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Showing 1 to 15 of 34 results Save | Export
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Phil Seok Oh; Gyeong-Geon Lee – Science & Education, 2025
How and why science education scholars and practitioners might use artificial intelligence (AI) in the classroom has been a controversial agenda for decades. ChatGPT, a state-of-the-art (SOTA) AI released in November 2022, has attracted global interest for its exceptionally high performance in generating human-like natural language answers to…
Descriptors: Science Education, Artificial Intelligence, Cognitive Processes, Affective Behavior
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Ce Song – European Journal of Education, 2025
This study examines the role of AI-powered learning tools in influencing cognitive load, well-being and academic success among music education students, with a focus on technology acceptance as a key factor. Data were collected through a random sampling of 454 Chinese music students (192 males, 262 females) aged 18-24, with varying levels of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Influence of Technology, Music Education
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Deliang Wang; Cunling Bian; Gaowei Chen – British Journal of Educational Technology, 2024
Deep neural networks are increasingly employed to model classroom dialogue and provide teachers with prompt and valuable feedback on their teaching practices. However, these deep learning models often have intricate structures with numerous unknown parameters, functioning as black boxes. The lack of clear explanations regarding their classroom…
Descriptors: Artificial Intelligence, Dialogs (Language), Discourse Analysis, Trust (Psychology)
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Ricardo Alberto Reza Flores; Citlali Michélle Reza-Flores; Cristinao Galafassi; Abril Acosta-Ochoa; Rosa Maria Vicari – Journal of Pedagogy, 2025
This study examines how secondary-school students recognize and relate to artificial intelligence (AI) and the meanings they attribute to it in their everyday lives. Using a quantitative, descriptive, cross-sectional design, we explore the subjectivities of a purposive sample of 576 students from both public and private schools. The analysis…
Descriptors: Secondary School Students, Artificial Intelligence, Ethics, Moral Values
Ashley Hampton – ProQuest LLC, 2021
Hashim, Tan, and Rashid's (2015) study, "Adult Learners' Intention to Adopt Mobile Learning: A Motivational Perspective," was intriguing because there were so many adult learners, also known as nontraditional students, who struggled with online or m-learning because it did not appeal to the desires and/or needs of students with families…
Descriptors: Electronic Learning, Adult Students, Adult Learning, Student Attitudes
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Stiller, Klaus D. – Journal of Educational Multimedia and Hypermedia, 2019
In three experiments, learners used computerized learning material, which consisted of static pictures and on-screen text relating to the physiology of vision in one of two formats. The formats differed in method of access to text. Accessing text by clicking on picture components was hypothesized to produce superior learning to linear access…
Descriptors: Educational Technology, Technology Uses in Education, Visual Stimuli, Pictorial Stimuli
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del Barrio-García, Salvador; Arquero, José L.; Romero-Frías, Esteban – Educational Technology & Society, 2015
As long as students use Web 2.0 tools extensively for social purposes, there is an opportunity to improve students' engagement in Higher Education by using these tools for academic purposes under a Personal Learning Environment approach (PLE 2.0). The success of these attempts depends upon the reactions and acceptance of users towards e-learning…
Descriptors: Foreign Countries, Learning Experience, Electronic Learning, Satisfaction
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Stiller, Klaus D.; Köster, Annamaria – European Journal of Open, Distance and E-Learning, 2016
Online learning has gained importance in education over the last 20 years, but the well-known problem of high dropout rates still persists. According to the multi-dimensional learning tasks model, the cognitive (over)load of learners is essential to attrition when dealing with five challenges (e.g. technology, user interface) of an online training…
Descriptors: Foreign Countries, Student Attrition, Advanced Courses, Online Courses
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Santoso, Harry B.; Lawanto, Oenardi; Becker, Kurt; Fang, Ning; Reeve, Edward M. – Journal of Pre-College Engineering Education Research, 2014
The purpose of this research was to investigate high school students' computer self-efficacy (CSE) and learning behavior in a self-regulated learning (SRL) framework while utilizing an interactive learning module. The researcher hypothesizes that CSE is reflected on cognitive actions and metacognitive strategies while the students are engaged with…
Descriptors: Self Efficacy, High School Students, Self Control, Educational Environment
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Rountree, Janet; Robins, Anthony; Rountree, Nathan – Computer Science Education, 2013
We propose an expanded definition of Threshold Concepts (TCs) that requires the successful acquisition and internalisation not only of knowledge, but also its practical elaboration in the domains of applied strategies and mental models. This richer definition allows us to clarify the relationship between TCs and Fundamental Ideas, and to account…
Descriptors: Fundamental Concepts, Concept Formation, Computer Science Education, Undergraduate Students
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Curwood, Jen Scott – Journal of Literacy Research, 2014
Prompted by calls for research on technology-focused professional development, this ethnographic case study investigates how teachers' participation in learning communities may influence technology integration within the secondary English curriculum. In this article, I draw on educational psychology, cognitive anthropology, and sociolinguistics to…
Descriptors: Faculty Development, Discourse Analysis, Ethnography, Communities of Practice
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Shin, Dong-Hee; Biocca, Frank; Choo, Hyunseung – Behaviour & Information Technology, 2013
This study examines the users' experiences with three-dimensional (3D) virtual environments to investigate the areas of development as a learning application. For the investigation, the modified technology acceptance model (TAM) is used with constructs from expectation-confirmation theory (ECT). Users' responses to questions about cognitive…
Descriptors: Foreign Countries, Virtual Classrooms, Expectation, Cognitive Processes
Christensen, Rhonda; Knezek, Gerald; Tyler-Wood, Tandra; Gibson, David – International Association for Development of the Information Society, 2013
The purpose of this paper is to determine whether the changes that were found to occur pre- to post intervention in students' cognitive structures (Mills, 2013; Knezek, Christensen, Tyler-Wood, & Periathiruvadi, 2013) continued to persist two years later. Major findings were: a) semantic perception of science and STEM as a career became more…
Descriptors: Middle School Students, Hands on Science, Science Instruction, Cognitive Processes
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Sayago, Sergio; Guijarro, Jose-Maria; Blat, Josep – Behaviour & Information Technology, 2012
This article reports on an exploratory study aimed to identify which ways of marking required and optional fields help older people fill in web forms correctly. Drawing on a pilot study and selective attention research in ageing, modified versions of widely used forms were created, in which standard asterisks were replaced with one of three…
Descriptors: Foreign Countries, Attention Control, Attention, Design Requirements
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Connolly, C.; Murphy, E.; Moore, S. – IEEE Transactions on Education, 2009
Low retention rates in third-level computing courses, despite continuing research into new and improved computer teaching methods, present a worrying concern. For some computing students learning programming is intimidating, giving rise to lack of confidence and anxiety. The noncognitive domain of anxiety with regard to learning computer…
Descriptors: Computer Science Education, Computer Attitudes, Programming, Anxiety
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