Abstract
We define job interviews as a domain of interaction that can be modelled automatically in a serious game for job interview skills training. We present four types of studies: (1) field-based human-to-human job interviews, (2) field-based computer-mediated human-to-human interviews, (3) lab-based wizard of oz studies, (4) field-based human-to-agent studies. Together, these highlight pertinent questions for the user modelling field as it expands its scope to applications for social inclusion. The results of the studies show that the interviewees suppress their emotional behaviours and although our system recognises automatically a subset of those behaviours, the modelling of complex mental states in real-world contexts poses a challenge for the state-of-the-art user modelling technologies. This calls for the need to re-examine both the approach to the implementation of the models and/or of their usage for the target contexts.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Posthuma, R.A., Morgeson, F.P., Campion, M.A.: Beyond employment interview validity: A comprehensive narrative review of recent research and trends over time. Personnel Psychology 55(1), 1–82 (1982)
Sieverding, M.: Be cool!: Emotional costs of hiding feelings in a job interview. International Journal of Selection and Assessment 17(4), 391–401 (2009)
Conati, C.: How to evaluate models of user affect? In: André, E., Dybkjær, L., Minker, W., Heisterkamp, P. (eds.) ADS 2004. LNCS (LNAI), vol. 3068, pp. 288–300. Springer, Heidelberg (2004)
Porayska-Pomsta, K., Mavrikis, M., D’Mello, S., Conati, C., Baker, R.: Knowledge elicitation methods for affect modelling in education. International Journal of Artificial Intelligence in Education 22(3), 107–140 (2013)
Porayska-Pomsta, K., Anderson, K., Damian, I., Baur, T., André, E., Bernardini, S., Rizzo, P.: Modelling users’ affect in job interviews: Technological demo. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds.) UMAP 2013. LNCS, vol. 7899, pp. 353–355. Springer, Heidelberg (2013)
Anderson, K., André, E., Baur, T., Bernardini, S., Chollet, M., Chryssafidou, E., Damian, I., Ennis, C., Egges, A., Gebhard, P., Jones, H., Ochs, M., Pelachaud, C., Porayska-Pomsta, K., Rizzo, P., Sabouret, N.: The TARDIS framework: Intelligent virtual agents for social coaching in job interviews. In: Reidsma, D., Katayose, H., Nijholt, A. (eds.) ACE 2013. LNCS, vol. 8253, pp. 476–491. Springer, Heidelberg (2013)
De Groot, T., Janaki, G.: Can nonverbal cues be used to make meaningful personality attributions in employment interviews? Journal of Business Psychology 24, 179–192 (2009)
Curhan, J., Pentland, A.: Thin slices of negotiation: predicting outcomes from conversational dynamics within the first 5 minutes. Journal of Applied Psychology 92(3), 802–811 (2007)
Schmidt, N.: Social and situational determinants of interview decisions: Implications for the employment interview. Journal of Personnel Psychology 29, 79–101 (1976)
Ryan, A.M., Daum, D., Friedel, L.: Interviewing behavior: Effects of experience, self-efficacy, attitudes and job-search behavior. In: Annual Conference of the Society for Industrial and Organizational Psychology, San Franscisco, CA (1993)
Barber, A.E., Hollenbeck, J.R., Tower, S.L., Phillips, J.M.: The effects of interview focus on recruitment effectiveness: a field experiment. Journal of Applied Psychology 79, 886–896 (1994)
Vinciarelli, A., Pantic, M., Heylen, C., Pelachaud, C., Poggi, F., Errico, A., Schroeder, M.: Bridging the gap between social animal and unsocial machine: A survey of social signal processing. IEEE Transactions on Affective Computing. 3(1), 69–87 (2012)
Vogt, T., André, E., Lewis, T., R., Leibbrandt, Powers, D.: Comparing feature sets for acted and spontaneous speech in view of automatic emotion recognition. In: IEEE International Conference on Multimedia and Expo, pp. 474–477 (2005)
Zeng, Z., Pantic, M., Roisman, G.I., Huang, T.S.: A survey of affect recognition methods: Audio, visual, and spontaneous expressions. IEEE Trans. Pattern Anal. Mach. Intell. 31(1), 39–58 (2009)
Kapoor, A., Picard, R.W.: Multimodal affect recognition in learning environments. In: Proceedings of ACM MM 2005, pp. 677–682 (2005)
Kleinsmith, A., Bianchi-Berthouze, N.: Form as a cue in the automatic recognition of non-acted affective body expressions. In: Proceedings of the 4th International Conference on Affective Computing and Intelligent Interaction, Amsterdam, Netherlands. Part I, pp. 155–164 (2011)
Batrinca, L., Stratou, G., Shapiro, A., Morency, L.-P., Scherer, S.: Cicero - towards a multimodal virtual audience platform for public speaking training. In: Aylett, R., Krenn, B., Pelachaud, C., Shimodaira, H. (eds.) IVA 2013. LNCS, vol. 8108, pp. 116–128. Springer, Heidelberg (2013)
Hoque, M.E., Courgeon, M., Martin, J., Mutlu, B., Picard, R.W.: Mach: My automated conversation coach. In: International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2013 (2013)
Damian, I., Baur, T., André, E.: Investigating social cue-based interaction in digital learning games. In: Proceedings of the 8th International Conference on the Foundations of Digital Games, SASDG (2013)
Wagner, J., Lingenfelser, F., Baur, T., Damian, I., Kistler, F., André, E.: The social signal interpretation (ssi) framework - multimodal signal processing and recognition in real-time. In: Proceedings of ACM MULTIMEDIA 2013, Barcelona (2013)
Niewiadomski, R., Hofmann, J., Urbain, J., Platt, T., Wagner, J., Piot, B., Cakmak, H., Pammi, S., Baur, T., Dupont, S., Geist, M., Lingenfelser, F., McKeown, G., Pietquin, O., Ruch, W.: Laugh-aware virtual agent and its impact on user amusement. In: Proceedings of the 2013 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2013, pp. 619–626. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2013)
Kistler, F., Endrass, B., Damian, I., Dang, C.T., André, E.: Natural interaction with culturally adaptive virtual characters. Journal on Multimodal User Interfaces 6, 39–47 (2012)
Küblbeck, C., Ernst, A.: Face detection and tracking in video sequences using the modifiedcensus transformation. Image Vision Comput. 24(6), 564–572 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Porayska-Pomsta, K. et al. (2014). Who’s Afraid of Job Interviews? Definitely a Question for User Modelling. In: Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P., Houben, GJ. (eds) User Modeling, Adaptation, and Personalization. UMAP 2014. Lecture Notes in Computer Science, vol 8538. Springer, Cham. https://doi.org/10.1007/978-3-319-08786-3_37
Download citation
DOI: https://doi.org/10.1007/978-3-319-08786-3_37
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08785-6
Online ISBN: 978-3-319-08786-3
eBook Packages: Computer ScienceComputer Science (R0)