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Nuangchalerm, Prasart; Prachagool, Veena – Online Submission, 2023
In recent years, the integration approach of Artificial Intelligence (AI) is called for many disciplines, it also STEM education has paved the way for transformative advancements. This paper provides an example of AI-driven learning analytics within the context of STEM education. It provides a thorough analysis of the AI-driven STEM curriculum and…
Descriptors: Artificial Intelligence, Learning Analytics, STEM Education, Technology Uses in Education
Ley, Tobias; Tammets, Kairit; Pishtari, Gerti; Chejara, Pankaj; Kasepalu, Reet; Khalil, Mohammad; Saar, Merike; Tuvi, Iiris; Väljataga, Terje; Wasson, Barbara – Journal of Computer Assisted Learning, 2023
Background: With increased use of artificial intelligence in the classroom, there is now a need to better understand the complementarity of intelligent learning technology and teachers to produce effective instruction. Objective: The paper reviews the current research on intelligent learning technology designed to make models of student learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Learning Analytics, Instructional Effectiveness
O. Trevisan; R. Christensen; K. Drossel; S. Friesen; A. Forkosh-Baruch; M. Phillips – Technology, Knowledge and Learning, 2024
In an era marked by the widespread use of digital technology, educators face the need to constantly learn and develop their own new literacies for the information era, as well as their competencies to teach and apply best practices using technologies. This paper underscores the vital role of ongoing teacher professional learning (OTPL) with a…
Descriptors: Educational Technology, Technology Uses in Education, Faculty Development, Reflective Teaching
Kasra Lekan; Zachary A. Pardos – Journal of Learning Analytics, 2025
Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major selection using a large language model (LLM), GPT-4. Through a three-phase survey, we compare GPT suggestions and responses for undeclared first- and second-year students…
Descriptors: Technology Uses in Education, Artificial Intelligence, Academic Advising, Majors (Students)
Ayse Alkan – International Journal of Technology in Education and Science, 2024
Artificial intelligence (AI) based education represents a significant transformation in the field of education of our age. Artificial intelligence (AI) technology has great potential to enrich the learning experience of special needs students, provide support to teachers, and reduce inequalities in education. Artificial intelligence (AI)…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Students with Disabilities
Paul Prinsloo; Mohammad Khalil; Sharon Slade – British Journal of Educational Technology, 2024
Students' physical and digital lives are increasingly entangled. It is difficult to separate students' "digital" well-being from their offline well-being given that artificial intelligence increasingly shapes both. Within the context of education's fiduciary and moral duty to ensure safe, appropriate and effective digital learning spaces…
Descriptors: Educational Technology, Technology Uses in Education, Well Being, Artificial Intelligence
Wongvorachan, Tarid; Lai, Ka Wing; Bulut, Okan; Tsai, Yi-Shan; Chen, Guanliang – Journal of Applied Testing Technology, 2022
Feedback is a crucial component of student learning. As advancements in technology have enabled the adoption of digital learning environments with assessment capabilities, the frequency, delivery format, and timeliness of feedback derived from educational assessments have also changed progressively. Advanced technologies powered by Artificial…
Descriptors: Artificial Intelligence, Feedback (Response), Learning Analytics, Natural Language Processing
Stanislav Pozdniakov; Jonathan Brazil; Mehrnoush Mohammadi; Mollie Dollinger; Shazia Sadiq; Hassan Khosravi – Journal of Learning Analytics, 2025
Engaging students in creating high-quality novel content, such as educational resources, promotes deep and higher-order learning. However, students often lack the necessary training or knowledge to produce such content. To address this gap, this paper explores the potential of incorporating generative AI (GenAI) to review students' work and…
Descriptors: Student Evaluation, Artificial Intelligence, Student Developed Materials, Feedback (Response)
Bruce Parsons; John H. Curry – TechTrends: Linking Research and Practice to Improve Learning, 2024
This article investigates an artificial intelligence language model, ChatGPT, and its ability to complete graduate-level instructional design assignments. The approach subjected ChatGPT to a needs, task, and learner analysis for a 12th-grade media literacy module and benchmarked its performance by expert evaluation and measurements via grading…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Instructional Design
Li, Kam Cheong; Wong, Billy Tak-Ming – Interactive Technology and Smart Education, 2023
Purpose: This paper aims to present a comprehensive overview of the patterns and trends of publications on artificial intelligence (AI) in personalised learning. It addresses the need to investigate the intellectual structure and development of this area in view of the growing amount of related research and practices. Design/methodology/approach:…
Descriptors: Artificial Intelligence, Individualized Instruction, Technology Uses in Education, Bibliometrics
Umar Bin Qushem; Solomon Sunday Oyelere; Gökhan Akçapinar; Rogers Kaliisa; Mikko-Jussi Laakso – Technology, Knowledge and Learning, 2024
Predicting academic performance for students majoring in computer science has long been a significant field of research in computing education. Previous studies described that accurate prediction of students' early-stage performance could identify low-performing students and take corrective action to improve performance. Besides, adopting machine…
Descriptors: Predictor Variables, Learning Analytics, At Risk Students, Computer Science
Inclusive Learning Using Industry 4.0 Technologies: Addressing Student Diversity in Modern Education
Ishteyaaq Ahmad; Sonal Sharma; Rajesh Singh; Anita Gehlot; Lovi Raj Gupta; Amit Kumar Thakur; Neeraj Priyadarshi; Bhekisipho Twala – Cogent Education, 2024
This study explores the potential benefits of integrating Industry 4.0 technologies into educational settings, focusing on Artificial Intelligence/Machine Learning, Augmented Reality, Big Data, Blockchain, Cloud Computing, Internet of Things, Metaverse, Robotics, and Virtual Reality. The aim is to develop learning environments that are more…
Descriptors: Student Diversity, Inclusion, Technology Uses in Education, Educational Technology
Ling Wang; Shen Zhan – Education Research and Perspectives, 2024
Generative Artificial Intelligence (GenAI) is transforming education, with assessment design emerging as a crucial area of innovation, particularly in computer science (CS) education. Effective assessment is critical for evaluating student competencies and guiding learning processes, yet traditional practices face significant challenges in CS…
Descriptors: Artificial Intelligence, Computer Science Education, Technology Uses in Education, Student Evaluation
Taylor, Kevin – Education and Culture, 2022
For Dewey, growth in the educative process means education that enriches and expands one's experience as it prepares students for not only a vocation but also entry into and transaction with the world. In few places can we see growth, generally understood, to be occurring as fast as in big data technology. This essay begins with an overview of…
Descriptors: Educational Philosophy, Educational Development, Technology Uses in Education, Learning Analytics
Unggi Lee; Ariel Han; Jeongjin Lee; Eunseo Lee; Jiwon Kim; Hyeoncheol Kim; Cheolil Lim – Education and Information Technologies, 2024
The rapid advancements in artificial intelligence (AI) have transformed various domains, including education. Generative AI models have garnered significant attention for their potential in educational settings, but image-generative AI models need to be more utilized. This study explores the potential of integrating generative AI, specifically…
Descriptors: Artificial Intelligence, Art Education, STEM Education, Learning Analytics