The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Probabilistic assessment of user's emotions in educational games
Open accessAbstract
We present a probabilistic model to monitor a user's emotions and engagement during the interaction with educational games. We illustrate how our probabilistic model assesses affect by integrating evidence on both possible causes of the user's emotional arousal (i.e., the state of the interaction) and its effects (i.e., bodily expressions that are known to be influenced by emotional reactions). The probabilistic model relies on a Dynamic Decision Network to leverage any indirect evidence on the user's emotional state, in order to estimate this state and any other related variable in the model. This is crucial in a modeling task in which the available evidence usually varies with the user and with each particular interaction. The probabilistic model we present is to be used by decision theoretic pedagogical agents to generate interventions aimed at achieving the best tradeoff between a user's learning and engagement during the interaction with educational games.
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Cites
Picard, R. W. (1997) · MIT Press · doi:10.7551/mitpress/1140.001.0001 · Cited by 7,382
The Cognitive Structure of Emotions
Ortony, A., Clore, G. L., & Collins, A. (1988) · doi:10.1017/cbo9780511571299 · Cited by 6,208
A model for reasoning about persistence and causation
Dean, T., & Kanazawa, K. (1989) · Computational Intelligence · doi:10.1111/j.1467-8640.1989.tb00324.x · Cited by 999
Cited by
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
Calvo, R. A., & D'Mello, S. (2010) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2010.1 · Cited by 1,893
Baker, R. S. J. D., D'Mello, S. K., Rodrigo, M. M. T., & Graesser, A. C. (2010) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2009.12.003 · Cited by 936
Experience-Driven Procedural Content Generation
Yannakakis, G. N., & Togelius, J. (2011) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.6 · Cited by 470
Toward an Affect-Sensitive AutoTutor
D'Mello, S., Picard, R. W., & Graesser, A. (2007) · IEEE Intelligent Systems · doi:10.1109/mis.2007.79 · Cited by 386
Are they different? Affect, feeling, emotion, sentiment, and opinion detection in text
Munezero, M., Montero, C. S., Sutinen, E., & Pajunen, J. (2014) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2014.2317187 · Cited by 374
Metadata
- Authors
- Conati, C.
- Venue
- Applied Artificial Intelligence
- Publisher
- Informa UK Limited
- Published
- 2002-08
- Volume
- 16
- Issue
- 7-8
- Pages
- 555-575
- ISSN
- 0883-9514 (ISSN-L)
- 1087-6545
- OpenAlex
- W2151562475
- Cited by
- 498
- References
- 3
- FWCI
- 16.39
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Conati, C. (2002). Probabilistic assessment of user's emotions in educational games. Applied Artificial Intelligence. https://doi.org/10.1080/08839510290030390
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
