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Liu, Mingya; Barthel, Mathias – Journal of Psycholinguistic Research, 2021
In this paper, the meaning and processing of the German conditional connectives (CCs) such as "wenn" 'if' and "nur wenn" 'only if' are investigated. In Experiment 1, participants read short scenarios containing a conditional sentence (i.e., If P, Q.) with "wenn"/"nur wenn" 'if/only if' and a confirmed or…
Descriptors: German, Language Processing, Psycholinguistics, Morphemes
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Lee, Eun-Kyung; Lam, Tuan Q.; Watson, Duane G. – Discourse Processes: A Multidisciplinary Journal, 2021
Although it is clear that unaccented referring expressions are associated with given information in a discourse, it is less clear what aspects of givenness are relevant. We examine whether listeners' expectation of givenness depends on repetition of a referring expression or on contextual evocation of a referent. The results from two visual world…
Descriptors: Discourse Analysis, Visual Stimuli, Eye Movements, Listening Comprehension
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Fairchild, Sarah; Papafragou, Anna – Cognitive Science, 2021
In sentences such as "Some dogs are mammals," the literal semantic meaning ("Some 'and possibly all' dogs are mammals") conflicts with the pragmatic meaning ("'Not all' dogs are mammals," known as a "scalar implicature"). Prior work has shown that adults vary widely in the extent to which they adopt the…
Descriptors: Executive Function, Theory of Mind, Semantics, Pragmatics
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Wan, Qian; Crossley, Scott; Banawan, Michelle; Balyan, Renu; Tian, Yu; McNamara, Danielle; Allen, Laura – International Educational Data Mining Society, 2021
The current study explores the ability to predict argumentative claims in structurally-annotated student essays to gain insights into the role of argumentation structure in the quality of persuasive writing. Our annotation scheme specified six types of argumentative components based on the well-established Toulmin's model of argumentation. We…
Descriptors: Essays, Persuasive Discourse, Automation, Identification
Botarleanu, Robert-Mihai; Dascalu, Mihai; Watanabe, Micah; McNamara, Danielle S.; Crossley, Scott Andrew – Grantee Submission, 2021
The ability to objectively quantify the complexity of a text can be a useful indicator of how likely learners of a given level will comprehend it. Before creating more complex models of assessing text difficulty, the basic building block of a text consists of words and, inherently, its overall difficulty is greatly influenced by the complexity of…
Descriptors: Multilingualism, Language Acquisition, Age, Models
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Emiko Tsutsumi; Yiming Guo; Ryo Kinoshita; Maomi Ueno – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines item response theory (IRT) with a deep learning method, provides superior performance. It can express the abilities of each student…
Descriptors: Item Response Theory, Academic Ability, Intelligent Tutoring Systems, Artificial Intelligence
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Aurélia Nana Gassa Gonga; Onno Crasborn; Ellen Ormel – International Journal of Multilingualism, 2024
In simultaneous interpreting studies, the concept of interference -- namely, the marks of the source language in the target language -- is perceived as a negative phenomenon. However, interference is likely to happen at a lexical level when the target language does not have its own lexicon. This is the case in international sign (IS), which can be…
Descriptors: Multilingualism, Linguistic Borrowing, Sign Language, Second Languages
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Heather Johnston; Rebecca F. Wells; Elizabeth M. Shanks; Timothy Boey; Bryony N. Parsons – International Journal for Educational Integrity, 2024
The aim of this project was to understand student perspectives on generative artificial intelligence (GAI) technologies such as Chat generative Pre-Trained Transformer (ChatGPT), in order to inform changes to the University of Liverpool Academic Integrity code of practice. The survey for this study was created by a library student team and vetted…
Descriptors: Artificial Intelligence, Higher Education, Student Attitudes, Universities
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Seyum Getenet – International Electronic Journal of Mathematics Education, 2024
This study compared the problem-solving abilities of ChatGPT and 58 pre-service teachers (PSTs) in solving a mathematical word problem using various strategies. PSTs were asked to solve a problem individually. Data was collected from PSTs' submitted assignments, and their problem-solving strategies were analyzed. ChatGPT was also given the same…
Descriptors: Problem Solving, Ability, Preservice Teachers, Artificial Intelligence
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Erin S. M. Matsuba; Beth A. Prieve; Emily Cary; Devon Pacheco; Angela Madrid; Elizabeth McKernan; Elizabeth Kaplan-Kahn; Natalie Russo – Journal of Autism and Developmental Disorders, 2024
This study characterizes the subcortical auditory brainstem response (speech-ABR) and cortical auditory processing (P1 and Mismatch Negativity; MMN) to speech sounds and their relationship to autistic traits and sensory features within the same group of autistic children (n = 10) matched on age and non-verbal IQ to their typically developing (TD)…
Descriptors: Correlation, Brain Hemisphere Functions, Autism Spectrum Disorders, Language Processing
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Shahid A. Choudhry; Timothy J. Muckle; Christopher J. Gill; Rajat Chadha; Magnus Urosev; Matt Ferris; John C. Preston – Practical Assessment, Research & Evaluation, 2024
The National Board of Certification and Recertification for Nurse Anesthetists (NBCRNA) conducted a one-year research study comparing performance on the traditional continued professional certification assessment, administered at a test center or online with remote proctoring, to a longitudinal assessment that required answering quarterly…
Descriptors: Nurses, Certification, Licensing Examinations (Professions), Computer Assisted Testing
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Yu-Chi Chen; Huei-Tse Hou – Journal of Educational Computing Research, 2024
Technologies like ChatGPT and other AI tools have impacted learning by giving students more chances to ask questions and explore knowledge. The inclusion of Non-Player Characters (NPCs) as scaffolding in game-based situated learning activities can have a positive impact on learning. The application of ChatGPT to role-playing has potential;…
Descriptors: Educational Games, Artificial Intelligence, Natural Language Processing, Scaffolding (Teaching Technique)
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Keith Cochran; Clayton Cohn; Peter Hastings; Noriko Tomuro; Simon Hughes – International Journal of Artificial Intelligence in Education, 2024
To succeed in the information age, students need to learn to communicate their understanding of complex topics effectively. This is reflected in both educational standards and standardized tests. To improve their writing ability for highly structured domains like scientific explanations, students need feedback that accurately reflects the…
Descriptors: Science Process Skills, Scientific Literacy, Scientific Concepts, Concept Formation
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Younglong Kim; Katherine A. Curry; Ashlyn M. Fiegener – Journal of School Administration Research and Development, 2024
Educational leaders are faced with multi-faceted dilemmas that place decision-making at the heart of their day-to-day work. For support, they often turn to collaborative networks of experienced educators, such as Project ECHO, for solutions to address challenges they encounter while working in the field. The availability of generative AI…
Descriptors: Artificial Intelligence, Natural Language Processing, Barriers, Educational Practices
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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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