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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Journal ArticleDOI
Keep Me in the Loop: Real-Time Feedback with Multimodal Data
TL;DR: The CPR Tutor as discussed by the authors is a real-time multimodal feedback system for cardiopulmonary resuscitation (CPR) training that detects training mistakes using recurrent neural networks.
Proceedings ArticleDOI
Students' experiences in guided computer-based learning: A progressive evaluation
TL;DR: Computer-based guided learning systems should consider students' background of knowledge in their design to achieve effective learning, and the combination of the fully-and partially-guided features may create an adaptive computer-based learning system.
Book ChapterDOI
Adaptive Technologies for Training and Education: Progress in Assessment and Tutoring of Lifelong Learning Skills
Journal ArticleDOI
Integrating a dialog system with an intelligent tutoring system for a 3D virtual laboratory
TL;DR: This paper addresses the challenge of integrating a dialog system with an ITS created for supporting procedural training in a 3D virtual environment by describing the desired feat.
A Conversational Agent for the Improvement of Human Reasoning Skills
TL;DR: The evaluation study shows that the conversational agent Liza improved the reasoning skills of the participants, who had conversations with the agent to solve reasoning problems and that the group using Liza achieved much better learning effects than a group studying with a non-interactive online course that was implemented as a control condition.
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.