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Pugh, Samuel L.; Subburaj, Shree Krishna; Rao, Arjun Ramesh; Stewart, Angela E. B.; Andrews-Todd, Jessica; D'Mello, Sidney K. – International Educational Data Mining Society, 2021
We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…
Descriptors: Problem Solving, Cooperation, Middle School Students, High School Students
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Albacete, Patricia; Jordan, Pamela; Katz, Sandra; Chounta, Irene-Angelica; McLaren, Bruce M. – Grantee Submission, 2019
This paper describes an initial pilot study of Rimac, a natural-language tutoring system for physics. Rimac uses a student model to guide decisions about "what content to discuss next" during reflective dialogues that are initiated after students solve quantitative physics problems, and "how much support to provide" during…
Descriptors: Natural Language Processing, Teaching Methods, Educational Technology, Technology Uses in Education
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Jordan, Pamela; Albacete, Patricia; Katz, Sandra – Grantee Submission, 2016
Prior research aimed at identifying linguistic features of tutoring that predict learning found interactions between student characteristics (e.g., incoming knowledge level, gender, and affect) and learning. This paper addresses the question: "What do these interactions suggest for developing adaptive natural-language tutoring systems?"…
Descriptors: Intelligent Tutoring Systems, Tutoring, Natural Language Processing, Student Characteristics
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Jordan, Pamela; Albacete, Patricia; Katz, Sandra – Grantee Submission, 2016
We explore the effectiveness of a simple algorithm for adaptively deciding whether to further decompose a step in a line of reasoning during tutorial dialogue. We compare two versions of a tutorial dialogue system, Rimac: one that always decomposes a step to its simplest sub-steps and one that adaptively decides to decompose a step based on a…
Descriptors: Algorithms, Decision Making, Intelligent Tutoring Systems, Scaffolding (Teaching Technique)
Oberem, Graham E. – 1994
The limited language capability of CAI systems has made it difficult to personalize problem-solving instruction. The intelligent tutoring system, ALBERT, is a problem-solving monitor and coach that has been used with high school and college level physics students for several years; it uses a natural language system to understand kinematics…
Descriptors: Computer Assisted Instruction, Computer Simulation, Higher Education, Intelligent Tutoring Systems