Enhance Knowledge Communication and Learning: A Surprise Paradox.

Ruth Chatelain-Jardon, Jesus S Carmona, Jose Luis Daniel


Human-computer interface is a pivotal factor that can promote or deter the effectiveness of Web-based knowledge communication. There is abundant research that strain to improve interfaces by considering user needs through usability studies, however, few research considers the incorporation of automatic brain mechanisms in order to improve knowledge communication performance. The objective of this research is not to establish a relationship between the negative stimulus presence and improved knowledge communication, but rather to show that the shape of this function follows the Yerkes–Dodson Law. Partial least squares (PLS) was utilized to analyze the data. Results found in this study support the evidence that surprising negative events enhance knowledge communication effectiveness, but more importantly that the surprise-performance relationship is not a linear function but follows the inverted U shape.


Human Computer Interaction; Web Interface Design; Automatic Brain Mechanisms; Enhanced Memorization Capacity; Web-based Learning

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Training Industry Report, (2017), Retrieved September 4th 2017, from https://trainingmag.com/trgmag-article/2017-training-industry-report/

Alhajraf, N. M., & Alasfour, A. M. (2014). The impact of demographic and academic characteristics on academic performance. International Business Research, 7(4), 92-100.

Babson Survey Research Group, (2016): Grade increase: Tracking distance education in the United States, Retrieved September, 4th 2017, from https://www.onlinelearningsurvey.com/highered.html

Buss, D.M. (1995). Evolutionary psychology: A new paradigm for psychological science. Psychological Inquiry, 6(1), 1-30.

Chatelain-Jardon, R., Carmona, J., & Kock, N. (2016). An extension to simulated web-based threats and their impact on knowledge communication effectiveness. International Journal of Technology and Human Interaction, 12(3), 64-77

Chin, W.W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7-16.

Du, C., & Wu, J. (2014). The effect of human interactions on student performance and satisfaction of blended learning. Academy of Educational Leadership Journal, 18(3), 11-21.

Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.

Gefen, D., Straub, D. W., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the AIS, 4(7), 1-76.

Guile, D. & Griffiths, T. (2001). Learning through work experience. Journal of Education and Work, 14(1), 113-131.

Hair, J.F., Anderson, R.E., & Tatham, R.L. (1987). Multivariate data analysis, 2nd Edition. New York, NY: Macmillan.

Johnston CA, Moreno JP, Regas K, Tyler C, Foreyt JP. The application of the Yerkes-Dodson law in a childhood weight management program: examining weight dissatisfaction. J Pedi- atr Psychol. 2012;37:674-9.

Kock, N. (2018). WarpPLS User Manual: Version 6.0. Laredo, TX: ScriptWarp Systems

Kock, N., Chatelain-Jardon, R. & Carmona, J. (2008). An experimental study of simulated web-based threats and their impact on knowledge communication effectiveness. IEEE Transactions on Professional Communication, 51(2), 183-197.

Kock, N., Chatelain-Jardon, R. & Carmona, J. (2008) a. Incorporating simulated animal attacks in human-technology interaction interfaces: The predictive power of biosemiotics and evolutionary psychology. International Journal of Technology and Human Interaction, 4(4), 68-87.

Kock, N., Chatelain-Jardón, R. & Carmona, J. (2009), Scaring them into learning!? Using a snake screen to enhance the knowledge transfer effectiveness of a web interface. Decision Sciences Journal of Innovative Education, 7(2), 359-375.

Kock, N., & Lynn, G.S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustrationand recommendations. Journal of the Association for Information Systems, 13(7), 546-580.

Maksy, M. (2014). Factors associated with student performance in intermediate accounting: A comparative study at commuter and residential schools. The Journal of Applied Business and Economics, 16(5), 86-108.

Meyer, W., Reisenzein, R., & Schutzwohl, A. (1997). Toward a process analysis of emotions: The case of surprise. Motivation and Emotion, 21(3), 251-274.

Newell, A., & Card, S.K. (1985). The prospects for psychological science in human-computer interaction. Human Computer Interaction, 1(3), 209-242.

Picciano, A.G. (2002). Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal for Asynchronous Learning Networks 6(1), 21-40.

Real, J.C., Leal, A. & Roldan, J.L. (2006). Information technology as a determinant of organizational learning and technological distinctive competencies. Industrial Marketing Management, 35(4), 505-521.

Schnitman, I. (2007). The Dynamics Involved in Web-based Learning Environment (WLE) Interface Design and Human-Computer Interactions (HCI): Connections with Learning Performance. Morgantown, West Virginia: West Virginia University.

Schmidt, N., Richey, A., Zvolensky, M., & Maner, J. (2008). Exploring human freeze responses to a threat stressor. Journal of Behavior Therapy and Experimental Psychiatry, 39(3), 292-304.

Schützwohl, A. & Borgstedt, K. (2005). The processing of affectively valenced stimuli: The role of surprise. Cognition & Emotion, 19(4), 583-600.

Sotgiu, I. & Galati, D. (2007). Long-term memory for traumatic events: Experiences and emotional reactions during the 2000 flood in Italy. The Journal of Psychology, 141, 91-108.

Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habitformation. Journalof Comparative Neurology, 18, 459-482.

DOI: http://dx.doi.org/10.4301/S1807-1775201815011