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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
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Imtiaz Ahamed; Afsana Azmari – Journal of Education and Learning, 2025
A crucial aspect of this research is determining the effectiveness of the tool developed for this study. This tool is built upon the understanding that technology continually evolves and significantly impacts higher education. It is believed that technology plays a vital role in how students learn in college today. This belief is supported by the…
Descriptors: Educational Technology, Educational History, Automation, Educational Innovation
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Patrick Bowers; Kelley Graydon; Tracii Ryan; Jey Han Lau; Dani Tomlin – Australasian Journal of Educational Technology, 2024
This study presents a scoping review of research on artificial intelligence (AI)- driven virtual patients (VPs) for communication skills training of healthcare students. We aimed to establish what is known about these emergent learning tools, to characterise their design and implementation into training programmes. The preferred reporting items…
Descriptors: Allied Health Occupations Education, Artificial Intelligence, Computer Simulation, College Students
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O¨zgu¨r Keles¸; Vincent Brubaker-Gianakos; Vimal Viswanathan; Farshid Marbouti – Journal of STEM Education: Innovations and Research, 2023
This paper describes the application of new Virtual Learning Environments (VLEs) in engineering education. It demonstrates how VLEs improve student learning in two engineering concepts compared with the traditional classroom setting. Literature has conflicting studies on both the advantages and disadvantages of learning in VLEs. The application of…
Descriptors: Educational Environment, Virtual Classrooms, Computer Simulation, Artificial Intelligence
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Shahper Richter; Shohil Kishore; Inna Piven; Patrick Dodd; Guy Bate – British Journal of Educational Technology, 2025
This study investigates how anthropomorphic AI chatbot avatars, designed in line with the Stereotype Content Model (SCM) dimensions of warmth and competence, influence university students' perceptions of support for self-directed learning (SDL) activities. We examined student responses to two distinct avatars--one projecting warmth and the other…
Descriptors: Artificial Intelligence, Technology Uses in Education, Postsecondary Education, Computer Simulation
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Roland Kiraly; Sandor Kiraly; Martin Palotai – Education and Information Technologies, 2024
Deep learning is a very popular topic in computer sciences courses despite the fact that it is often challenging for beginners to take their first step due to the complexity of understanding and applying Artificial Neural Networks (ANN). Thus, the need to both understand and use neural networks is appearing at an ever-increasing rate across all…
Descriptors: Artificial Intelligence, Computer Science Education, Problem Solving, College Faculty
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Belle Dang; Luna Huynh; Faaiz Gul; Carolyn Rosé; Sanna Järvelä; Andy Nguyen – British Journal of Educational Technology, 2025
The rise of generative artificial intelligence (GAI), especially with multimodal large language models like GPT-4o, sparked transformative potential and challenges for learning and teaching. With potential as a cognitive offloading tool, GAI can enable learners to focus on higher-order thinking and creativity. Yet, this also raises questions about…
Descriptors: Man Machine Systems, Artificial Intelligence, Technology Uses in Education, Cooperative Learning
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Nagwa Yousif; Enaam Youssef; Salah Gad – European Journal of Education, 2025
The main purpose of this article is to investigate the prospects of using AI in the education of social workers and social work in general. The research methodology encompassed both pre-test and post-test assessments administered for closed examinations across five academic disciplines, all of which were instructed through the utilisation of the…
Descriptors: Artificial Intelligence, Social Work, Professional Education, College Students
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Luis Alberto Laurens-Arredondo – Education and Information Technologies, 2024
The use of technologies in the classroom has become one of the main allies for university teachers in pedagogical innovation, especially during, and after the pandemic. Therefore, the main objective of this article is to investigate how different types of innovative technologies are most effective in increasing motivation among university…
Descriptors: Educational Technology, Student Motivation, Technology Uses in Education, College Students
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Robin Jephthah Rajarathinam; Chris Palaguachi; Jina Kang – International Educational Data Mining Society, 2024
Multimodal Learning Analytics (MMLA) has emerged as a powerful approach within the computer-supported collaborative learning community, offering nuanced insights into learning processes through diverse data sources. Despite its potential, the prevalent reliance on traditional instruments such as tripod-mounted digital cameras for video capture…
Descriptors: Learning Analytics, Cooperative Learning, Photography, Video Technology
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Kangxu Cui – Interactive Learning Environments, 2023
The article is devoted to the study of the possibilities of augmented reality (AR) mobile applications in acquiring piano skills. The study presents concept of the online course "Piano for Beginners" with the implementation in the educational practices of mobile applications: Flowkey -- Learn Piano; Simply Piano; Skoove: Learn to Play…
Descriptors: Foreign Countries, Music Education, College Students, Student Attitudes
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Oscar Yecid Aparicio-Gómez; Olga Lucia Ostos-Ortiz; Constanza Abadía-García – Journal of Technology and Science Education, 2024
In today's educational environment, the convergence of emerging technologies and active methodologies has become a fundamental driver of change in university education. Emerging technologies, such as artificial intelligence, virtual reality, machine learning, and data analytics, are redefining the dynamics of higher education. Active…
Descriptors: Technological Advancement, Technology Uses in Education, Higher Education, Problem Based Learning
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Eleni Meletiadou, Editor – IGI Global, 2025
Generative Artificial Intelligence (GAI) has emerged as a transformative force in higher education, offering both challenges and opportunities. The integration of AI with Education for Sustainable Development (ESD) in Higher Education has sparked a paradigm shift in teaching, learning and assessment offering both incredible opportunities and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Sustainable Development
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Azzah Al-Maskari; Thuraya Al Riyami; Sami Ghnimi – Journal of Applied Research in Higher Education, 2024
Purpose: Knowing the students' readiness for the fourth industrial revolution (4IR) is essential to producing competent, knowledgeable and skilled graduates who can contribute to the skilled workforce in the country. This will assist the Higher Education Institutions (HEIs) to ensure that their graduates own skill sets needed to work in the 4IR…
Descriptors: Career Readiness, Technological Literacy, Student Attitudes, Information Technology
Opeyemi Peter Ojajuni – ProQuest LLC, 2023
This research study employed quantitative and qualitative designs to explore the impact of immersive technology on the Computational Thinking (CT) capabilities of students enrolled in an engineering program at a Historically Black College or University (HBCU). The quantitative study in this research employs a survey design approach to explore the…
Descriptors: Engineering Education, Mental Computation, Thinking Skills, Computer Simulation
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