On Modeling of Interviewee Motivation Mental States for an Intelligent Coaching Agent

N. S. Ajoge, A. A. Aziz, S. A. Mohd Yusof

Abstract


This paper is on agent based model of interview motivation to be integrated in a mental constructs model which serves as a basic mechanics for an intelligent virtual agent coaching for job interview. It has been hypothesized that interview motivation combines with self-efficacy and anxiety to define the mental state of a job interviewee. The concepts were modeled based on psychological theories defining human mental state in a time bounded tasking situation like job interview. The proposed model was formalized and simulated to according to its temporal behaviours. The results of the simulation conform to patterns of a number of relations and casual effects on motivation identified in literature. Additionally, the formal model has been automatically verified using Temporal Trace Language (TTL) to find out which stable situations exist. Consequently, this model can serve as a platform for designing an intelligent agent that can understand the metal state of the user during job interview coaching session.

Keywords


Cognitive Modelling; Intelligent Virtual Agent; Interview Mental State; Motivation in Job Interview;

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References


K. Anderson et al., “The TARDIS framework: Intelligent virtual agents for social coaching in job interviews,” in Advances in Computer Entertainment, vol. 8253 LNCS, D. Reidsma, H. Katayose, and A. Nijholt, Eds. Berlin, Heidelberg: Springer, 2013, pp. 476–491.

M. Hoque, M. Courgeon and J. Martin, “Mach: My automated conversation coach,” in Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2013, pp. 697–706.

A. I. Huffcutt, C. H. Van Iddekinge, and P. L. Roth, “Understanding applicant behavior in employment interviews: A theoretical model of interviewee performance,” Hum. Resour. Manag. Rev., vol. 21, no. 4, pp. 353–367, 2011.

E. L. Deci and R. Ryan, “Motivation, personality, and development within embedded social contexts: An overview of self-determination theory,” in The Oxford Handbook of Human Motivation, R. M. Ryan, Ed. Oxford University Press, 2012.

A. A. Aziz, M. C. A. Klein, and J. Treur, “An agent model of temporal dynamics in relapse and recurrence in depression,” in Proceedings of the Belgian/Netherlands Artificial Intelligence Conference, 2009, pp. 279–280.

S. B. Brundage, K. Graap, K. F. Gibbons, M. Ferrer, and J. Brooks, “Frequency of stuttering during challenging and supportive virtual reality job interviews,” Journal of Fluency Disorder, vol. 31, no. 4, pp. 325–339, 2006.

J. H. Kwon, J. Powell, and A. Chalmers, “How level of realism influences anxiety in virtual reality environments for a job interview,” International Journal of Human-Computer Studies, vol. 71, no. 10, pp. 978–987, 2013.

J. Sabourin, B. Mott, and J. Lester, “Computational models of affect and empathy for pedagogical virtual agents,” in Standards in Emotion Modeling, 2011, pp. 1-14.

H. Prendinger, J. Mori, and M. Ishizuka, “Recognizing, modeling, and responding to users’ affective states,” in Proceedings of the 10th Int. Conf. on User Model. 2005, pp. 60-69.

C. LeRouge, K. Dickhut, C. Lisetti, S. Sangameswaran, and T. Malasanos, “Engaging adolescents in a computer-based weight management program: Avatars and virtual coaches could help,” Journal of the American Medical Informatics Association, vol. 23, no. 1, pp. 19–28, 2016.

S. Carnell, S. Halan, M. Crary, A. Madhavan, and B. Lok, “Adapting virtual patient interviews for interviewing skills training of novice healthcare students,” in International Conference on Intelligent Virtual Agents, 2015, pp. 50–59.

A. Shamekhi and T. Bickmore, “Breathe with me: A virtual meditation coach,” in International Conference on Intelligent Virtual Agents, 2015, pp. 279–282.

D. H. Schunk, J. R. Meece, and P. R. Pintrich, Motivation in Education: Theory, Research, and Applications. NJ: Pearson Higher Ed., 2012.

D. Weinberg, Robert & Gould, Foundations of Sport and Exercise Psychology, 5th ed. Human Kinetics, 2011.

E. Locke, “Motivation, cognition, and action: An analysis of studies of task goals and knowledge,” Applied Psychology, vol. 49, no. 3, pp. 408- 429, 2000.

C. J. De Brabander and R. L. Martens, “Towards a unified theory of task-specific motivation,” Educational Research Review, vol. 11, pp. 27-44, 2014.

A. Wigfield, and J. S. Eccles, “Expectancy-Value Theory of achievement motivation,” Contemporary Educational Psychology, vol. 25, no. 1, pp. 68-81, 2000.

E. A. Locke and G. P. Latham, “Building a practically useful theory of goal setting and task motivation: A 35-year odyssey,” American Psychologist, vol. 57, no. 9, pp. 705-717, 2002.

K. C. Cukrowicz, A. T. Franzese, S. R. Thorp, J. S. Cheavens and T. R. Lynch, “Personality traits and perceived social support among depressed older adults,” Aging Mental Health, vol. 12, no. 5, pp. 662- 669, 2008.

B. Weiner, Human Motivation. Psychology Press, 2013.

J. B. Vancouver and L. N. Kendall, “When self-efficacy negatively relates to motivation and performance in a learning context.,” Journal of Applied Psychology, vol. 91, no. 5, pp. 1146-1153, 2006.

T. Bosse, C. M. Jonker, L. Van Der Meij, A. Sharpanskykh and J. Treur, “Specification and verification of dynamics in agent models,” The International Journal of Cooperative Information System., vol. 18, no. 1, pp. 167–193, 2009.


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