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Reginald Lucien; Sanghoon Park – TechTrends: Linking Research and Practice to Improve Learning, 2024
The purpose of this study was to share the design and development case of Advising Virtual Assistant (AVA), a chatbot created to provide support in academic advising in higher education. By analyzing participants' usage data and chatbot performance, we attempted to understand how students engage with AVA to fulfill their advising needs. AVA…
Descriptors: Artificial Intelligence, Academic Advising, College Students, Program Effectiveness
Abdul Ghaffar; Irfan Ud Din; Asadullah Tariq; Mohammad Haseeb Zafar – Review of Education, 2025
University Examination Timetabling Problem is the most important combinational problem to develop a conflict-free timetable to execute all of the exams in and with the limited timeslots and other resources for universities, colleges or schools. It is also an important Nondeterministic Polynomial Time (NP)-hard problem that has no deterministic…
Descriptors: Artificial Intelligence, Universities, Tests, Student Evaluation
Sefa Emre Öncü; Merve Gevher; Erdem Erdogdu – Journal of Educational Technology and Online Learning, 2025
This study addresses the applicability of generative artificial intelligence (GenAI) within the administrative learner support services at Anadolu University Open Education System, a giga university with more than one million learners in Türkiye. The study reveals the performance differences between a rule-based chatbot and different GenAI-based…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, College Students
Seyma Çaglar-Özhan; Perihan Tekeli; Selay Arkün-Kocadere – Journal of Computer Assisted Learning, 2025
Background: Feedback is an essential part of the educational process as it enriches students' learning experiences, provides information about their current performance, shows them what is lacking in achieving goals, and provides guidance on the strategies needed to achieve those goals. Teachers, especially in crowded classrooms, often have…
Descriptors: Feedback (Response), Artificial Intelligence, Teacher Role, Technology Uses in Education
Andreas Haraldsrud; Tor Ole B. Odden – Journal of Chemical Education, 2025
Chemistry education researchers have, for many years, explored different ways of learning chemistry through modeling and open-ended problem-solving. With the emergence of generative artificial intelligence (GenAI) tools such as ChatGPT, students now have access to dynamic scaffolds that can potentially support them in modeling. However, we still…
Descriptors: Chemistry, Science Education, College Students, College Science
Aklilu Mandefro Messele – Discover Education, 2025
Science, Technology, Engineering, and Mathematics (STEM) education spans all levels, from preschool to postgraduate studies, fostering growth in social, cognitive, and psychomotor skills. In Ethiopia, the aim of STEM education is to cultivate engineers and scientists who can drive economic competitiveness on a global scale. Understanding and…
Descriptors: Foreign Countries, STEM Education, Artificial Intelligence, Technology Uses in Education
Safaa M. Abdelhalim; Raniya Abdullah Alsehibany – Language Learning & Technology, 2025
Grounded in Vygotsky's sociocultural theory, this study examines the effectiveness of integrating ChatGPT into classroom instruction to enhance vocabulary learning. It evaluates ChatGPT's impact on vocabulary knowledge and retention compared to traditional teacher-led instruction. Using a quasi-experimental pre- and posttest control group design…
Descriptors: Artificial Intelligence, Technology Uses in Education, Vocabulary Development, Second Language Instruction
Blasius Erik Sibarani – Turkish Online Journal of Distance Education, 2025
As a result of the COVID-19 pandemic, the approach to learning in education has transitioned from traditional to online (distance learning). It is undeniable that distance education has become a new approach to learning. In the past decade, many institutions have offered distance learning approaches. However, the effectiveness of distance…
Descriptors: Artificial Intelligence, Distance Education, Learner Engagement, Program Effectiveness
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
Abrar H. Alsofyani; Amal M. Barzanji – Journal of Educational Computing Research, 2025
Corrective feedback plays a critical role in enhancing writing skills among English as a Foreign Language (EFL) learners, but large class sizes often hinder the provision of personalized feedback. Generative AI tools such as ChatGPT have emerged as promising solutions that offer immediate and individualized feedback for writing. This study…
Descriptors: Feedback (Response), Artificial Intelligence, English (Second Language), Second Language Learning
Cunyuan Yang; Jiabin Shen; Zhe Qian – Journal of Baltic Science Education, 2025
This study explores the effects of embedding Socio-Scientific Issues (SSI) into vocational design education on students' ethics awareness, social responsibility, and design performance. A mixed-methods quasi-experimental design was employed, involving 80 vocational design students divided into an experimental group (SSI-based workshop) and a…
Descriptors: Career and Technical Education, Design, Ethics, Social Responsibility
Hao-Chiang Koong Lin; Chun-Hsiung Tseng; Nian-Shing Chen – Educational Technology & Society, 2025
In recent years, learning programming has been a challenge for both learners and educators. How to enhance student engagement and learning outcomes has been a significant concern for researchers. This study examines the effects of AI-based pedagogical agents on students' learning experiences in programming courses, focusing on web game development…
Descriptors: Programming, Learner Engagement, Self Efficacy, Artificial Intelligence
Kamila Misiejuk; Jarle Bastesen; Tatiana Ershova – Innovations in Education and Teaching International, 2025
In this study, we explore the effects of self-reported or suspected generative artificial intelligence (GenAI) use in essay writing on peer assessment and revision patterns among a group of early student adopters. The data were collected from a higher education course, where students engaged in a group peer assessment activity, and analysed using…
Descriptors: Artificial Intelligence, Essays, Writing (Composition), Peer Evaluation
Qian Xu – Discover Education, 2024
This research suggests a methodology to examine the effectiveness Artificial Intelligence (AI) on the cognitive abilities of college students so that future researchers can utilize this experimental project to focus on how AI-powered Intelligent Tutoring Systems (ITSs) affect learning outcomes. As AI continues to revolutionize all walks of life,…
Descriptors: Artificial Intelligence, Cognitive Ability, College Students, Intelligent Tutoring Systems
Yu-Ju Lan; Scott Grant; Hui-Chin Yeh – Educational Technology & Society, 2025
This study investigated the use of virtual chatbots in a 3D multi-user virtual environment (3D MUVE) to enhance the communication skills of Chinese as a foreign language (CFL) learners. Several virtual chat agents, developed using pattern matching techniques and embedded in Second Life, created a blended learning environment in which CFL learners…
Descriptors: Artificial Intelligence, Communication Skills, Educational Technology, Technology Uses in Education

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