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Marilena Panaite; Mihai Dascalu; Amy Johnson; Renu Balyan; Jianmin Dai; Danielle S. McNamara; Stefan Trausan-Matu – Grantee Submission, 2018
Intelligent Tutoring Systems (ITSs) are aimed at promoting acquisition of knowledge and skills by providing relevant and appropriate feedback during students' practice activities. ITSs for literacy instruction commonly assess typed responses using Natural Language Processing (NLP) algorithms. One step in this direction often requires building a…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Algorithms, Decision Making
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…
Descriptors: Phrase Structure, Networks, Semantics, Feedback (Response)
Jinnie Shin; Renu Balyan; Michelle P. Banawan; Tracy Arner; Walter L. Leite; Danielle S. McNamara – Grantee Submission, 2023
Despite the proliferation of video-based instruction and its benefits--such as promoting student autonomy and self-paced learning--the complexities of online teaching remain a challenge. To be effective, educators require extensive training in digital teaching methodologies. As such, there's a pressing need to examine and comprehend the…
Descriptors: Algebra, Mathematics Instruction, Video Technology, Personal Autonomy
Allen, Laura K.; Mills, Caitlin; Perret, Cecile; McNamara, Danielle S. – Grantee Submission, 2019
This study examines the extent to which instructions to self-explain vs. "other"-explain a text lead readers to produce different forms of explanations. Natural language processing was used to examine the content and characteristics of the explanations produced as a function of instruction condition. Undergraduate students (n = 146)…
Descriptors: Language Processing, Science Instruction, Computational Linguistics, Teaching Methods
Steven Moore; John Stamper; Norman Bier; Mary Jean Blink – Grantee Submission, 2020
In this paper we show how we can utilize human-guided machine learning techniques coupled with a learning science practitioner interface (DataShop) to identify potential improvements to existing educational technology. Specifically, we provide an interface for the classification of underlying Knowledge Components (KCs) to better model student…
Descriptors: Learning Analytics, Educational Improvement, Classification, Learning Processes
Lillie Moffett; Frederick J. Morrison – Grantee Submission, 2020
Behavioral self-regulation supports young children's learning and is a strong predictor of later academic achievement. The capacity to manage one's attention and control one's behavior is commonly measured via direct assessments of executive function (EF). However, to understand how EF skills contribute to academic achievement, it is helpful to…
Descriptors: Self Control, Executive Function, Inhibition, Short Term Memory
Chounta, Irene-Angelica; Albacete, Patricia; Jordan, Pamela; Katz, Sandra; McLaren, Bruce M. – Grantee Submission, 2017
In this paper, we propose a computational approach to model the Zone of Proximal Development (ZPD) using predicted probabilities of correctness and engaging students in reflective dialogue. To that end, we employ a predictive model that uses a linear function of a variety of parameters, including difficulty and student knowledge and we analyze the…
Descriptors: Learning Theories, Sociocultural Patterns, Intelligent Tutoring Systems, Physics
Chounta, Irene-Angelica; McLaren, Bruce M.; Albacete, Patricia; Jordan, Pamela; Katz, Sandra – Grantee Submission, 2017
In this paper, we propose a computational approach to modeling the Zone of Proximal Development of students who learn using a natural language tutoring system for physics. We employ a student model that predicts students' performance based on their prior knowledge and their activity when using a dialogue tutor to practice with conceptual,…
Descriptors: Learning Theories, Sociocultural Patterns, Intelligent Tutoring Systems, Physics
Brawner, Catherine E.; Felder, Richard M.; Allen, Rodney; Brent, Rebecca – Grantee Submission, 2003
SUCCEED (Southeastern University and College Coalition for Engineering Education) is an eight-campus coalition of engineering schools formed in 1992 under the sponsorship of the National Science Foundation. In 1997, a faculty survey of instructional practices and attitudes regarding the climate for teaching on the Coalition campuses was designed…
Descriptors: Teacher Surveys, Teaching Methods, Teacher Attitudes, Active Learning