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Yuan Chih Fu; Jin Hua Chen; Kai Chieh Cheng; Xuan Fen Yuan – Higher Education: The International Journal of Higher Education Research, 2024
Using data from approximately 342,000 course-taking records collected from 4406 college students enrolled at Taipei Tech during the 2009-2012 academic years, we examine the impact of multidisciplinarity on students' academic performance. Our study contributes to the literature in three ways. First, by applying natural language processing (NLP), we…
Descriptors: College Students, Interdisciplinary Approach, Academic Achievement, Natural Language Processing
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Muhammad Farrukh Shahzad; Shuo Xu; Hira Zahid – Education and Information Technologies, 2025
Artificial Intelligence (AI) technologies have rapidly transformed the education sector and affect student learning performance, particularly in China, a burgeoning educational landscape. The development of generative artificial intelligence (AI) based technologies, such as chatbots and large language models (LLMs) like ChatGPT, has completely…
Descriptors: Artificial Intelligence, Technology Uses in Education, Academic Achievement, Self Efficacy
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Nisar Ahmed Dahri; Noraffandy Yahaya; Waleed Mugahed Al-Rahmi – Education and Information Technologies, 2025
Enhancing student academic success and career readiness is important in the rapidly evolving educational field. This study investigates the influence of ChatGPT, an AI tool, on these outcomes using the Stimulus-Organism-Response (SOR) theory and constructs from the Technology Acceptance Model (TAM). The aim is to explore how ChatGPT impacts…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Career Readiness
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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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Promethi Das Deep; Yixin Chen – Higher Education Studies, 2025
The COVID-19 pandemic significantly disrupted higher education. The sudden and profound transformations it necessitated had a direct and negative impact on higher education students, as evidenced by the widely reported instances of academic disengagement, decreased motivation, and lower performance. This was often due to student burnout caused by…
Descriptors: COVID-19, Pandemics, Electronic Learning, Fatigue (Biology)
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Sha Gao – International Review of Research in Open and Distributed Learning, 2024
Artificial Intelligence (AI), as an innovation in technology, has greatly affected human life. AI applications such as ChatGPT have been used in different fields, particularly education. However, the use of AI applications to enhance undergraduate students' academic emotions and test anxiety has not been appropriately investigated. This study…
Descriptors: Artificial Intelligence, Undergraduate Students, Test Anxiety, Technology Uses in Education
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Clinton Chidiebere Anyanwu; Pauline Ndidi Ononiwu; Grace Ngozi Isiozor – Education and Information Technologies, 2024
In contemporary society, information and communication technology permeates every aspect of human life, including education. This study investigates the impact of WhatsApp chatbot technology and Glaser's teaching approaches on the academic performance of economics education students in tertiary institutions. Grounded in activity theory, the study…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Teaching Methods
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Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
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Fan Ouyang; Tuan Anh Dinh; Weiqi Xu – Journal for STEM Education Research, 2023
Artificial intelligence (AI), as an emerging technology, has been widely used in STEM education to promote the educational assessment. Although AI-driven educational assessment has the potential to assess students' learning automatically and reduce the workload of instructors, there is still a lack of review works to holistically examine the field…
Descriptors: Educational Assessment, Artificial Intelligence, STEM Education, Academic Achievement
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Donald M. Johnson; Will Doss; Christopher M. Estepp – Journal of Research in Technical Careers, 2024
A posttest-only control group experimental design compared novice Arduino programmers who developed their own programs (self-programming group, n = 17) with novice Arduino programmers who used ChatGPT 3.5 to write their programs (ChatGPT-programming group, n = 16) on the dependent variables of programming scores, interest in Arduino programming,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Novices
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Alexandra Farazouli; Teresa Cerratto-Pargman; Klara Bolander-Laksov; Cormac McGrath – Assessment & Evaluation in Higher Education, 2024
AI chatbots have recently fuelled debate regarding education practices in higher education institutions worldwide. Focusing on Generative AI and ChatGPT in particular, our study examines how AI chatbots impact university teachers' assessment practices, exploring teachers' perceptions about how ChatGPT performs in response to home examination…
Descriptors: Artificial Intelligence, Natural Language Processing, Student Evaluation, Educational Change
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Maria Dimeli; Apostolos Kostas – Journal of Information Technology Education: Research, 2025
Aim/Purpose: The purpose of this systematic review is to identify and analyze the current findings of empirical research on the use of ChatGPT in school and higher education. Background: As AI reshapes education, the adoption of ChatGPT has the potential to revolutionize teaching and learning in school and higher educational settings. Meanwhile,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Barriers
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Kochmar, Ekaterina; Vu, Dung Do; Belfer, Robert; Gupta, Varun; Serban, Iulian Vlad; Pineau, Joelle – International Journal of Artificial Intelligence in Education, 2022
Intelligent tutoring systems (ITS) have been shown to be highly effective at promoting learning as compared to other computer-based instructional approaches. However, many ITS rely heavily on expert design and hand-crafted rules. This makes them difficult to build and transfer across domains and limits their potential efficacy. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Automation, Feedback (Response), Dialogs (Language)
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Muhammet Remzi Karaman; I?dris Göksu – International Journal of Technology in Education, 2024
In this research, we aimed to determine whether students' math achievements improved using ChatGPT, one of the chatbot tools, to prepare lesson plans in primary school math courses. The research was conducted with a pretest-posttest control group experimental design. The study comprises 39 third-grade students (experimental group = 24, control…
Descriptors: Artificial Intelligence, Natural Language Processing, Lesson Plans, Instructional Effectiveness
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Raj Sandu; Ergun Gide; Mahmoud Elkhodr – Discover Education, 2024
Artificial intelligence (AI) tools, notably ChatGPT, are increasingly recognised for their transformative potential in higher education. This study employs a detailed case study approach complemented by a survey, delving into ChatGPT's impact on pedagogical practices, student engagement, and academic performance. It involved 74 undergraduate and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Foreign Countries
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