{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,6]],"date-time":"2025-07-06T04:42:04Z","timestamp":1751776924188,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009]]},"abstract":"<jats:p>This study shows that affect-adaptive computer tutoring can significantly improve performance on learning efficiency and user satisfaction. We compare two different student uncertainty adaptations which were designed, implemented and evaluated in a controlled experiment using four versions of a wizarded spoken dialogue tutoring system: two adaptive systems used in two experimental conditions (basic and empirical), and two non-adaptive systems used in two control conditions (normal and random). In prior work we compared learning gains across the four systems; here we compare two other important performance metrics: learning efficiency and user satisfaction. We show that the basic adaptive system outperforms the normal (non-adaptive) and empirical (adaptive) systems in terms of learning efficiency. We also show that the empirical (adaptive) and random (non-adaptive) systems outperform the basic adaptive system in terms of user perception of tutor response quality. However, only the basic adaptive system shows a positive correlation between learning and user perception of decreased uncertainty.<\/jats:p>","DOI":"10.3233\/978-1-60750-028-5-33","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:05Z","timestamp":1740133625000},"source":"Crossref","is-referenced-by-count":9,"title":["Adapting to Student Uncertainty Improves Tutoring Dialogues"],"prefix":"10.3233","author":[{"family":"Forbes-Riley Kate","sequence":"additional","affiliation":[]},{"family":"Litman Diane","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Artificial Intelligence in Education"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:02:00Z","timestamp":1740135720000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0922-6389&volume=200&spage=33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-60750-028-5-33","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2009]]}}}