AutoTutor: A tutor with dialogue in natural language

By A. Graesser, Shulan Lu, G. T. Jackson, Heather H. Mitchell, M. Ventura, Andrew McGregor Olney, Max M. Louwerse. Behavoir research methods, instruments & computers, 2004

583 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/92bed1ffb5d5eb17a5d45d0e8f784c46caaa693c

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In Artificial Intelligence

In Developmental and Educational Psychology

Citations in the corpus

The Behavior of Tutoring Systems (2006, background): “org/) teaches by engaging students in a natural language (English) dialogue (Graesser et al., 2004; Graesser et al., 2003; Graesser, WiemerHastings, Wiemer-Hastings, & Kreuz, 1999; Person, Graesser, Bautista, Mathews, & TRG, 2001) For AutoTutor, a task corresponds to a single question, such as the o”
Better to be frustrated than bored: The incidence, persistence, and impact of learners' cognitive-affective states during interactions with three different computer-based learning environments (2010, result): “Similar results were reported in a version of AutoTutor on the subject matter of computer literacy (Graesser et al., 2004).”
Scaffolding Deep Comprehension Strategies Through Point&Query, AutoTutor, and iSTART (2005, background): “AutoTutor is a computer tutor that attempts to simulate the dialogue moves of a human tutor (Graesser, Lu, et al., 2004; Graesser, Person & Harter, 2001; Graesser, VanLehn, Rose, Jordan, & Harter, 2001).”
Do pedagogical agents make a difference to student motivation and learning (2011, unknown): “Accordingly, evaluative studies of specific pedagogical agents such as “AutoTutor” or “Ore-Age” (Graesser, Chipman, Haynes, & Olney, 2005; Graesser et al., 2004; Guray, Celebi, Atalay, & Pasamehmetoglu, 2003), or the prototypes “CoPAS”, “SA-Agent” and “Rule-Editor” (Morch, Dolonen, & Naevdal,…”
Affect and learning: An exploratory look into the role of affect in learning with AutoTutor (2004, methodology): “The 34 undergraduate participants were observed individually while they worked with AutoTutor.”
Handbook of Research on Learning and Instruction (2011, background): “Thus, children were taught to move based on elite, adult movement models rather than developmentally appropriate patterns such as those that Roberton (1982) described.”
Symbol Interdependency in Symbolic and Embodied Cognition (2011, methodology): “AutoTutor uses LSA for its model of the world knowledge serving as a model of the long-term memory of a conversational partner and determining the semantic association between a student answer, and ideal good and bad answers (Graesser, VanLehn, Rose, Jordan, & Harter, 2001; Graesser et al., 2004).”
Dynamics of affective states during complex learning (2012, background): “The impact of AutoTutor in facilitating the learning of deep conceptual knowledge has been validated in over a dozen experiments on college students (Graesser et al., 2004; VanLehn et al., 2007).”
Intelligent tutoring systems and learning outcomes: A meta-analysis (2014, methodology): “AutoTutor is an ITS that supports natural language dialogue for instruction that, like much observed human tutoring, involves " imprecise verbal content , a low to medium level of user knowledge about a topic, and earnest literal replies " (Graesser et al., 2004, p. 181).”
Multimodal semi-automated affect detection from conversational cues, gross body language, and facial features (2010, background): “The impact of AutoTutor in facilitating the learning of deep conceptual knowledge has been validated in more than a dozen experiments on college students (Graesser et al. 2004; Storey et al. (in press); VanLehn et al. 2007).”
AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring (2014, methodology): “This foreshadowed a pattern of higher learning gains for deep reasoning with AutoTutor (Graesser et al. 2004b, 2010).”
Detection of Emotions during Learning with AutoTutor (2006, background): “…that college students experience while interacting with AutoTutor, an intelligent tutoring system that helps students learn by holding a conversation in natural language (Graesser, Chipman, Haynes, & Olney, 2005; Graesser et al., 2004; Graesser, Person, & Harter, 2001; VanLehn et al., in press).”