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Giovanni Zimotti; Claire Frances; Luke Whitaker – Technology in Language Teaching & Learning, 2024
This study explores the perceptions of second language (L2) educators on the surge of Large Language Models (LLMs) like ChatGPT, and their potential impact on language education. We surveyed over 100 L2 instructors, asking questions about their ideas for AI-proofing assignments, their policies, and their perceptions of how this tool will impact…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Second Language Instruction
Murat Demirkol; Nedim Malkoc – Educational Process: International Journal, 2023
Background/purpose: The unprecedented developments in AI-based technologies and large language models such as ChatGPT have exhibited a brand-new territory to be explored. Since its first release in November 2022, the potential utility of ChatGPT has garnered incremental attention in the scientific world, and has already accumulated a great number…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Educational Research
Cheryl P. Stewart – ProQuest LLC, 2023
Purpose: This study will evaluate the organizational effectiveness of an artificial intelligence (AI)/machine learning (ML) recommender system at a higher education institution. It will determine the positive or negative net benefits (i.e., organizational effectiveness) of utilizing the D&M ISSM. Background: Identifying the value and efficacy…
Descriptors: Two Year College Students, Artificial Intelligence, Organizational Effectiveness, Information Systems
Shayan Doroudi – Journal of the Learning Sciences, 2023
When the Learning Sciences emerged in 1991, there was an ethos of studying learning in humans and machines in conjunction with one another. This ethos reflected three decades of prior work on the interdisciplinary study of learning; however, in the three decades since the emergence of the Learning Sciences, it seems to have largely disappeared. I…
Descriptors: Interdisciplinary Approach, Educational Research, Man Machine Systems, Learning Processes
James Lamb; Tim Fawns; Joe Noteboom; Jen Ross – Higher Education Research and Development, 2025
Ideas of space within higher education are changing, influenced by pedagogical innovation, emerging technologies, and the experiences of the COVID-19 pandemic. This is most obvious in the expansion of hybrid education, where teaching happens simultaneously both online and on the physical campus. Hybrid learning spaces emerge from dynamic,…
Descriptors: Foreign Countries, Graduate Students, College Faculty, Blended Learning
Sokratis Tselegkaridis; Theodosios Sapounidis; Christos Tokatlidis; Dimitrios Papakostas – IEEE Transactions on Education, 2025
Contribution: This study focuses on microcontroller circuits and aims to: 1) investigate the impact of formal reasoning on students' post-knowledge using catastrophe theory; 2) compare the different combination sequences of tangible user interface (TUI) and graphical user interface (GUI); and 3) assess the usability of both interfaces and explore…
Descriptors: College Students, Electronics, Electronic Equipment, Engineering Education
Xiaoyan Chu; Minjuan Wang; Jonathan Michael Spector; Nian-Shing Chen; Ching Sing Chai; Gwo-Jen Hwang; Xuesong Zhai – Educational Technology Research and Development, 2025
The Flipped Classroom Model (FCM) has gained widespread acceptance in higher education as an effective pedagogical strategy. Despite its success, the FCM still faces persistent concerns, including a lack of personalized interaction, limited application to introductory courses, and insufficient analysis of the learning process. The integration of…
Descriptors: Flipped Classroom, Artificial Intelligence, Technology Uses in Education, Educational Technology
Zhai, Xiaoming; Shi, Lehong; Nehm, Ross H. – Journal of Science Education and Technology, 2021
Machine learning (ML) has been increasingly employed in science assessment to facilitate automatic scoring efforts, although with varying degrees of success (i.e., magnitudes of machine-human score agreements [MHAs]). Little work has empirically examined the factors that impact MHA disparities in this growing field, thus constraining the…
Descriptors: Meta Analysis, Man Machine Systems, Artificial Intelligence, Computer Assisted Testing
Seyum Getenet – International Electronic Journal of Mathematics Education, 2024
This study compared the problem-solving abilities of ChatGPT and 58 pre-service teachers (PSTs) in solving a mathematical word problem using various strategies. PSTs were asked to solve a problem individually. Data was collected from PSTs' submitted assignments, and their problem-solving strategies were analyzed. ChatGPT was also given the same…
Descriptors: Problem Solving, Ability, Preservice Teachers, Artificial Intelligence
Yifan Zhang – ProQuest LLC, 2024
Computational thinking (CT) has been an increasing focus of research and practice since the seminal paper by Wing in 2006, especially in pre-college (K-12) education. Barr and Stephenson defined CT as a problem-solving methodology that can be automated, transferred, and applied across disciplines. With the challenges of fitting CT into already…
Descriptors: Mental Computation, Elementary Education, Problem Solving, Intellectual Disciplines
Mark E. Pickering; Ryan Jopp; Melissa A. Wheeler; Cheree Topple – Australasian Journal of Educational Technology, 2024
Advances in technology have significantly enhanced the quality of mixed-reality simulations, incorporating both real and virtual aspects. Mixed-reality simulations have been used to develop individual knowledge, skills and abilities in higher education; however, the use of such simulations to introduce authentic learning activities into higher…
Descriptors: Foreign Countries, Undergraduate Students, Business Administration Education, Computer Simulation
Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
Irene Picton; Christina Clark – National Literacy Trust, 2024
Recent developments in technology have accelerated the influence of artificial intelligence (AI) on our lives. The ability of generative-AI tools such as ChatGPT, Gemini and Claude to both 'write' (generate new texts) and 'read' (e.g. summarise texts) in a human-like manner means they are set to play an increasingly important role in the literacy…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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
Tang Minh Dung; Vo Khoi Nguyen; Ðoàn Cao Minh Trí; Phú Lúóng Chí Quõc; Bui Hoang Dieu Ban – Canadian Journal of Learning and Technology, 2024
The rapid rise of artificial intelligence (AI), exemplified by ChatGPT, has transformed education. However, few studies have examined the factors influencing its adoption in higher education, especially among Mathematics student teachers. This study investigates factors that influence the behavioural intentions of Mathematics student teachers…
Descriptors: Mathematics Teachers, Intention, Artificial Intelligence, Man Machine Systems

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