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Direct linkNisar 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
Junbin Wang; Chuanbo Zhang – SAGE Open, 2025
This study aims to explore the criteria and success factors for the application of Artificial Intelligence Generated Content (AIGC) in higher education, and guide its practice through the construction of a comprehensive system and framework. This study first identifies seven primary criteria, encompassing technical robustness, integration with…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Higher Education
Dirk H. R. Spennemann; Jessica Biles; Lachlan Brown; Matthew F. Ireland; Laura Longmore; Clare L. Singh; Anthony Wallis; Catherine Ward – Interactive Technology and Smart Education, 2024
Purpose: The use of generative artificial intelligence (genAi) language models such as ChatGPT to write assignment text is well established. This paper aims to assess to what extent genAi can be used to obtain guidance on how to avoid detection when commissioning and submitting contract-written assignments and how workable the offered solutions…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Cheating
Download full textShi Pu; Yu Yan; Brandon Zhang – Journal of Educational Data Mining, 2024
We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…
Descriptors: Prediction, Success, Data Analysis, Learning Analytics
Christopher Dann; Petrea Redmond; Melissa Fanshawe; Alice Brown; Seyum Getenet; Thanveer Shaik; Xiaohui Tao; Linda Galligan; Yan Li – Australasian Journal of Educational Technology, 2024
Making sense of student feedback and engagement is important for informing pedagogical decision-making and broader strategies related to student retention and success in higher education courses. Although learning analytics and other strategies are employed within courses to understand student engagement, the interpretation of data for larger data…
Descriptors: Artificial Intelligence, Learner Engagement, Feedback (Response), Decision Making
Biju Theruvil Sayed; Zein Bassam Bani Younes; Ahmad Alkhayyat; Iroda Adhamova; Habesha Teferi – Language Testing in Asia, 2024
There has been a surge in employing artificial intelligence (AI) in all areas of language pedagogy, not the least among them language testing and assessment. This study investigated the effects of AI-powered tools on English as a Foreign Language (EFL) learners' speaking skills, psychological well-being, autonomy, and academic buoyancy. Using a…
Descriptors: Artificial Intelligence, Language Tests, Success, Speech Skills
