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Irene Picton; Christina Clark – National Literacy Trust, 2024
Recent developments in technology have accelerated the influence of artificial intelligence (AI) on our lives. The National Literacy Trust is interested in exploring how such platforms might influence, and potentially redefine, what it means to be literate in the digital age. Based on data from more than 50,000 children and young people taking…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Victoria Olubola Adeyele; Umesh Ramnarain – International Journal of Technology in Education, 2024
ChatGPT, an AI-powered service known for its effective delivery of information and solutions, has the potential to transform education, scientific problem-solving, and student learning. However, to fully harness its advantages, understanding the pedagogical approach needed is essential. This study explores teachers' awareness of ChatGPT and the…
Descriptors: Technology Integration, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Areej ElSayary – Journal of Computer Assisted Learning, 2024
Background: The widespread use of information and communication technology (ICT) has led to significant changes in societal aspects, resulting in the emergence of a "knowledge society." However, students and teachers have faced challenges in adapting to this digitalization. In the United Arab Emirates (UAE), transitioning to a…
Descriptors: Teacher Attitudes, Artificial Intelligence, Information Technology, Barriers
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Ghadeer Sawalha; Imran Taj; Abdulhadi Shoufan – Cogent Education, 2024
Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link…
Descriptors: Cues, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Surya Bahadur G. C.; Pooja Bhandari; Santosh Kumar Gurung; Ekta Srivastava; Deepak Ojha; Bharat Ram Dhungana – Cogent Education, 2024
This study examined factors influencing students' intention to use ChatGPT using UTAUT2 model. The cross-sectional study is based on responses collected from 578 students selected through convenience sampling at a university in Nepal through a structured questionnaire. Using PLS-SEM, the study found that habit ([beta] = 0.315, p < 0.001),…
Descriptors: Social Influences, Value Judgment, Habit Formation, Intention
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Fengkai Liu; Yishi Jiang; Chun Lai; Tan Jin – Language Learning & Technology, 2024
Differentiated instruction is much demanded yet quite challenging in face of the growing student diversity in today's K-12 classrooms. One major challenge is the provision of differentiated materials to students. Automated text simplification (ATS) tools fueled by natural language processing may serve as a useful assistant for teachers. However,…
Descriptors: Automation, Individualized Instruction, Natural Language Processing, Technology Uses in Education
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Colin Green; Eric Brewe; Jillian Mellen; Adrienne Traxler; Sarah Scanlin – Physical Review Physics Education Research, 2024
This project aims to understand physics faculty responses to transitioning to online teaching during the COVID-19 pandemic. We surveyed 662 physics faculty from the United States following the Spring 2020 term; of these, 258 completed a follow-up survey after the Fall 2020 term. We used natural language processing to measure the sentiment scores…
Descriptors: Teacher Attitudes, Online Courses, Physics, Science Instruction
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Haerim Hwang; Hyunwoo Kim – Language Testing, 2024
Given the lack of computational tools available for assessing second language (L2) production in Korean, this study introduces a novel automated tool called the Korean Syntactic Complexity Analyzer (KOSCA) for measuring syntactic complexity in L2 Korean production. As an open-source graphic user interface (GUI) developed in Python, KOSCA provides…
Descriptors: Korean, Natural Language Processing, Syntax, Computer Graphics
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Robert-Mihai Botarleanu; Micah Watanabe; Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Age of Acquisition (AoA) scores approximate the age at which a language speaker fully understands a word's semantic meaning and represent a quantitative measure of the relative difficulty of words in a language. AoA word lists exist across various languages, with English having the most complete lists that capture the largest percentage of the…
Descriptors: Multilingualism, English (Second Language), Second Language Learning, Second Language Instruction
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Osama Koraishi – Language Teaching Research Quarterly, 2024
This study conducts a comprehensive quantitative evaluation of OpenAI's language model, ChatGPT 4, for grading Task 2 writing of the IELTS exam. The objective is to assess the alignment between ChatGPT's grading and that of official human raters. The analysis encompassed a multifaceted approach, including a comparison of means and reliability…
Descriptors: Second Language Learning, English (Second Language), Language Tests, Artificial Intelligence
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Xiaojing Weng; Qi Xia; Mingyue Gu; Kumaran Rajaram; Thomas K. F. Chiu – Australasian Journal of Educational Technology, 2024
Generative artificial intelligence (GenAI) impacts higher education assessment and learning outcomes, which are closely related and intertwined. Literature suggests that educators and researchers have many varied concerns regarding student assessment in the higher education GenAI context, such as how to assess students' learning and the new…
Descriptors: Evaluation Methods, Outcomes of Education, Artificial Intelligence, Natural Language Processing
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Imre Bende – Acta Didactica Napocensia, 2024
The continuous development of artificial intelligence-based tools makes their emergence inevitable in education as well as other fields of life. This article presents findings of a mixed method study aimed at investigating the current perceptions and potential applications of AI in Hungarian educational settings. Through interviews with high…
Descriptors: Readiness, Artificial Intelligence, Technology Uses in Education, Foreign Countries
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Crossley, Scott A.; Skalicky, Stephen; Dascalu, Mihai – Journal of Research in Reading, 2019
Background: Advances in natural language processing (NLP) and computational linguistics have facilitated major improvements on traditional readability formulas that aim at predicting the overall difficulty of a text. Recent studies have identified several types of linguistic features that are theoretically motivated and predictive of human…
Descriptors: Natural Language Processing, Readability, Reading Comprehension, Reading Rate
Panaite, Marilena; Ruseti, Stefan; Dascalu, Mihai; Balyan, Renu; McNamara, Danielle S.; Trausan-Matu, Stefan – Grantee Submission, 2019
Intelligence Tutoring Systems (ITSs) focus on promoting knowledge acquisition, while providing relevant feedback during students' practice. Self-explanation practice is an effective method used to help students understand complex texts by leveraging comprehension. Our aim is to introduce a deep learning neural model for automatically scoring…
Descriptors: Computer Assisted Testing, Scoring, Intelligent Tutoring Systems, Natural Language Processing
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Baral, Sami; Botelho, Anthony; Santhanam, Abhishek; Gurung, Ashish; Cheng, Li; Heffernan, Neil – International Educational Data Mining Society, 2023
Teachers often rely on the use of a range of open-ended problems to assess students' understanding of mathematical concepts. Beyond traditional conceptions of student open-ended work, commonly in the form of textual short-answer or essay responses, the use of figures, tables, number lines, graphs, and pictographs are other examples of open-ended…
Descriptors: Mathematics Instruction, Mathematical Concepts, Problem Solving, Test Format
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