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Wu Xu; Zhang Wei; Peng Yan – European Journal of Education, 2025
This study investigates the use of Large Language Models (LLMs) by undergraduates majoring in Instrumentation and Control Engineering (ICE) at University of Shanghai for Science and Technology. We conducted a questionnaire survey to assess the awareness and usage habits of these LLMs among ICE undergraduates in ICE courses, focusing on the model…
Descriptors: Artificial Intelligence, Natural Language Processing, Engineering Education, Majors (Students)
Thanh Pham; Binh Nguyen; Son Ha; Thanh Nguyen Ngoc – Australasian Journal of Educational Technology, 2023
This research explored the potential of artificial intelligence (AI)-assisted learning using ChatGPT in an engineering course at a university in South-east Asia. The study investigated the benefits and challenges that students may encounter when utilising ChatGPT-3.5 as a learning tool. This research developed an AI-assisted learning flow that…
Descriptors: Artificial Intelligence, Engineering Education, Universities, Foreign Countries
Mohammad Islam Biswas; Md. Shamim Talukder; Yasheng Chen – International Journal of Educational Management, 2025
Purpose: The adoption and usage of generative artificial intelligence tools like Chat Generative Pre-Trained Transformer (ChatGPT) in academia is the subject of increasing research interest. This study investigates the factors influencing the intention, usage and recommendation of ChatGPT among university students by employing the…
Descriptors: Intention, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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
Dave Kim; Aref Majdara; Wendy Olson – International Journal of Technology in Education, 2024
This exploratory study focuses on the use of ChatGPT, a generative artificial intelligence (GAI) tool, by undergraduate engineering students in lab report writing in the major. Literature addressing the impact of ChatGPT and AI on student writing suggests that such technologies can both support and limit students' composing and learning processes.…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Science Laboratories
Fabian Kieser; Peter Wulff; Jochen Kuhn; Stefan Küchemann – Physical Review Physics Education Research, 2023
Generative AI technologies such as large language models show novel potential to enhance educational research. For example, generative large language models were shown to be capable of solving quantitative reasoning tasks in physics and concept tests such as the Force Concept Inventory (FCI). Given the importance of such concept inventories for…
Descriptors: Physics, Science Instruction, Artificial Intelligence, Computer Software
Menekse, Muhsin – Journal of Experimental Education, 2020
This study addressed the role of the reflection-informed learning and instruction (RILI) model on students' academic success by using CourseMIRROR mobile system. We hypothesized that prompting students to reflect on confusing concepts stimulates their self-monitoring activities according to which students are expected to review their…
Descriptors: Reflection, Academic Achievement, Undergraduate Students, Instructional Effectiveness
Menekse, Muhsin – Grantee Submission, 2020
This study addressed the role of the reflection-informed learning and instruction (RILI) model on students' academic success by using CourseMIRROR mobile system. We hypothesized that prompting students to reflect on confusing concepts stimulates their self-monitoring activities according to which students are expected to review their…
Descriptors: Reflection, Academic Achievement, Undergraduate Students, Instructional Effectiveness