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Showing 1 to 15 of 29 results Save | Export
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Yanjun Liu; Ben R. Newell; Jaimie E. Lee; Brett K. Hayes – Cognitive Science, 2025
A simple-rule learning trap occurs when people show suboptimal category learning due to insufficient exploration of the learning environment. By combining experimental methods and computational modeling, the current study investigated the impact of two key factors believed to play essential roles in the development of a simple-rule learning trap:…
Descriptors: Early Experience, Attention Control, Educational Environment, Barriers
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Malte Rolf Teichmann – IEEE Transactions on Learning Technologies, 2025
Due to the rise of virtual reality and the--at least now--hypothetical construct of the Metaverse, learning processes are increasingly transferred to immersive virtual learning environments. While the literature provides few design guidelines, most papers miss an application and evaluation description of the design and development processes. As a…
Descriptors: Instructional Design, Computer Simulation, Educational Environment, Learning Processes
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Audur Palsdottir – International Research in Geographical and Environmental Education, 2025
The purpose of this research is to develop the use of Virtual Reality (VR) and fieldwork with teenagers in two compulsory schools in the capital city area of Iceland. The study aims to understand how teenagers succeed in an enquiry driven work combining simple digital tools, such as mobile phones, when making 360° photos, analysing opportunities…
Descriptors: Adolescents, Geography Instruction, Computer Simulation, Foreign Countries
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Yingbin Zhang; Luc Paquette; Nigel Bosch – International Journal of Artificial Intelligence in Education, 2025
Understanding the transitions among affective states during computer-based learning may guide the design of affect-responsive learning environments. Current studies have focused on the marginal strength of an affect transition, which is the average transition tendency over possible affective states preceding the transition. However, marginal…
Descriptors: Affective Behavior, Emotional Response, Electronic Learning, Learning Experience
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Radek Pelánek – International Journal of Artificial Intelligence in Education, 2025
While the potential of personalized education has long been emphasized, the practical adoption of adaptive learning environments has been relatively slow. Discussion about underlying reasons for this disparity often centers on factors such as usability, the role of teachers, or privacy concerns. Although these considerations are important, I argue…
Descriptors: Educational Environment, Modeling (Psychology), Barriers, Adjustment (to Environment)
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Chai Ping Woon; Meng Yew Tee – On the Horizon, 2025
Purpose: This study aims to examine how learners manage their self-directed learning (SDL) in different SDL contexts through the lens of structuration theorizing. Design/methodology/approach: In this comparative case study, data were collected primarily from in-depth semi-structured interviews with three self-directed learners aged between 15 and…
Descriptors: Foreign Countries, Independent Study, Educational Environment, Learning Strategies
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Siu Shing Man; Yizhen Fang; Alan Hoi Shou Chan; Jiayan Han – Education and Information Technologies, 2025
With the continuous evolution of information technology shaping advancements in education, virtual reality (VR) technology has been increasingly applied to enhance English learning amongst students, aiming to boost learning efficiency and performance. This study introduced a VR technology acceptance model (TAM) to fulfil these requirements. The…
Descriptors: Computer Simulation, Technology Uses in Education, Educational Environment, Anxiety
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Youngmi Kim; Shinyu Oh; Tae-Young Kim – English Teaching, 2025
This study explored factors affecting variability in second language (L2) learning motivation among Korean university students and how they appraised their L2 learning experience. In this study, 85 undergraduate students majoring in English or English education from three universities in Seoul, South Korea, reflected on their past English learning…
Descriptors: Second Language Learning, Learning Motivation, Learning Experience, Foreign Countries
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Patrick N. Beymer; Matthew J. Schell; Kimberly M. Alberts; Vicky Phun; Joshua M. Rosenberg; Jennifer A. Schmidt – Journal of Research in Science Teaching, 2025
Student engagement is widely considered to be a multidimensional construct consisting of behavioral, cognitive, and affective components. Recent research has examined student engagement in science learning contexts using holistic approaches that account for multidimensionality through the identification of engagement profiles. However, it is not…
Descriptors: Informal Education, Science Education, Learner Engagement, Profiles
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Jill Bamforth; Elizabeth Levin; Jeff Waters; Sean Gallagher; Kristina Turner; Bin Wu – Higher Education Research and Development, 2025
Hybrid teaching & learning (T&L) environments in higher education are on the rise. This study adopts a qualitative exploratory approach to draw on data from interviews with 15 academics to examine their perspectives of hybrid T&L in a higher education, post COVID-19 context. In a unique application of both the Reset, Restore, Reframe…
Descriptors: Blended Learning, Learning Processes, Teaching Methods, COVID-19
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EL Hassane Ait Ali – Journal of Educators Online, 2025
The Community of Inquiry (COI) framework theory, developed by Garrison et al. (1999), is an established theoretical framework in distant and online learning. The purpose of this study is to discover more about how university students view instructors' presence and how it affects their motivation and learning outcomes. Data were gathered using the…
Descriptors: Outcomes of Education, Student Motivation, Learning Processes, Educational Environment
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Jan Elen; Fien Depaepe – Educational Technology Research and Development, 2025
The relationship between technology and educational processes is a complex one. At this moment, increased digitization as well as efforts to limit the use of digital tools can be observed. In view of (a) deepening our understanding of the relationship between technology and educational processes and (b) strengthening the productive educational use…
Descriptors: Students, Teachers, Educational Technology, Learning Processes
Quazi Mahtab Zaman – Sage Research Methods Cases, 2025
The Stitching Urban Vision (SUV)1 method is innovative, facilitating children to co-create a sense of empowerment. SUV© fosters an understanding of negotiation using a shared vision. SUV© sits apart from traditional negotiating methods that often result in delayed, unresolved, and fragmented ideas. Adults often resist reaching collective decisions…
Descriptors: Instructional Innovation, Teaching Methods, Content Analysis, Cooperative Learning
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Anna Hawrot; Lena Nusser – Scandinavian Journal of Educational Research, 2025
This study investigated whether various aspects of the home learning environment -- that is, learning-related processes, parental perceptions of their child, and structural characteristics -- predicted private tutoring attendance in Grade 8. We used the data of 7393 students from the German National Educational Panel Study. Seventeen percent of…
Descriptors: Family Environment, Educational Environment, Tutoring, Private Education
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M. El-Sayed; J. El-Sayed; K. Burke; D. Apple – European Journal of Education, 2025
In any educational setting, stigmatisation and implicit biases can stifle growth and reduce the quality of the learning experience of students from low socio-economic status by creating invisible barriers to opportunity and achievement. Furthermore, due to the lack of monitoring and mentoring, these invisible barriers become harder to detect and…
Descriptors: Social Bias, Negative Attitudes, Educational Environment, Attitude Change
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