Abstract
Adapting to user context, individual features and behavior patterns is a topic of great attention nowadays in the field of Web-based and mobile mediated platforms, such as eTraining, eCommerce, eLearning and so on. A challenge is to design an expressive ontology that is composed of human factors that can be used in any application, whether that is the WWW or any other embedded information system. Based on that ontology, engineers will design and develop personalized and adaptive interfaces and software. This will enable easy access to any content while being sufficiently flexible to handle changes in users’ context, perception and available resources, optimizing the content delivery while increasing their comprehension capabilities and satisfaction. Therefore, this paper describes a human factors ontology that has been positively evaluated, called UPPC (User Perceptual Preference Characteristics), and could be used in any computer mediated application for returning an optimized adaptive result to the user.
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References
Germanakos, P., Samaras, G., Christodoulou, E.: Multi-channel Delivery of Services - the Road from eGovernment to mGovernment: Further Technological Challenges and Implications (2005)
Germanakos, P., Tsianos, N., Lekkas, Z., Mourlas, C., Samaras, G.: Realizing Comprehensive User Profile as the Core Element of Adaptive and Personalized Communication Environments and Systems. The Computer Journal, Special Issue on Profiling Expertise and Behaviour (2008)
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)
Germanakos, P., Tsianos, N., Mourlas, C., Samaras, G.: New Fundamental Profiling Characteristics for Designing Adaptive Web-based Educational Systems. In: Proceeding of the IADIS International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2005), Porto, December 14-16, pp. 10–17 (2005)
Demetriou, A., Efklides, A., Platsidou, M.: 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 58 (Serial No. 234), 5–6 (1993)
Demetriou, A., Kazi, S.: 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, London (2001)
Baddeley, A.: Working Memory. Science 255, 556–559 (1992)
McKay, M.T., Fischler, I., Dunn, B.R.: Cognitive style and recall of text: An EEG analysis. Learning and Individual Differences 14, 1–21 (2003)
Cassidy, S.: Learning Styles: An overview of theories, models, and measures. Educational Psychology 24(4), 419–444 (2004)
Riding, R.: Cognitive Style Analysis – Research Administration. Learning and Training Technology (2001)
Sadler-Smith, E., Riding, R.J.: Cognitive style and instructional preferences. Instructional Science 27(5), 355–371 (1999)
Glass, A., Riding, R.J.: EEG differences and cognitive style. Biological Psychology 51, 23–41 (1999)
Kim, J., Gorman, J.: The psychobiology of anxiety. Clinical Neuroscience Research 4, 335–347 (2005)
Barlow, D.H.: Anxiety and its disorders: The nature and treatment of anxiety and panic, 2nd edn. The Guilford Press, New York (2002)
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), http://affect.media.mit.edu/projectpages/lc/vworlds.pdf
Goleman, D.: Emotional Intelligence: why it can matter more than IQ. Bantam Books, New York (1995)
Salovey, P., Mayer, J.D.: Emotional intelligence. Imagination, Cognition and Personality 9, 185–211 (1990)
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)
Jarrar, M.: Towards Effectiveness and Transparency in e-Business Transactions, An Ontology for Customer Complaint Management. In: Semantic Web Methodologies for E-Business Applications. Idea Group Inc. (2007)
Tsianos, N., Germanakos, P., Lekkas, Z., Mourlas, C., Samaras, G.: Evaluating the Significance of Cognitive and Emotional Parameters in e-Learning Adaptive Environments. In: Proceedings of the IADIS International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2007), Algarve, Portugal, December 7-9, 2007, pp. 93–98 (2007)
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Germanakos, P., Belk, M., Tsianos, N., Lekkas, Z., Mourlas, C., Samaras, G. (2008). Towards a Human Factors Ontology for Computer-Mediated Systems*. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2008 Workshops. OTM 2008. Lecture Notes in Computer Science, vol 5333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88875-8_83
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DOI: https://doi.org/10.1007/978-3-540-88875-8_83
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