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Andreea Dutulescu; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This…
Descriptors: Difficulty Level, Reading Tests, Test Items, Reading Comprehension
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Reski Ramadhani; Hilmi Aulawi; Risma Liyana Ulfa – Indonesian Journal of English Language Teaching and Applied Linguistics, 2023
Selecting the appropriate texts as the authentic material for English teaching, particularly at the university level, matched with students' mastery level is still challenging. This study attempts to investigate the readability level of reading texts through the framework of Systemic Functional Linguistics (SFL) issued by ChatGPT, focused on…
Descriptors: Artificial Intelligence, Readability, Reading Materials, Reading Material Selection
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Özcan, Halil Ziya; Batur, Zekerya – International Journal of Education and Literacy Studies, 2021
Literacy is a term generally used for adults and young people. Basically, it is an acquisition that includes the process of reading, writing and understanding symbols in any language. While this concept, whose definition and scope has expanded over time, refers to people who can only say their names in the past, today it refers to individuals who…
Descriptors: Bibliometrics, Journal Articles, Difficulty Level, Reading Comprehension
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Xizhe Wang; Yihua Zhong; Changqin Huang; Xiaodi Huang – IEEE Transactions on Learning Technologies, 2024
Reading comprehension is a widely adopted method for learning English, involving reading articles and answering related questions. However, the reading comprehension training typically focuses on the skill level required for a standardized learning stage, without considering the impact of individual differences in linguistic competence. This…
Descriptors: Reading Comprehension, Artificial Intelligence, Computer Software, Synchronous Communication
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Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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Perkins, Kyle; And Others – Language Testing, 1995
This article reports the results of using a three-layer back propagation artificial neural network to predict item difficulty in a reading comprehension test. Three classes of variables were examined: text structure, propositional analysis, and cognitive demand. Results demonstrate that the networks can consistently predict item difficulty. (JL)
Descriptors: Artificial Intelligence, Difficulty Level, English (Second Language), Language Tests
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Gorin, Joanna S.; Embretson, Susan E. – Applied Psychological Measurement, 2006
Recent assessment research joining cognitive psychology and psychometric theory has introduced a new technology, item generation. In algorithmic item generation, items are systematically created based on specific combinations of features that underlie the processing required to correctly solve a problem. Reading comprehension items have been more…
Descriptors: Difficulty Level, Test Items, Modeling (Psychology), Paragraph Composition