Adaptive web-based learning: accommodating individual differences through system's adaptation

The idea of developing educational hypermedia systems for the Web is very challenging, and demands the synergy of computer science and instructional science. The paper builds on theories from instructional design and learning styles to develop a design rational and guidelines for adaptive web-based learning systems that use individual differences as a basis of system’s adaptation. Various examples are provided to illustrate how instructional manipulations with regards to content adaptation and presentation, and adaptive navigation support, as well as the overall degree of system adaptation are guided by educational experiences geared towards individual differences. Adaptive web-based learning: accommodating individual differences through system’s adaptation George Magoulas, Kyparisia Papanikolaou and Maria Grigoriadou George D. Magoulas is a Lecturer at Brunel University and conducts interdisciplinary research concerned with learning and adaptation in intelligent systems. He has a PhD in the area of intelligent systems and a Post Graduate Certificate in Teaching and Learning in Higher Education. Kyparisia Papanikolaou works as a research fellow at the Department of Informatics and Telecommunications of the University of Athens. Maria Grigoriadou is Associate Professor of Computer Science in the Department of Informatics and Telecommunications at the University of Athens and director of the “Educational and Language Technology” laboratory at the same department. Address for correspondence: Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3 PH, UK. Email: [email protected] © British Educational Communications and Technology Agency, 2003. Published by Blackwell Publishing Ltd., 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA. Introduction The appearance and spread of educational technology, and particularly of computerbased systems, is beginning to transform the processes of teaching and learning in higher education. Along this line, individualised learning provides students the capability to select the mode of delivery and timing of module material. A primary principle of individualised learning is that no single instructional strategy is best for all students. As a consequence students will be able to achieve learning goals more efficiently when pedagogical procedures are adapted to their individual differences (Federico, 2000). Among other considerations, an important step in the design of instruction and its methodologies is the identification of student needs and learning preferences. Investigations of student learning preferences have shown that among the variables that influence the success of learning, e.g. gender, age group, prior experience and discipline of study, learning styles are considered particularly important (Ford and Chen, 2000). British Journal of Educational Technology Vol 34 No 4 2003 – bjet_12 5/30/2003 7:08 PM Page 1 Among a range of categorisations of learning styles, Curry (1987) organised the various learning styles into three categories or models (i) Instructional and environmental learning preferences: this model refers to the individual’s choice of the environment within which they learn. It is expected that these preferences are likely to change and are influenced by the learning context. (ii) Information processing style: this model, whilst not directly interacting with the learning environment, is capable of adaptation through learning experience and the development of learning strategies. (iii) Personality related learning preferences: this is considered as an underlying and relatively permanent personality characteristic. Sadler-Smith (1996) extended Curry’s models to include (iv) Learning strategies: these are similar to a plan of action adopted in learning through study and experience, and (v) Cognitive strategy: this is considered as a plan of action adopted in organising and processing information. An attempt to integrate the many conceptualisations of learning styles has been made by Riding and Cheema (1991), and led to the development of a two-dimensional model of cognitive style. In their model, one dimension is conceptualised as Wholist-Analytic and the other as Verbaliser-Imager. Riding and Sadler-Smith (1992) have suggested that the Field-dependence/Field-independence dimension (Witkin et al, 1977) is a label used within the Wholist-Analytic cognitive style family (p. 324), with the Fielddependents lying within the Wholist category. Another effort has been made by Honey and Mumford (1992). Honey and Mumford, based on Kolb’s theory of experiential learning (Kolb, 1984), suggested four types of learners: Activists, Pragmatists, Reflectors, and Theorists. Also, several attempts have been made, such as those proposed by Smith and Kolb (1996) and Sadler-Smith and Riding (1999) with the aim to assess students’ learning styles. Assessing students’ learning styles provides awareness of their particular preferences, which can be used to design, develop, and deliver educational material or resources to maximally motivate and stimulate students’ acquisition of subject matter in an attempt to individualise instruction (Kaplan and Kies, 1995). Understanding learning styles can improve the planning, producing, and implementing of educational experiences, so they are more appropriately tailored to students’ expectations, in order to enhance their learning, retention and retrieval (Federico, 2000). The emergence of the Web as an instructional medium has led to the design of studentcentred systems with the aim to enhance the learning experience (Lin and Hsieh, 2001). It is expected that enhancement of the effectiveness can be achieved by recognising students’ learning needs, the diversification of learning styles, preferences with respect to specific learning processes, as well as interests in specific learning modules that cover their knowledge deficit. All these are important attributes that characterise each student and form a kind of student model that incorporates student’s individual 2 British Journal of Educational Technology Vol 34 No 4 2003 © British Educational Communications and Technology Agency, 2003. bjet_12 5/30/2003 7:08 PM Page 2