pullin, G., Newell, A.: Focussing on extra-ordinary users. Lecture Notes in Computer Science, vol. 4554, pp. 253–262 (2007)

  52. Rich, E.: Users are individuals: individualizing user models. Int. J. Hum.-Comput. Stud. 51, 323–338 (1999)

    Article  Google Scholar 

  53. Schneider-Hufschmidt, M., Kühme, T., Malinowski, U.: Adaptive User Interfaces: Principles and Practice. Elsevier, Amsterdam (1993)

    Google Scholar 

  54. Schweizer, K.: An overview of research into the cognitive basis of intelligence. J. Individ. Differ. 26, 43–51 (2005)

    Article  Google Scholar 

  55. Shute, V., Towle, B.: Adaptive e-learning. Educ. Psychol. 38, 105–114 (2003)

    Article  Google Scholar 

  56. SIGCHI: Notes from E-learning Special Interest Group (SIG). Discussion at CHI 2001, http://www.elearning.org (2001)

  57. Soloway, E., Guzdial, M., Hay, K.E.: Learner-centred design: the challenge for HCI in the 21st Century. Interactions 1, 36–48 (1994)

    Article  Google Scholar 

  58. Soloway, E., Jackson, S., Klein, J., Quintana, C., Reed, J., Spitulnik, J., Stratford, S., Studer, S., Eng, J., Scala, N.: Learning theory in practice: case studies of learner-centered design. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Common Ground. Vancouver, British Columbia, Canada, pp. 189–196 (1996)

  59. Spector, J.M., Anderson, T.M. (eds.): Integrated and Holistic Perspectives on Learning, Instruction and Technology: Understanding Complexity. Kluwer, Dordrecht (2000)

    Google Scholar 

  60. Squires, D., Preece, J.: Usability and learning: evaluating the potential of educational software. Comput. Educ. 27, 15–22 (1996)

    Article  Google Scholar 

  61. VanLehn, K., Lynch, C., Schulze, K., Shapiro, J.A., Shelby, R.: The Andes physics tutoring system: five years of evaluations. In: Proceedings of the 12th International Conference on Artificial Intelligence in Education. IOS Press, Amsterdam (2005)

  62. Woolf, B.: AI in education. In: Shapiro, I., Stuart, C. (eds.) Artificial Intelligence—Encyclopaedias, pp. 434–444. Wiley, New York (1992)

    Google Scholar 

  63. Woolf, B.P., Cunningham, P.: Building a Community Memory for Intelligent Tutoring Systems, pp. 82–89. AAAI, New York (1987)

    Google Scholar 

  64. Yang, S.C., Chen, Y.: Technology-enhanced language learning: a case study. Comput. Hum. Behav. 23, 860–879 (2007)

    Article  Google Scholar 

  65. Zaharias, P.: E-learning design quality: a holistic conceptual framework. In: Encyclopaedia of Distance Learning, Vol. II. Idea Group Inc (2005)

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Acknowledgments

The authors would like to acknowledge support for the work from the project 177-0361994-1998 Usability and Adaptivity of Interfaces for Intelligent Authoring Shells funded by the Ministry of Science, Education and Sports of the Republic of Croatia.

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Granić, A., Adams, R. User sensitive research in e-learning: exploring the role of individual user characteristics. Univ Access Inf Soc 10, 307–318 (2011). https://doi.org/10.1007/s10209-010-0207-7

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