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Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
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Schmid, Samuel; Saddy, Douglas; Franck, Julie – Cognitive Science, 2023
In this article, we explore the extraction of recursive nested structure in the processing of binary sequences. Our aim was to determine whether humans learn the higher-order regularities of a highly simplified input where only sequential-order information marks the hierarchical structure. To this end, we implemented a sequence generated by the…
Descriptors: Learning Processes, Sequential Learning, Grammar, Language Processing
Laura K. Allen; Sarah C. Creer; Püren Öncel – Grantee Submission, 2022
As educators turn to technology to supplement classroom instruction, the integration of natural language processing (NLP) into educational technologies is vital for increasing student success. NLP involves the use of computers to analyze and respond to human language, including students' responses to a variety of assignments and tasks. While NLP…
Descriptors: Natural Language Processing, Learning Analytics, Learning Processes, Methods
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Ailís Cournane; Mina Hirzel; Valentine Hacquard – Language Acquisition: A Journal of Developmental Linguistics, 2024
Modals (e.g., "can," "must") vary along two dimensions of meaning: "force" (i.e., possibility or necessity), and "flavor" (i.e., possibilities relative to knowledge [epistemic], goals [teleological], or rules [deontic] …). Comprehension studies show that children struggle with both force and flavor…
Descriptors: Verbs, Language Acquisition, Child Language, Definitions
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Carvalho, Floran; Henriet, Julien; Greffier, Francoise; Betbeder, Marie-Laure; Leon-Henri, Dana – Journal of Education and e-Learning Research, 2023
This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this…
Descriptors: Learning Processes, Algorithms, Artificial Intelligence, Programming Languages
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Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
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Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
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Sarah Berger; Laura J. Batterink – Developmental Science, 2024
Children achieve better long-term language outcomes than adults. However, it remains unclear whether children actually learn language "more quickly" than adults during real-time exposure to input--indicative of true superior language learning abilities--or whether this advantage stems from other factors. To examine this issue, we…
Descriptors: Child Language, Language Acquisition, Learning Processes, Language Skills
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Linda Espey; Marta Ghio; Christian Bellebaum; Laura Bechtold – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
We used a novel linguistic training paradigm to investigate the experience-dependent acquisition, representation, and processing of novel emotional and neutral abstract concepts. Participants engaged in mental imagery (n = 32) or lexico-semantic rephrasing (n = 34) of linguistic material during five training sessions and successfully learned the…
Descriptors: Linguistic Input, Concept Teaching, Concept Formation, Learning Processes
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Sebastian Hobert; Florian Berens – Educational Technology Research and Development, 2024
Individualized learning support is an essential part of formal educational learning processes. However, in typical large-scale educational settings, resource constraints result in limited interaction among students, teaching assistants, and lecturers. Due to this, learning success in those settings may suffer. Inspired by current technological…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Learning Processes, Teaching Methods
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Hinano Iida; Kimi Akita – Cognitive Science, 2024
Iconicity is a relationship of resemblance between the form and meaning of a sign. Compelling evidence from diverse areas of the cognitive sciences suggests that iconicity plays a pivotal role in the processing, memory, learning, and evolution of both spoken and signed language, indicating that iconicity is a general property of language. However,…
Descriptors: Japanese, Cognitive Science, Language Processing, Memory
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Unger, Layla; Yim, Hyungwook; Savic, Olivera; Dennis, Simon; Sloutsky, Vladimir M. – Developmental Science, 2023
Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of…
Descriptors: Natural Language Processing, Language Usage, Vocabulary Development, Linguistic Input
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Nur Basak Karatas; Oya Özemir; Jarrett T. Lovelett; Bora Demir; Kemal Erkol; João Veríssimo; Gülcan Erçetin; Michael T. Ullman – Language Teaching Research, 2025
We investigated whether learning and retaining vocabulary in a second language (L2) can be improved by leveraging a combination of memory enhancement techniques. Specifically, we tested whether combining retrieval practice, spacing, and related manipulations in a 'multidomain' pedagogical approach enhances vocabulary acquisition as compared to a…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Accuracy
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Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
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Aras Bozkurt; Ramesh C. Sharma – Asian Journal of Distance Education, 2024
This study explores the transformative potential of Generative AI (GenAI) and ChatBots in educational interaction, communication, and the broader implications of human-GenAI collaboration. By examining the related literature through data mining and analytical methods, the paper identifies three main research themes: the revolutionary role of…
Descriptors: Algorithms, Artificial Intelligence, Man Machine Systems, Technology Uses in Education
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