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Jose Berengueres – Discover Education, 2025
GPT-based models have enabled the creation of natural language chatbots that support both Inquiry-Based and Structured Learning approaches. This study offers a direct comparison of these two paradigms within a UNIX Shell scripting course by means of two chatbots: a Lesson Plan-Driven chatbot that ensures all students cover the same topics…
Descriptors: Lesson Plans, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
Andreea Dutulescu; Stefan Ruseti; Denis Iorga; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
The process of generating challenging and appropriate distractors for multiple-choice questions is a complex and time-consuming task. Existing methods for an automated generation have limitations in proposing challenging distractors, or they fail to effectively filter out incorrect choices that closely resemble the correct answer, share synonymous…
Descriptors: Multiple Choice Tests, Artificial Intelligence, Attention, Natural Language Processing
Nezihe Korkmaz Guler; Zeynep Gul Dertli; Elif Boran; Bahadir Yildiz – Pedagogical Research, 2024
The aim of the research is to investigate the academic achievement of ChatGPT, an artificial intelligence based chatbot, in a national mathematics exam. For this purpose, 3.5 and 4 versions of ChatGPT were asked mathematics questions in a national exam. The method of the research is a case study. In the research, 3.5 and 4 versions of ChatGPT were…
Descriptors: Mathematics Education, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Moira Newton; Rebecca Jesson; Judy Parr – Australian Journal of Language and Literacy, 2023
Children's increasing expertise in composition relies partly on word choice. Little is known about how children consider words as they write, their meta-lexical awareness, or about their choice of words for writing. In this study, we investigate children's meta-lexical awareness, as one aspect of their metalinguistic awareness, which guides their…
Descriptors: Metalinguistics, Writing (Composition), Vocabulary Skills, Writing Achievement
Stephen Kintz; Hana Kim; Heather Harris Wright – International Journal of Language & Communication Disorders, 2024
Background: Core lexicon (CL) analysis is a time efficient and possibly reliable measure that captures discourse production abilities. For people with aphasia, CL scores have demonstrated correlations with aphasia severity, as well as other discourse and linguistic measures. It was also found to be clinician-friendly and clinically sensitive…
Descriptors: Vocabulary Skills, Dementia, Measures (Individuals), Language Skills
Qiao, Chen; Hu, Xiao – IEEE Transactions on Learning Technologies, 2023
Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a "black box"…
Descriptors: Computer Assisted Testing, Automation, Test Items, Semantics
Perlman-Arrow, Sara; Loo, Noel; Bobrovitz, Niklas; Yan, Tingting; Arora, Rahul K. – Research Synthesis Methods, 2023
The laborious and time-consuming nature of systematic review production hinders the dissemination of up-to-date evidence synthesis. Well-performing natural language processing (NLP) tools for systematic reviews have been developed, showing promise to improve efficiency. However, the feasibility and value of these technologies have not been…
Descriptors: Natural Language Processing, Screening Tests, COVID-19, Pandemics
Ibnatul Jalilah Yusof – Journal of Information Technology Education: Research, 2025
Aim/Purpose: This paper examines the potential of ChatGPT-assisted retrieval practice to enhance students' final exam performance. ChatGPT was utilized to generate questions and deliver timely feedback during retrieval practice, supporting learning in large class settings where providing personalized feedback is often challenging. Background:…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Scores
Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
Torres-Jimenez, Jose; Lescano, Germán; Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo – Education and Information Technologies, 2023
Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…
Descriptors: Conflict, Identification, Computer Assisted Instruction, Cooperative Learning
Monteiro, Kátia; Crossley, Scott; Botarleanu, Robert-Mihai; Dascalu, Mihai – Language Testing, 2023
Lexical frequency benchmarks have been extensively used to investigate second language (L2) lexical sophistication, especially in language assessment studies. However, indices based on semantic co-occurrence, which may be a better representation of the experience language users have with lexical items, have not been sufficiently tested as…
Descriptors: Second Language Learning, Second Languages, Native Language, Semantics
Düzenli-Öztürk, Seren; Hünerli-Gündüz, Duygu; Emek-Savas, Derya Durusu; Olichney, John; Yener, Görsev G.; Ergenç, H. Iclal – Journal of Psycholinguistic Research, 2022
Semantic priming in Turkish was examined in 36 right-handed healthy participants in a delayed lexical decision task via taxonomic relations using EEG. Prime--target relations included related- unrelated- and pseudo-words. Taxonomically related words at long stimulus onset asynchrony (SOA) were shown to modulate N400 and late positive component…
Descriptors: Taxonomy, Semantics, Priming, Turkish
Li, Wei; Rohde, Hannah; Corley, Martin – Journal of Autism and Developmental Disorders, 2022
How do we decide whether a statement is literally true? Here, we contrast participants' eventual evaluations of a speaker's meaning with the real-time processes of comprehension. We record participants' eye movements as they respond to potentially misleading instructions to click on one of two objects which might be concealing treasure ("the…
Descriptors: Autism Spectrum Disorders, Deception, Cognitive Processes, Scores
YiHsuan Wood; Jeffrey J. Green; Ellen Knell; Yu Liu – Language Awareness, 2025
This study used eye-tracking to investigate the real-time processing of phonetic and semantic radicals (components of Chinese characters that give clues to their pronunciation and meaning) by intermediate-level university Chinese foreign language (CFL) learners. Additionally, the study examined how knowledge and awareness of radicals affect…
Descriptors: Eye Movements, Chinese, Second Language Learning, Second Language Instruction
Dan Song; Alexander F. Tang – Language Learning & Technology, 2025
While many studies have addressed the benefits of technology-assisted L2 writing, limited research has delved into how generative artificial intelligence (GAI) supports students in completing their writing tasks in Mandarin Chinese. In this study, 26 university-level Mandarin Chinese foreign language students completed two writing tasks on two…
Descriptors: Artificial Intelligence, Second Language Learning, Standardized Tests, Writing Tests