Eye-Tracking Users' Behavior in Relation to Cognitive Style within an E-learning Environment

Eye-tracking measurements may be used as a method of identifying users’ actual behavior in a hypermedia setting. In this research, an eye-tracking experiment was conducted in order to validate the construct of cognitive style as a personalization parameter in adaptive e-Learning systems. The main research question was whether the verbalizer/ imager axis of the Cognitive Style Analysis theory reflects actual preferences in an e-learning environment and properly identifies learner types. The findings from a sample of 21 participants reveal statistically significant differences among types of learners; as hypothesized, imagers concentrate on visual content, verbalizers on text, while intermediates are placed in between.

[1]  Carrick C. Williams,et al.  Eye movements during information processing tasks: Individual differences and cultural effects , 2007, Vision Research.

[2]  George D. Magoulas,et al.  Personalizing the Interaction in a Web-based Educational Hypermedia System: the case of INSPIRE , 2003, User Modeling and User-Adapted Interaction.

[3]  Larry Katz,et al.  Evaluation of the reliability and validity of the cognitive styles analysis , 2004 .

[4]  George Ghinea,et al.  The impact of cognitive styles on perceptual distributed multimedia quality , 2003, Br. J. Educ. Technol..

[5]  Bruce R. Dunn,et al.  Cognitive style and recall of text: An EEG analysis , 2003 .

[6]  David N. Rapp,et al.  The value of attention aware systems in educational settings , 2006, Comput. Hum. Behav..

[7]  S. Cassidy,et al.  Learning Styles: An overview of theories, models, and measures , 2004 .

[8]  Alexandros Paramythis,et al.  Adaptive Learning Environments and e-Learning Standards. , 2004 .

[9]  E. Sadler‐Smith,et al.  Cognitive style and instructional preferences , 1999 .

[10]  R. Riding,et al.  Cognitive Styles—an overview and integration , 1991 .

[11]  Rico Fischer,et al.  Eye tracking and its application in usability and media research , 2003, MMI Interakt..

[12]  K. Ecclestone,et al.  Learning styles and pedagogy in post-16 learning , 2004 .

[13]  Paul Dan Cristea,et al.  Adaptive Hypermedia System Interoperability: a 'real world' evaluation , 2007, J. Digit. Inf..

[14]  F. Coffield.  Learning styles and pedagogy in post-16 learning: a systematic and critical review , 2004 .

[15]  Panagiotis Germanakos,et al.  The Role of Emotions in the Design of Personalized Educational Systems , 2008, 2008 Eighth IEEE International Conference on Advanced Learning Technologies.

[16]  Fred Paas,et al.  How do I do? Investigating effects of expertise and performance-process records on self-assessment. , 2009 .

[17]  Cristina Conati,et al.  Eye-tracking for user modeling in exploratory learning environments: An empirical evaluation , 2007, Knowl. Based Syst..

[18]  E. Sadler‐Smith.  The relationship between learning style and cognitive style , 2001 .

[19]  Curtis A. Carver,et al.  Enhancing student learning through hypermedia courseware and incorporation of student learning styles , 1999 .

[20]  Carl P. T. Jackson,et al.  Sex differences in a virtual water maze: An eye tracking and pupillometry study , 2008, Behavioural Brain Research.

[21]  Panagiotis Germanakos,et al.  User-Centric Profiling on the Basis of Cognitive and Emotional Characteristics: An Empirical Study , 2008, AH.

[22]  Christian Gütl,et al.  AdELE: A Framework for Adaptive E-Learning through Eye Tracking , 2004 .

[23]  R. Riding,et al.  Towards a Categorisation of Cognitive Styles and Learning Styles , 1997 .

[24]  Juan E. Gilbert,et al.  Arthur: A personalized instructional system , 2002, J. Comput. High. Educ..

[25]  V. Shute,et al.  Adaptive E-Learning , 2003, Educational Psychologist.

[26]  D Galin,et al.  Individual differences in cognitive style--I. Reflective eye movements. , 1974, Neuropsychologia.