Journal ArticleDOI
AutoTutor: an intelligent tutoring system with mixed-initiative dialogue
TLDR
Grounded in constructivist learning theories and tutoring research, AutoTutor achieves learning gains of approximately 0.8 sigma (nearly one letter grade), depending on the learning measure and comparison condition.Abstract:
AutoTutor simulates a human tutor by holding a conversation with the learner in natural language. The dialogue is augmented by an animated conversational agent and three-dimensional (3-D) interactive simulations in order to enhance the learner's engagement and the depth of the learning. Grounded in constructivist learning theories and tutoring research, AutoTutor achieves learning gains of approximately 0.8 sigma (nearly one letter grade), depending on the learning measure and comparison condition. The computational architecture of the system uses the .NET framework and has simplified deployment for classroom trials.read more
Citations
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Proceedings Article
Question Ranking and Selection in Tutorial Dialogues
TL;DR: This work learns to rank using judgments collected from expert human tutors, and shows that adding features derived from a rich, multi-layer dialogue act representation improves system performance over baseline lexical and syntactic features to a level in agreement with the judges.
Intentionally Generating Choices in Interactive Narratives.
TL;DR: This system description paper presents a system that creates choices by reasoning about their structure, and describes the architecture that enables it to do so.
Book ChapterDOI
How to Integrate Emotions in Dialogues With Pedagogic Conversational Agents to Teach Programming to Children
TL;DR: Al Alcody as mentioned in this paper is an interactive system that allows children to interact with a pedagogic conversational agent (PCA) to teach programming to children, using six emotions: happiness, anger, sadness, fear, surprise, and disgust.
Journal ArticleDOI
The Effects of System Initiative during Conversational Collaborative Search
TL;DR: In this paper , the authors report on a Wizard of Oz lab study in which 27 pairs of participants collaborated on search tasks over the Slack messaging platform, where the role of the searchbot was played by a reference librarian.
Book ChapterDOI
Q-Genesis: Question Generation System Based on Semantic Relationships
TL;DR: Question generation system based on semantic relationships (Q-Genesis) is proposed to generate more relevant knowledge level questions automatically and it will be useful for the trainer to assess the knowledge level of the learners.
References
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Book
Affective Computing
TL;DR: Key issues in affective computing, " computing that relates to, arises from, or influences emotions", are presented and new applications are presented for computer-assisted learning, perceptual information retrieval, arts and entertainment, and human health and interaction.
Journal ArticleDOI
An introduction to latent semantic analysis
TL;DR: The adequacy of LSA's reflection of human knowledge has been established in a variety of ways, for example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word‐word and passage‐word lexical priming data.
Journal ArticleDOI
Intelligent tutoring systems
TL;DR: Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP.
Journal ArticleDOI
Cognitive Tutors: Lessons Learned
TL;DR: The 10-year history of tutor development based on the advanced computer tutoring (ACT) theory is reviewed, finding that a new system for developing and deploying tutors is being built to achieve the National Council of Teachers of Mathematics (NCTM) standards for high-school mathematics in an urban setting.