Designing learner-controlled educational interactions based on learning/cognitive style and learner behaviour

Abstract

Recently, research in individual differences and in particular, learning and cognitive style, has been used as a basis to consider learner preferences in a web-based educational context. Modelling style in a web-based learning environment demands that developers build a specific framework describing how to design a variety of options for learners with different approaches to learning. In this paper two representative examples of educational systems, Flexi-OLM and INSPIRE, that provide learners a variety of options designed according to specific style categorisations, are presented. Experimental results from two empirical studies performed on the systems to investigate learners' learning and cognitive style, and preferences during interaction, are described. It was found that learners do have a preference regarding their interaction, but no obvious link between style and approaches offered, was detected. Derived from an examination of this experimental data, we suggest that while style information can be used to inform the design of learning environments that accommodate learners' individual differences, it would be wise to recommend interactions based on learners' behaviour. Learning environments should allow learners or learners' interaction behaviour to select or trigger the appropriate approach for Interacting with Computers 18 (2006) 356-384 www.elsevier.com/locate/intcom 0953-5438/$ -see front matter q (K.A. Papanikolaou), axm891@bham.ac.uk (A. Mabbott), s.bull@bham. ac.uk (S. Bull), gregor@di.uoa.gr (M. Grigoriadou).the particular learner in the specific context. Alternative approaches towards these directions are also discussed. q

Adaptive Content Presentation in Asynchronous Learning Environments

“…Considerably more efforts have been made so far regarding the online LS detection [5]. To this direction, empirical studies were conducted on two educational systems (Flexi-OLM & INSPIRE) to investigate learners' learning and cognitive style, and preferences during interaction [6]. The Index of LSs questionnaire was used to assess the style of each participant according to the four dimensions of the Felder-Silverman LS model.…”

“…Based on techniques described in [6] the system estimates the best possible LS that fit the user's cognitive characteristics. As far as the available tools for such estimation rank the LS from the most to the less alike, the proposed P-TPN may use the second best fitted to the user LS.…”

Recent Contributions to a Generic Architecture Design that Supports Learning Objects Interoperability

“…Learning Styles (LSs) or Cognitive Styles (CSs) [11]. Although some authors do not distinguish between LSs and CSs [12], there are others who clearly do [13], [14]. According to Riding and Rayner (1998) [15], CS refers to an individual's method of processing information.…”

“…In another work, Papanikolaou, Mabbott et al, (2006) [13] conducted empirical studies on two educational systems (Flexi-OLM and INSPIRE) to investigate learners' learning and cognitive style, and preferences during interaction. The Index of Learning Styles questionnaire was used to asses the style of each participant according to the four dimensions of the Felder-Silverman LS model.…”

Information systems for higher education: interactive design perspective

“…These differences include amongst others, gender differences (Ford and Miller, 1996), system experience (Holscherl and Strubel, 2000), prior knowledge and spatial ability (Mayer and Gallini, 1990), occupational experience (Durling et al, 1996), culture differences (De Vita 2001;Fry 1975), cultural andvocational (Al-Khatib, 2007) and cognitive styles (Durfresne and Turcotte, 1997;Shih and Gamon, 1999). However, individual differences make designing learning systems a complex task that requires flexibility in terms of accommodating a wide range of characteristics (Galitz, 2002;Papanikolaou et al, 2006), and for such systems to be interactive, certain qualities and principles need to be applied to different learners' needs . Effective use of Computer Mediated Communication (CMC) can result in an increase, not a decrease, in learning interactions such as student-student and instructor-student interactivity (Lavooy & Newlin, 2003), and technology tools can be used to communicate, scaffold, and clarify course concepts and content while engaging students with information (Solvie and Kloek, 2007).…”