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Kevin Peyton; Saritha Unnikrishnan; Brian Mulligan – Discover Education, 2025
Within the university sector, student recruitment and enrolment are key strategies as institutions strive to attract, retain and engage students. This strategy is underpinned by the provision of services, applications and technologies that facilitate lecturing and support staff. Universities that offer online learning have a particular incentive…
Descriptors: Universities, Artificial Intelligence, Computer Mediated Communication, College Students
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Muylle, Merel; Bernolet, Sarah; Hartsuiker, Robert J. – Language Learning, 2020
Several studies found cross-linguistic structural priming with various language combinations. Here, we investigated the role of two important domains of language variation: case marking and word order, for transitive and ditransitive structures. We varied these features in an artificial language learning paradigm, using three different artificial…
Descriptors: Bilingualism, Priming, Language Processing, Language Variation
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Peel, Hayden J.; Royals, Kayla A.; Chouinard, Philippe A. – Journal of Psycholinguistic Research, 2022
It is widely assumed that subliminal word priming is case insensitive and that a short SOA (< 100 ms) is required to observe any effects. Here we attempted to replicate results from an influential study with the inclusion of a longer SOA to re-examine these assumptions. Participants performed a semantic categorisation task on visible word…
Descriptors: Priming, Psycholinguistics, Reaction Time, Semantics
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Kocab, Annemarie; Davidson, Kathryn; Snedeker, Jesse – Cognitive Science, 2022
Classical quantifiers (like "all," "some," and "none") express relationships between two sets, allowing us to make generalizations (like "no elephants fly"). Devices like these appear to be universal in human languages. Is the ubiquity of quantification due to a universal property of the human mind or is it…
Descriptors: Natural Language Processing, Form Classes (Languages), Cognitive Processes, Spanish
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Kalandadze, Tamara; Braeken, Johan; Brynskov, Cecilia; Naess, Kari-Anne Bottegaard – Journal of Autism and Developmental Disorders, 2022
Poor metaphor comprehension was considered a hallmark of autism spectrum disorder (ASD), but recent research has questioned the extent and the sources of these difficulties. In this cross-sectional study, we compared metaphor comprehension in individuals with ASD (N = 29) and individuals with typical development (TD; N = 31), and investigated the…
Descriptors: Figurative Language, Language Processing, Comprehension, Language Skills
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Brown, Violet A.; Fox, Neal P.; Strand, Julia F. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Listeners make use of contextual cues during continuous speech processing that help overcome the limitations of the acoustic input. These semantic, grammatical, and pragmatic cues facilitate prediction of upcoming words and/or reduce the lexical search space by inhibiting activation of contextually inappropriate words that share phonological…
Descriptors: Cues, Language Processing, Grammar, Sentence Structure
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Bulut, Okan; Yildirim-Erbasli, Seyma Nur – International Journal of Assessment Tools in Education, 2022
Reading comprehension is one of the essential skills for students as they make a transition from learning to read to reading to learn. Over the last decade, the increased use of digital learning materials for promoting literacy skills (e.g., oral fluency and reading comprehension) in K-12 classrooms has been a boon for teachers. However, instant…
Descriptors: Reading Comprehension, Natural Language Processing, Artificial Intelligence, Automation
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Chantavarin, Suphasiree; Morgan, Emily; Ferreira, Fernanda – Cognitive Science, 2022
Prior research has shown that various types of conventional multiword chunks are processed faster than matched novel strings, but it is unclear whether this processing advantage extends to variant multiword chunks that are less formulaic. To determine whether the processing advantage of multiword chunks accommodates variations in the canonical…
Descriptors: Eye Movements, Form Classes (Languages), Cognitive Ability, Language Processing
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Shannag, Fatima; Hammo, Bassam H.; Faris, Hossam – Education and Information Technologies, 2022
Cyberbullying (CB) is classified as one of the severe misconducts on social media. Many CB detection systems have been developed for many natural languages to face this phenomenon. However, Arabic is one of the under-resourced languages suffering from the lack of quality datasets in many computational research areas. This paper discusses the…
Descriptors: Bullying, Computer Mediated Communication, Social Media, Arabic
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Matthew T. McCrudden; Linh Huynh; Bailing Lyu; Jonna M. Kulikowich; Danielle S. McNamara – Grantee Submission, 2024
Readers build a mental representation of text during reading. The coherence building processes readers use to build a mental representation during reading is key to comprehension. We examined the effects of self- explanation on coherence building processes as undergraduates (n =51) read five complementary texts about natural selection and…
Descriptors: Reading Processes, Reading Comprehension, Undergraduate Students, Evolution
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Lixiang Yan; Lele Sha; Linxuan Zhao; Yuheng Li; Roberto Martinez-Maldonado; Guanliang Chen; Xinyu Li; Yueqiao Jin; Dragan Gaševic – British Journal of Educational Technology, 2024
Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…
Descriptors: Educational Technology, Artificial Intelligence, Natural Language Processing, Educational Innovation
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Musa Adekunle Ayanwale; Rethabile Rosemary Molefi – International Journal of Educational Technology in Higher Education, 2024
The increasing prevalence of Fourth Industrial Revolution (4IR) technologies has led to a surge in the popularity of AI application tools, particularly chatbots, in various fields, including education. This research explores the factors influencing undergraduate students' inclination to embrace AI application tools, specifically chatbots, for…
Descriptors: Undergraduate Students, Intention, Student Attitudes, Artificial Intelligence
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Shang Jiang – Journal of Psycholinguistic Research, 2024
It has been well documented that formulaic language (such as collocations; e.g., "provide information") enjoys a processing advantage over novel language (e.g., "compare information"). In natural language use, however, many formulaic sequences are often inserted with words intervening in between the individual constituents…
Descriptors: Phrase Structure, Language Processing, Psycholinguistics, Orthographic Symbols
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Kathryn E. Prescott; Kimberly Crespo; Susan Ellis Weismer – Journal of Autism and Developmental Disorders, 2024
"Purpose:" ASD is associated with relative strengths in the visuospatial domain but varying abilities in the linguistic domain. Previous studies suggest parallels between spatial language and spatial cognition in older autistic individuals, but no research to date has examined this relationship in young autistic children. Therefore, the…
Descriptors: Preschool Children, Autism Spectrum Disorders, Spatial Ability, Cognitive Ability
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Hung Manh Nguyen; Daisaku Goto – Education and Information Technologies, 2024
The proliferation of artificial intelligence (AI) technology has brought both innovative opportunities and unprecedented challenges to the education sector. Although AI makes education more accessible and efficient, the intentional misuse of AI chatbots in facilitating academic cheating has become a growing concern. By using the indirect…
Descriptors: Academic Achievement, Cheating, Student Behavior, Artificial Intelligence
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