Towards new forms of knowledge communication: the adaptive dimension of a web-based learning environment

Adaptive Educational Hypermedia Systems aim to increase the functionality of hypermedia by making it personalised to individual learners. The adaptive dimension of these systems mainly supports knowledge communication between the system and the learner by adapting the content or the appearance of hypermedia to the knowledge level, goals and other characteristics of each learner. The main objectives are to protect learners from cognitive overload and disorientation by supporting them to find the most relevant content and path in the hyperspace. In the approach presented in this paper, learners’ knowledge level and individual traits are used as valuable information to represent learners’ current state and personalise the educational system accordingly, in order to facilitate learners to achieve their personal learning goals and objectives. Learners’ knowledge level is approached through a qualitative model of the level of performance that learners exhibit with respect to the concepts they study and is used to adapt the lesson contents and the navigation support. Learners’ individual traits and especially their learning style represent the way learners perceive and process information, and are exploited to adapt the presentation of the educational material of a lesson. The proposed approach has been implemented through various adaptation technologies and incorporated into a prototype hypermedia system. Finally, a pilot study has been conducted to investigate system’s educational effectiveness. # 2002 Elsevier Science Ltd. All rights reserved.

[1]  Marcus Specht ACE - Adaptive Courseware Environment , 2000, AH.

[2]  Peter Brusilovsky,et al.  Adaptive and Intelligent Technologies for Web-based Eduction , 1999, Künstliche Intell..

[3]  Ann L. Brown,et al.  How people learn: Brain, mind, experience, and school. , 1999 .

[4]  Annemarie Hauf,et al.  Computers in education , 1983 .

[5]  Patrick Brézillon,et al.  Lecture Notes in Artificial Intelligence , 1999 .

[6]  Charles M. Reigeluth,et al.  The elaboration theory of instruction , 1983 .

[7]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[8]  Peter Brusilovsky,et al.  Methods and techniques of adaptive hypermedia , 1996, User Modeling and User-Adapted Interaction.

[9]  George D. Magoulas,et al.  INSPIRE: An INtelligent System for Personalized Instruction in a Remote Environment , 2001, OHS-7/SC-3/AH-3.

[10]  Margaret Honey,et al.  A manual of learning styles , 1986 .

[11]  Charles M. Reigeluth,et al.  Instructional Design Theories and Models : An Overview of Their Current Status , 1983 .

[12]  George A. Vouros,et al.  Methods and Applications of Artificial Intelligence , 2004, Lecture Notes in Computer Science.

[13]  Juan E. Gilbert,et al.  Adapting instruction in search of 'a significant difference' , 1999, J. Netw. Comput. Appl..

[14]  Gerhard Weber,et al.  User Modeling and Adaptive Navigation Support in WWW-Based Tutoring Systems , 1997 .

[15]  Peter Brusilovsky,et al.  Web-Based Education for All: A Tool for Development Adaptive Courseware , 1998, Comput. Networks.

[16]  George D. Magoulas,et al.  Neuro-fuzzy synergism for planning the content in a web-based course , 2001, Informatica.

[17]  Anne Groat,et al.  Learning styles: Individualizing computer‐based learning environments , 1995 .

[18]  Emilia Pecheanu,et al.  A Hybrid Aproach to Dynamic Course Generation on the WWW , 2000 .

[19]  Kyparisia A. Papanikolaou,et al.  LEARNING ENVIRONMENTS ON THE WEB: The Pedagogical Role of the Educational Material , 2000 .

[20]  Mia Stern,et al.  Adaptive Content in an Online Lecture System , 2000, AH.

[21]  Ioannis Vlahavas,et al.  Methods and Applications of Artificial Intelligence , 2002, Lecture Notes in Computer Science.

[22]  Mary Beth Rosson,et al.  Human-computer interaction scenarios as a design representation , 1990, Twenty-Third Annual Hawaii International Conference on System Sciences.

[23]  Jakob Nielsen,et al.  Designing web usability , 1999 .

[24]  Peter Brusilovsky Intelligent Tutoring Systems for the World-Wide Web , 1995, WWW Spring 1995.

[25]  Petrus A.M. Kommers,et al.  Intelligent Agent Instructional Design Tool for Hypermedia Design Course. , 1999 .

[26]  George D. Magoulas,et al.  A Connectionist Approach for Supporting Personalized Learning in a Web-Based Learning Environment , 2000, AH.

[27]  Riichiro Mizoguchi,et al.  Artificial Intelligence in Education: Knowledge and Media in Learning Systems , 1997 .

[28]  D. Dunn,et al.  Experiential Learning , 2019, High Impact Teaching for Sport and Exercise Psychology Educators.