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Marian Marchal; Merel C. J. Scholman; Vera Demberg – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Linguistic phenomena (e.g., words and syntactic structure) co-occur with a wide variety of meanings. These systematic correlations can help readers to interpret a text and create predictions about upcoming material. However, to what extent these correlations influence discourse processing is still unknown. We address this question by examining…
Descriptors: Statistical Analysis, Correlation, Discourse Analysis, Cues
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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
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Dadi Ramesh; Suresh Kumar Sanampudi – European Journal of Education, 2024
Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…
Descriptors: Scoring, Essays, Writing Evaluation, Memory
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Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
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
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Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
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Robert-Mihai Botarleanu; Micah Watanabe; Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Age of Acquisition (AoA) scores approximate the age at which a language speaker fully understands a word's semantic meaning and represent a quantitative measure of the relative difficulty of words in a language. AoA word lists exist across various languages, with English having the most complete lists that capture the largest percentage of the…
Descriptors: Multilingualism, English (Second Language), Second Language Learning, Second Language Instruction
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Li Nguyen; Oliver Mayeux; Zheng Yuan – International Journal of Multilingualism, 2024
Multilingualism presents both a challenge and an opportunity for Natural Language Processing, with code-switching representing a particularly interesting problem for computational models trained on monolingual datasets. In this paper, we explore how code-switched data affects the task of Machine Translation, a task which only recently has started…
Descriptors: Code Switching (Language), Vietnamese, English (Second Language), Second Language Learning