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Showing all 11 results Save | Export
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Tal Waltzer; Celeste Pilegard; Gail D. Heyman – International Journal for Educational Integrity, 2024
The release of ChatGPT in 2022 has generated extensive speculation about how Artificial Intelligence (AI) will impact the capacity of institutions for higher learning to achieve their central missions of promoting learning and certifying knowledge. Our main questions were whether people could identify AI-generated text and whether factors such as…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, College Students
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Gary Lieberman – Journal of Instructional Research, 2024
Artificial intelligence (AI) first made its entry into higher education in the form of paraphrasing tools. These tools were used to take passages that were copied from sources, and through various methods, disguised the original text to avoid academic integrity violations. At first, these tools were not very good and produced nearly…
Descriptors: Artificial Intelligence, Higher Education, Integrity, Ethics
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Sanchez-Ferreres, Josep; Delicado, Luis; Andaloussi, Amine Abbab; Burattin, Andrea; Calderon-Ruiz, Guillermo; Weber, Barbara; Carmona, Josep; Padro, Lluis – IEEE Transactions on Learning Technologies, 2020
The creation of a process model is primarily a formalization task that faces the challenge of constructing a syntactically correct entity, which accurately reflects the semantics of reality, and is understandable to the model reader. This article proposes a framework called "Model Judge," focused toward the two main actors in the process…
Descriptors: Models, Automation, Validity, Natural Language Processing
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Anna Y. Q. Huang; Jei Wei Chang; Albert C. M. Yang; Hiroaki Ogata; Shun Ting Li; Ruo Xuan Yen; Stephen J. H. Yang – Educational Technology & Society, 2023
To improve students' learning performance through review learning activities, we developed a personalized intervention tutoring approach that leverages learning analysis based on artificial intelligence. The proposed intervention first uses text-processing artificial intelligence technologies, namely bidirectional encoder representations from…
Descriptors: Academic Achievement, Tutoring, Artificial Intelligence, Individualized Instruction
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Lin Xiao; Jianping Zeng – International Education Studies, 2023
Strategic competence, as a meta-cognitive ability, determines the other translation sub-competences. To tease out how students' strategic competence is developed in translation project is significant in enlightening the translation teaching practice. This study explores how five Chinese college students' translation competence, particularly their…
Descriptors: Translation, Teaching Methods, Second Languages, Language Processing
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McHugh, David; Shaw, Sarah; Moore, Travis R.; Ye, Leafia Zi; Romero-Masters, Philip; Halverson, Richard – Journal of Research on Technology in Education, 2020
Using a natural language processing tool, this study examined participant discourse in personalized learning schools to better understand what personalized learning looks like in practice. Term frequency-inverse document frequency (tf-idf) was used to identify the significant words and potential emergent themes for 134 interview transcripts. This…
Descriptors: Natural Language Processing, Discourse Analysis, Word Frequency, Identification
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Wei, Tao; Schnur, Tatiana T. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Processing semantically related stimuli creates interference across various domains of cognition, including language and memory. In this study, we identify the locus and mechanism of interference when retrieving meanings associated with words and pictures. Subjects matched a probe stimulus (e.g., cat) to its associated target picture (e.g., yarn)…
Descriptors: Semantics, Cues, Pictorial Stimuli, Interference (Learning)
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Berent, Iris; Lennertz, Tracy – Journal of Experimental Psychology: Human Perception and Performance, 2010
Languages are known to exhibit universal restrictions on sound structure. The source of such restrictions, however, is contentious: Do they reflect abstract phonological knowledge, or properties of linguistic experience and auditory perception? We address this question by investigating the restrictions on onset structure. Across languages, onsets…
Descriptors: Phonology, Auditory Perception, Acoustics, Language Processing
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Burt, Jennifer S. – Journal of Memory and Language, 2009
University students participated in five experiments concerning the effects of unmasked, orthographically similar, primes on visual word recognition in the lexical decision task (LDT) and naming tasks. The modal prime-target stimulus onset asynchrony (SOA) was 350 ms. When primes were words that were orthographic neighbors of the targets, and…
Descriptors: Word Recognition, College Students, Experiments, Task Analysis
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Yang, Yu-Fen; Wong, Wing-Kwong; Yeh, Hui-Chin – Computers & Education, 2009
Referential identification and resolution are considered the keys to help readers grasp the main idea of a text and solve lexical ambiguities. The goal of this study is to design a computer system for helping college students who learn English as a Foreign Language (EFL) develop mental maps of referential identification and resolution in reading.…
Descriptors: English (Second Language), Second Language Instruction, Knowledge Representation, Concept Mapping
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers