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Diego G. Campos; Tim Fütterer; Thomas Gfrörer; Rosa Lavelle-Hill; Kou Murayama; Lars König; Martin Hecht; Steffen Zitzmann; Ronny Scherer – Educational Psychology Review, 2024
Systematic reviews and meta-analyses are crucial for advancing research, yet they are time-consuming and resource-demanding. Although machine learning and natural language processing algorithms may reduce this time and these resources, their performance has not been tested in education and educational psychology, and there is a lack of clear…
Descriptors: Artificial Intelligence, Algorithms, Computer System Design, Natural Language Processing
Becker, Kirk A.; Kao, Shu-chuan – Journal of Applied Testing Technology, 2022
Natural Language Processing (NLP) offers methods for understanding and quantifying the similarity between written documents. Within the testing industry these methods have been used for automatic item generation, automated scoring of text and speech, modeling item characteristics, automatic question answering, machine translation, and automated…
Descriptors: Item Banks, Natural Language Processing, Computer Assisted Testing, Scoring
Joseph Gagen Stockdale III – Online Submission, 2025
"A Dictionary of Contemporary Figurative Language" is meant to be an appendix to an earlier, more comprehensive work: ED648945, "A Dictionary and Thesaurus of Contemporary Figurative Language and Metaphor 2024." This appendix simply updates the dictionary of that previous work to better reflect the language used during the 2024…
Descriptors: Figurative Language, Language Usage, Dictionaries, Phrase Structure
Richie, Russell; Bhatia, Sudeep – Cognitive Science, 2021
Similarity is one of the most important relations humans perceive, arguably subserving category learning and categorization, generalization and discrimination, judgment and decision making, and other cognitive functions. Researchers have proposed a wide range of representations and metrics that could be at play in similarity judgment, yet have not…
Descriptors: Classification, Generalization, Decision Making, Cognitive Processes
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
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)
Jones, Michael N. – Grantee Submission, 2018
Abstraction is a core principle of Distributional Semantic Models (DSMs) that learn semantic representations for words by applying dimensional reduction to statistical redundancies in language. Although the posited learning mechanisms vary widely, virtually all DSMs are prototype models in that they create a single abstract representation of a…
Descriptors: Abstract Reasoning, Semantics, Memory, Learning Processes
Cai, Zhiqiang; Siebert-Evenstone, Amanda; Eagan, Brendan; Shaffer, David Williamson; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2019
Coding is a process of assigning meaning to a given piece of evidence. Evidence may be found in a variety of data types, including documents, research interviews, posts from social media, conversations from learning platforms, or any source of data that may provide insights for the questions under qualitative study. In this study, we focus on text…
Descriptors: Semantics, Computational Linguistics, Evidence, Coding
Michelle P. Banawan; Jinnie Shin; Tracy Arner; Renu Balyan; Walter L. Leite; Danielle S. McNamara – Grantee Submission, 2023
Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities in how they construe and communicate meaning. This study examines the extent to which discourse…
Descriptors: Algebra, Discourse Analysis, Semantics, Syntax
Olmos, Ricardo; Jorge-Botana, Guillermo; León, José Antonio; Escudero, Inmaculada – Discourse Processes: A multidisciplinary journal, 2014
This study presents a new approach for transforming the latent representation derived from a Latent Semantic Analysis (LSA) space into one where dimensions have nonlatent meanings. These meanings are based on lexical descriptors, which are selected by the LSA user. The authors present three analyses that provide examples of the utility of this…
Descriptors: Natural Language Processing, Methods, Validity, Reliability
Liu, Ming; Rus, Vasile; Liu, Li – IEEE Transactions on Learning Technologies, 2017
Question generation is an emerging research area of artificial intelligence in education. Question authoring tools are important in educational technologies, e.g., intelligent tutoring systems, as well as in dialogue systems. Approaches to generate factual questions, i.e., questions that have concrete answers, mainly make use of the syntactical…
Descriptors: Chinese, Questioning Techniques, Automation, Natural Language Processing
Kim, Minkyu – Educational Technology Research and Development, 2013
The purpose of this study is to develop a better understanding of technologies that use natural language as the basis for concept map construction. In particular, this study focuses on the semantic relation (SR) approach to drawing rich and authentic concept maps that reflect students' internal representations of a problem situation. The…
Descriptors: Concept Mapping, Natural Language Processing, Semantics, Problem Solving
Lezcano, Leonardo; Sanchez-Alonso, Salvador; Roa-Valverde, Antonio J. – Program: Electronic Library and Information Systems, 2013
Purpose: The purpose of this paper is to provide a literature review of the principal formats and frameworks that have been used in the last 20 years to exchange linguistic resources. It aims to give special attention to the most recent approaches to publishing linguistic linked open data on the Web. Design/methodology/approach: Research papers…
Descriptors: Information Transfer, Data, Computational Linguistics, Internet
Alqady, Mohammed – ProQuest LLC, 2012
The construction industry is a knowledge intensive industry. Thousands of documents are generated by construction projects. Documents, as information carriers, must be managed effectively to ensure successful project management. The fact that a single project can produce thousands of documents and that a lot of the documents are generated in a…
Descriptors: Construction Industry, Information Management, Semantics, Content Analysis
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