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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.

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Citations
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Journal ArticleDOI

Notions of explainability and evaluation approaches for explainable artificial intelligence

Giulia Vilone, +1 more
- 01 Dec 2021 - 
TL;DR: This systematic review contributes to the body of knowledge by clustering all the scientific studies via a hierarchical system that classifies theories and notions related to the concept of explainability and the evaluation approaches for XAI methods.
Journal ArticleDOI

Emote aloud during learning with AutoTutor: Applying the Facial Action Coding System to cognitive–affective states during learning

TL;DR: In this paper, the authors used an emote-aloud procedure in which participants were recorded as they verbalised their affective states while interacting with an intelligent tutoring system (AutoTutor).
Posted Content

Explainable Artificial Intelligence: a Systematic Review

TL;DR: This systematic review contributes to the body of knowledge by clustering these methods with a hierarchical classification system with four main clusters: review articles, theories and notions, methods and their evaluation.
Journal ArticleDOI

Explanation Feedback Is Better Than Correct Answer Feedback for Promoting Transfer of Learning

TL;DR: This paper investigated whether feedback that provides an explanation of the correct answer promotes superior transfer of learning to new questions and found that explanation feedback produced superior performance on the new inference questions compared to correct answer feedback.
Proceedings ArticleDOI

Programming challenges of chatbot: Current and future prospective

TL;DR: An overview of cloud-based chatbots technologies along with programming of chatbots and challenges of programming in current and future Era of chatbot is given.
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.