The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.03 - July-September (2009 vol.2)
pp: 249-258
Zacharias Lekkas , University of Athens, Athens
Panagiotis Germanakos , University of Nicosia, Nicosia
Costas Mourlas , University of Athens, Athens
Nikos Tsianos , University of Athens, Athens
ABSTRACT
In order to assess the positive effect and validity of personalization on the basis of users' cognitive and emotional characteristics, this study presents three subsequent experiments. The first experiment explores the relationship of cognitive style and users' eye gaze behavior as to validate this specific psychological construct in the context of educational hypermedia. The second and third experiments present the effect of a set of human factors (cognitive style, visual working memory span, control/speed of processing, and anxiety) in an adaptive educational system. The eye tracking experiment demonstrated that eye gaze patterns are robustly related to cognitive style ({\rm n} = 21), while matching the instructional style to users' characteristics was revealed to be statistically significant in optimizing users' performance ({\rm n} = 219), with the exception of control/speed of processing. Based on this empirical assessment, this paper argues that individual differences at this intrinsic level are important and adaptation on these parameters through personalization technologies may have a positive effect on learning performance.
INDEX TERMS
Adaptive hypermedia, computer-assisted instruction, psychology, human factors, personalization.
CITATION
Zacharias Lekkas, Panagiotis Germanakos, Costas Mourlas, Nikos Tsianos, "An Experimental Assessment of the Use of Cognitive and Affective Factors in Adaptive Educational Hypermedia", IEEE Transactions on Learning Technologies, vol.2, no. 3, pp. 249-258, July-September 2009, doi:10.1109/TLT.2009.29
REFERENCES
[1] J. Eklund and K. Sinclair, “An Empirical Appraisal of the Effectiveness of Adaptive Interfaces of Instructional Systems,” Educational Technology and Soc., vol. 3, no. 4, pp. 165-177, 2000.
[2] P. Brusilovsky and W. Neijdl, “Adaptive Hypermedia and Adaptive Web,” The Practical Handbook of Internet Computing, M.P. Singh, ed., vol. 1, no. 14, pp. 1.1-1.14, Chapman & Hall/CRC, 2004.
[3] A. Cristea, C. Stewart, T. Brailsford, and P. Cristea, “Adaptive Hypermedia System Interoperability: A ‘Real World’ Evaluation,” J. Digital Information, vol. 8, no. 3,http://journals.tdl.org/jodi/article/view/ 235192, 2007.
[4] K.A. Papanikolaou, M. Grigoriadou, H. Kornilakis, and G.D. Magoulas, “Personalizing the Interaction in a Web-Based Educational Hypermedia System: The Case of Inspire,” User-Modelling and User-Adapted Interaction, vol. 13, no. 3, pp. 213-267, 2003.
[5] C.A. Carver,Jr., R.A. Howard, and W.D. Lane, “Enhancing Student Learning through Hypermedia Courseware and Incorporation of Student Learning Styles,” IEEE Trans. Education, vol. 42, no. 1, pp. 33-38, 1999.
[6] J.E. Gilbert and C.Y. Han, “Arthur: A Personalized Instructional System,” J. Computing in Higher Education, vol. 14, no. 1, pp. 113-129, 2002.
[7] A.R. Rezaei and R. Katz, “Evaluation of the Reliability and Validity of the Cognitive Styles Analysis,” Personality and Individual Differences, vol. 36, no. 6, pp. 1317-1327, 2004.
[8] E.R. Peterson, I.J. Deary, and E.J. Austin, “The Reliability of Riding's Cognitive Style Analysis Test,” Personality and Individual Differences, vol. 34, no. 5, pp. 881-891, 2003.
[9] M.W. Eysenck and M.T. Keane, Cognitive Psychology, fifth ed. Psychology Press, 2005.
[10] R.J. Sternberg and E.L. Grigorenko, “Are Cognitive Styles Still in Style?” Am. Psychologist, vol. 52, no. 7, pp. 700-712, 1997.
[11] N. Tsianos, P. Germanakos, Z. Lekkas, C. Mourlas, and G. Samaras, “Evaluating the Significance of Cognitive and Emotional Parameters in e-Learning Adaptive Environments,” Proc. Int'l Assoc. Development of the Information Soc. (IADIS) Int'l Conf. Cognition and Exploratory Learning in Digital Age (CELDA '07), pp. 93-98, Dec. 2007.
[12] A. Baddeley, “Working Memory,” Science, vol. 255, pp. 556-559, 1992.
[13] A. Demetriou, A. Efklides, and M. Platsidou, “The Architecture and Dynamics of Developing Mind: Experiential Structuralism as a Frame for Unifying Cognitive Development Theories,” Monographs of the Society for Research in Child Development, Univ. of Chicago Press, 1993.
[14] J.C. Cassady and R.E. Jonhson, “Cognitive Test Anxiety and Academic Performance,” Contemporary Educational Psychology, vol. 27, no. 2, pp. 270-295, 2002.
[15] J.C. Cassady, “The Influence of Cognitive Test Anxiety Across the Learning-Testing Cycle,” Learning and Instruction, vol. 14, no. 6, pp. 569-592, 2004.
[16] C.D. Spielberger, Manual for the State-Trait Anxiety Inventory (STAI). Consulting Psychologists Press, 1983.
[17] P. Germanakos, N. Tsianos, Z. Lekkas, C. Mourlas, M. Belk, and G. Samaras, “An AdaptiveWeb System for Integrating Human Factors in Personalization of Web Content,” Proc. 11th Int'l Conf. User Modeling (UM '07), June 2007.
[18] P. Germanakos, N. Tsianos, Z. Lekkas, C. Mourlas, and G. Samaras, “Capturing Essential Intrinsic User Behaviour Values for the Design of Comprehensive Web-Based Personalized Environments,” Computers in Human Behavior, vol. 24, no. 4, pp. 1434-1451, 2007, doi:10.1016/j.chb.2007.07.010.
[19] S. Rayner, “Cognitive Styles and Learning Styles,” International Encyclopedia of Social & Behavioral Sciences, N.J. Smelser and P.B.Baltes, eds., Elsevier Science Ltd., 2001.
[20] R.J. Riding and I. Cheema, “Cognitive Styles—an Overview and Integration,” Educational Psychology, vol. 11, nos. 3/4, pp. 193-215, 1991.
[21] A. Baddeley, “The Concept of Working Memory: A View of Its Current State and Probable Future Development,” Cognition, vol. 10, nos. 1-3, pp. 17-23, 1981.
[22] A. Baddeley, “The Episodic Buffer: A New Component of Working Memory?” Trends in Cognitive Sciences, vol. 11, no. 4, pp. 417-423, 2000.
[23] R.H. Loggie, G.N. Zucco, and A.D. Baddeley, “Interference with Visual Short-Term Memory,” Acta Psychologica, vol. 75, no. 1, pp.55-74, 1990.
[24] D. DeStefano and J. Lefevre, “Cognitive Load in Hypertext Reading: A Review,” Computers in Human Behavior, vol. 23, no. 3, pp. 1616-1641, 2007.
[25] A. Demetriou and S. Kazi, Unity and Modularity in the Mind and the Self: Studies on the Relationships between Self-Awareness, Personality, and Intellectual Development from Childhood to Adolescence. Routdledge, 2001.
[26] R.W. Picard, Affective Computing. MIT Press, 1997.
[27] P. Salovey and J.D. Mayer, “Emotional Intelligence,” Imagination, Cognition, and Personality, vol. 9, pp. 185-211, 1990.
[28] D. Goleman, Emotional Intelligence: Why It Can Matter More Than IQ. Bantam Books, 1995.
[29] A. Bandura, “Self-Efficacy,” Encyclopedia of Human Behaviour, V.S.Ramachaudran, ed., vol. 4, pp. 71-81, Academic Press, 1994.
[30] A.G. Halberstadt, “Emotional Experience and Expression: An Issue Overview,” J. Nonverbal Behavior, vol. 17, no. 3, pp. 139-143, 2005.
[31] K. Rayner, L. Xingshan, C.C. Williams, R.C. Kyle, and W.D. Arnold, “Eye Movements during Information Processing Tasks: Individual Differences and Cultural Effects,” Vision Research, vol. 47, pp. 2714-2726, 2007.
[32] S.C. Mueller, C.P.T. Jackson, and R.W. Skelton, “Sex Differences in a Virtual Water Maze: An Eye Tracking and Pupillometry Study,” Behavioural Brain Research, vol. 193, pp. 209-215, 2008.
[33] D. Galin and R. Ornstein, “Individual Differences in Cognitive Style—I. Reflective Eye Movements,” Neuropsychologia, vol. 12, pp.367-376, 1974.
[34] A. Demetriou, C. Christou, G. Spanoudis, and M. Platsidou, The Development of Mental Processing: Efficiency, Working Memory, and Thinking (Monographs of the Society of Research in Child Development) vol. 67, no. 268, 2002.
[35] D.A. Norman, “Emotion and Design: Attractive Things Work Better,” Interactions Magazine, vol. 9, no. 4, pp. 36-42, 2002.
32 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool