Implementing Affect Parameters in Personalized Web-Based Design

  • Zacharias Lekkas
  • Nikos Tsianos
  • Panagiotis Germanakos
  • Constantinos Mourlas
  • George Samaras
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5612)


Researchers used to believe that emotional processes are beyond the scope of a scientific study. Recent advances in cognitive science and artificial intelligence, however, suggest that there is nothing mystical about emotional processes. Affective neuroscience and psychology have reported that human affect and emotional experience play a significant, and useful, role in human learning and decision making. Emotions are considered to play a central role in guiding and regulating learning, performance, behaviour and decision making, by modulating numerous cognitive and physiological activities. Our purpose is to improve learning performance and, most importantly, to personalize web-content to users’ needs and preferences, eradicating known difficulties that occur in traditional approaches. Affect parameters are implemented, by constructing a theory that addresses emotion and is feasible in Web-learning environments.


affect emotions mood disposition regulation personalization decision-making learning 


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  1. 1.
    Picard, R.W.: Affective Computing. MIT Press, Cambridge (1997)CrossRefGoogle Scholar
  2. 2.
    Lewis, M., Haviland-Jones, J.M.: Handbook of emotions, 2nd edn. The Guildford Press, New York (2004)Google Scholar
  3. 3.
    Bechara, A., Damasio, H., Damasio, A.R.: Emotion, decision-making, and the orbitofrontal cortex. Cerebral Cortex 10, 295–307 (2000)CrossRefGoogle Scholar
  4. 4.
    Levenson, R.W.: The intrapersonal functions of emotion. Cognition and Emotion 13, 481–504 (1999)CrossRefGoogle Scholar
  5. 5.
    Germanakos, P., Tsianos, N., Lekkas, Z., Mourlas, C., Samaras, G.: Capturing Essential Intrinsic User Behaviour Values for the Design of Comprehensive Web-based Personalized Environments. Computers in Human Behavior Journal, Special Issue on Integration of Human Factors in Networked Computing (2007), doi:10.1016/j.chb.2007. 07.010Google Scholar
  6. 6.
    Lekkas, Z., Tsianos, N., Germanakos, P., Mourlas, C.: Integrating Cognitive and Emotional Parameters into Designing Adaptive Hypermedia Environments. In: Proceedings of the Second European Cognitive Science Conference (EuroCogSci 2007), pp. 705–709 (2007)Google Scholar
  7. 7.
    Tsianos, N., Lekkas, Z., Germanakos, P., Mourlas, C., Samaras, G.: User-centered Profiling on the basis of Cognitive and Emotional Characteristics: An Empirical Study. In: Nejdl, W., Kay, J., Pu, P., Herder, E. (eds.) AH 2008. LNCS, vol. 5149, pp. 214–223. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  8. 8.
    Kim, J., Gorman, J.: The psychobiology of anxiety. Clinical Neuroscience Research 4, 335–347 (2005)CrossRefGoogle Scholar
  9. 9.
    Barlow, D.H.: Anxiety and its disorders: The nature and treatment of anxiety and panic, 2nd edn. The Guilford Press, New York (2002)Google Scholar
  10. 10.
    Schunk, D.H.: Self-efficacy and cognitive skill learning. In: Ames, C., Ames, R. (eds.) Research on motivation in education. Goals and cognitions, vol. 3, pp. 13–44. Academic Press, San Diego (1989)Google Scholar
  11. 11.
    Kort, B., Reilly, R.: Analytical Models of Emotions, Learning and Relationships: Towards an Affect-Sensitive Cognitive Machine. In: Conference on Virtual Worlds and Simulation (VWSim 2002) (2002),
  12. 12.
    Goleman, D.: Emotional Intelligence: why it can matter more than IQ. Bantam Books, New York (1995)Google Scholar
  13. 13.
    Salovey, P., Mayer, J.D.: Emotional intelligence. Imagination, Cognition and Personality 9, 185–211 (1990)CrossRefGoogle Scholar
  14. 14.
    Barsade, S., Brief, A., Spataro, S.: The affective revolution in organizational behavior: The emergence of a paradigm. In: Greenberg, J. (ed.) Organizational Behavior: The State of the Science, p. 352. Lawrence Erlbaum Associates, Publishers, London (2003)Google Scholar
  15. 15.
    Cassady, C.C.: The influence of cognitive test anxiety across the learning–testing cycle. Learning and Instruction 14, 569–592 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Zacharias Lekkas
    • 1
  • Nikos Tsianos
    • 1
  • Panagiotis Germanakos
    • 2
    • 3
  • Constantinos Mourlas
    • 1
  • George Samaras
    • 3
  1. 1.Faculty of Communication and Media StudiesNational & Kapodistrian University of AthensAthensGreece
  2. 2.Department of Management and MISUniversity of NicosiaNicosiaCyprus
  3. 3.Computer Science DepartmentUniversity of CyprusNicosiaCyprus

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