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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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Proceedings Article

The ADAIO System at the BEA-2023 Shared Task: Shared Task Generating AI Teacher Responses in Educational Dialogues

Adaeze Adigwe, +1 more
TL;DR: This article used a few-shot prompt-based approach with the OpenAI text-davinci-003 model for teacher response generation in the 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues.
Book ChapterDOI

Methods of Determining Errors in Open-Ended Text Questions

TL;DR: Open-ended text questions allow for better assessment students’ knowledge, but analyzing the answer, determining it’s correctness and providing detailed and meaningful feedback about errors to a student are more difficult tasks than for closed-ended and numerical questions.
Dissertation

Unsupervised Relation Extraction for E-Learning Applications

Naveed Afzal
TL;DR: This thesis proposes a Natural Language Processing (NLP) based approach that relies on semantic relations extracted using Information Extraction to automatically generate MCTs, and presents two unsupervised RE approaches (surface-based and dependencybased).
Posted Content

Towards Neural Speaker Modeling in Multi-Party Conversation: The Task, Dataset, and Models

TL;DR: This paper proposed speaker classification as a surrogate task for general speaker modeling, and collected massive data to facilitate research in this direction, and further investigate temporal-based and content-based models of speakers, and propose several hybrids of them.
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.