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Qiao Wang; Ralph L. Rose; Ayaka Sugawara; Naho Orita – Vocabulary Learning and Instruction, 2025
VocQGen is an automated tool designed to generate multiple-choice cloze (MCC) questions for vocabulary assessment in second language learning contexts. It leverages several natural language processing (NLP) tools and OpenAI's GPT-4 model to produce MCC items quickly from user-specified word lists. To evaluate its effectiveness, we used the first…
Descriptors: Vocabulary Skills, Artificial Intelligence, Computer Software, Multiple Choice Tests
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2017
This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…
Descriptors: Artificial Intelligence, Natural Language Processing, Reading Comprehension, Literature
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Educational Data Mining Society, 2017
This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…
Descriptors: Artificial Intelligence, Natural Language Processing, Reading Comprehension, Literature
McHugh, David; Shaw, Sarah; Moore, Travis R.; Ye, Leafia Zi; Romero-Masters, Philip; Halverson, Richard – Journal of Research on Technology in Education, 2020
Using a natural language processing tool, this study examined participant discourse in personalized learning schools to better understand what personalized learning looks like in practice. Term frequency-inverse document frequency (tf-idf) was used to identify the significant words and potential emergent themes for 134 interview transcripts. This…
Descriptors: Natural Language Processing, Discourse Analysis, Word Frequency, Identification
Grama, Ileana C.; Kerkhoff, Annemarie; Wijnen, Frank – Journal of Psycholinguistic Research, 2016
The ability to detect non-adjacent dependencies (i.e. between "a" and "b" in "aXb") in spoken input may support the acquisition of morpho-syntactic dependencies (e.g. "The princess 'is' kiss'ing' the frog"). Functional morphemes in morpho-syntactic dependencies are often marked by perceptual cues that render…
Descriptors: Role, Suprasegmentals, Intonation, Cues
Tegos, Stergios; Demetriadis, Stavros; Papadopoulos, Pantelis M.; Weinberger, Armin – International Journal of Computer-Supported Collaborative Learning, 2016
Conversational agents that draw on the framework of academically productive talk (APT) have been lately shown to be effective in helping learners sustain productive forms of peer dialogue in diverse learning settings. Yet, literature suggests that more research is required on how learners respond to and benefit from such flexible agents in order…
Descriptors: Interpersonal Communication, Computer Mediated Communication, Academic Discourse, Peer Relationship
Lintean, Mihai; Rus, Vasile; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2012
This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…
Descriptors: Semantics, Intelligent Tutoring Systems, Prior Learning, Mathematics
Mazur, Michal; Karolczak, Krzysztof; Rzepka, Rafal; Araki, Kenji – International Journal of Distance Education Technologies, 2016
Vocabulary plays an important part in second language learning and there are many existing techniques to facilitate word acquisition. One of these methods is code-switching, or mixing the vocabulary of two languages in one sentence. In this paper the authors propose an experimental system for computer-assisted English vocabulary learning in…
Descriptors: Vocabulary Development, Vocabulary, Code Switching (Language), English (Second Language)
Heiner, Cecily; Zachary, Joseph L. – International Working Group on Educational Data Mining, 2009
Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…
Descriptors: Classification, Questioning Techniques, Introductory Courses, Computer Science Education
Liu, Ming; Calvo, R. A.; Aditomo, A.; Pizzato, L. A. – IEEE Transactions on Learning Technologies, 2012
In this paper, we present a novel approach for semiautomatic question generation to support academic writing. Our system first extracts key phrases from students' literature review papers. Each key phrase is matched with a Wikipedia article and classified into one of five abstract concept categories: Research Field, Technology, System, Term, and…
Descriptors: Foreign Countries, Computer Assisted Instruction, Web 2.0 Technologies, Automation
Matthews, Danielle E.; VanLehn, Kurt; Graesser, Arthur C.; Jackson, G. Tanner; Jordan, Pamela; Olney, Andrew; Rosa, Andrew Carolyn P. – Cognitive Science, 2007
It is often assumed that engaging in a one-on-one dialogue with a tutor is more effective than listening to a lecture or reading a text. Although earlier experiments have not always supported this hypothesis, this may be due in part to allowing the tutors to cover different content than the noninteractive instruction. In 7 experiments, we tested…
Descriptors: Tutoring, Natural Language Processing, Physics, Computer Assisted Instruction
Zafra, Amelia; Ventura, Sebastian – International Working Group on Educational Data Mining, 2009
The ability to predict a student's performance could be useful in a great number of different ways associated with university-level learning. In this paper, a grammar guided genetic programming algorithm, G3P-MI, has been applied to predict if the student will fail or pass a certain course and identifies activities to promote learning in a…
Descriptors: Foreign Countries, Programming, Academic Achievement, Grades (Scholastic)
Osterholm, Magnus – Educational Studies in Mathematics, 2006
This study compares reading comprehension of three different texts: two mathematical texts and one historical text. The two mathematical texts both present basic concepts of group theory, but one does it using mathematical symbols and the other only uses natural language. A total of 95 upper secondary and university students read one of the…
Descriptors: Symbols (Mathematics), Prior Learning, Mathematics, Natural Language Processing
White, Daniel R.; Joy, Mike S. – Journal on Educational Resources in Computing, 2004
With the increasing levels of access to higher education in the United Kingdom, larger class sizes make it unrealistic for tutors to be expected to identify instances of peer-to-peer plagiarism by eye and so automated solutions to the problem are required. This document details a novel algorithm for comparison of suspect documents at a sentence…
Descriptors: Plagiarism, Computer Software, Foreign Countries, Natural Language Processing
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers