Detecting and Addressing Frustration in a Serious Game for Military Training

Autor/inn/en	DeFalco, Jeanine A.; Rowe, Jonathan P.; Paquette, Luc; Georgoulas-Sherry, Vasiliki; Brawner, Keith; Mott, Bradford W.; Baker, Ryan S.; Lester, James C.
Titel	Detecting and Addressing Frustration in a Serious Game for Military Training
Quelle	In: International Journal of Artificial Intelligence in Education, 28 (2018) 2, S.152-193 (42 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1560-4292
DOI	10.1007/s40593-017-0152-1
Schlagwörter	Psychological Patterns; Stress Variables; Educational Games; Intelligent Tutoring Systems; Military Training; Affective Behavior; Measurement Equipment; Validity; Intervention; Feedback (Response); Motivation Techniques; Outcomes of Education; Self Efficacy; Experiments; Computer Simulation; Learner Engagement; Persistence; Correlation; Statistical Analysis + Suchen Sie Ihr Suchwort? Educational game; Lernspiel; Intelligentes Tutorsystem; Militärausbildung; Affective disturbance; Active behaviour; Affektive Störung; Messinstrument; Gültigkeit; Motivationsförderung; Lernleistung; Schulerfolg; Self-efficacy; Selbstwirksamkeit; Erprobung; Computergrafik; Computersimulation; Ausdauer; Korrelation; Statistische Analyse
Abstract	Tutoring systems that are sensitive to affect show considerable promise for enhancing student learning experiences. Creating successful affective responses requires considerable effort both to detect student affect and to design appropriate responses to affect. Recent work has suggested that affect detection is more effective when both physical sensors and interaction logs are used, and that context-sensitive design of affective feedback is necessary to enhance engagement and improve learning. In this paper, we provide a comprehensive report on a multi-part study that integrates detection, validation, and intervention into a unified approach. This paper examines the creation of both sensor-based and interaction-based detectors of student affect, producing successful detectors of student affect. In addition, it reports results from an investigation of motivational feedback messages designed to address student frustration, and investigates whether linking these interventions to detectors improves outcomes. Our results are mixed, finding that self-efficacy enhancing interventions based on interaction-based affect detectors enhance outcomes in one of two experiments investigating affective interventions. This work is conducted in the context of the GIFT framework for intelligent tutoring, and the TC3Sim game-based simulation that provides training for first responder skills. (As Provided).
Anmerkungen	Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01