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Showing 1 to 15 of 348 results Save | Export
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Dahwi Ahn; Jason C. K. Chan – Applied Cognitive Psychology, 2025
COVID-19 greatly increased the online delivery of higher education. But one limitation of online learning is that students often struggle to stay engaged while watching online lectures. We examined whether including an instructor's face in lecture videos (instructor visibility) enhances student engagement or learning. In two preregistered…
Descriptors: Learner Engagement, Video Technology, Lecture Method, Student Attitudes
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Yu, Liqin; Wu, Di; Yang, Harrison Hao; Zhu, Sha – Australasian Journal of Educational Technology, 2022
In recent years, smart classrooms have been widely constructed in colleges and universities. To help the design of student-centred smart classroom in compliance with students' information literacy levels and enable all students to adapt to the smart classroom smoothly, this study utilised a quantitative method to investigate the information…
Descriptors: Educational Technology, Preferences, Information Literacy, College Students
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Chimezie O. Amaefule; Jan Britzwein; Jason C. Yip; Garvin Brod – Education and Information Technologies, 2025
Self-regulated learning (SRL) involves processes by which learners purposefully direct their cognitions, emotions, and behaviors towards the achievement of personal learning goals. Research has shown that young learners often struggle with SRL. Educational technology could be useful to support their SRL. However, it remains unclear how support…
Descriptors: Childrens Attitudes, Independent Study, Self Management, Educational Technology
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Rico Amoussohoui; Aminou Arouna; Miroslava Bavorova; Vladimir Verner; Wilfried Yergo; Jan Banout – Journal of Agricultural Education and Extension, 2024
Purpose: The study evaluates new approach of digital extension services for the long-term adoption of digital extension technologies. We propose an indirect adoption approach to address following research questions. What socioeconomic factors influence rice farmers' decision to prefer one business profile over another? Which business profile is…
Descriptors: Foreign Countries, Socioeconomic Influences, Agricultural Occupations, Predictor Variables
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Engin Demir; Huseyin Cevik – Turkish Online Journal of Distance Education, 2025
Students' attitudes towards distance education can be shaped by the compatibility of their learning styles with this new educational environment. The study aimed to investigate whether various variables and e-learning styles predict student's attitudes towards distance education. The present research was conducted on 387 students enrolled in the…
Descriptors: Student Attitudes, Electronic Learning, Educational Technology, Predictor Variables
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Rani, Neha; Chu, Sharon Lynn – Education and Information Technologies, 2022
Wearable devices are a popular class of portable ubiquitous technology. These devices are available in a variety of forms, ranging from smart glasses to smart rings. The fact that smart wearable devices are attached to the body makes them particularly suitable to be integrated into people's daily lives. Thus, we propose that wearables can be…
Descriptors: Electronic Learning, Assistive Technology, Affordances, Educational Technology
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Ahtsham U. Niazi; Alayne Kealey; Stephen Choi; Lilia Kaustov; Jordan Tarshis – Discover Education, 2024
To improve clinical teaching skills, feedback on teachers' strengths and weaknesses needs to be reliable, timely, and relevant. To provide timely feedback we undertook development of an analytical dashboard to provide learner feedback to our faculty. As dashboard data displays are limited we performed a modified Delphi (mDelphi) method to…
Descriptors: Teacher Effectiveness, Teacher Improvement, Feedback (Response), Preferences
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Gonul Ozsari; Cengiz Hakan Aydin – Open Learning, 2024
Technological advances allow open and distance learning (ODL) providers to offer all kinds of interaction opportunities for their students. In Turkey, different institutions adopt different interaction types in ODL services mostly because of legal procedures and a shortage of experience in ODL. Learning more about students' preferences and needs…
Descriptors: Distance Education, Interaction, Educational Technology, Electronic Learning
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Kheira Ouassif; Benameur Ziani – Education and Information Technologies, 2025
The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…
Descriptors: Predictor Variables, College Students, Majors (Students), Decision Making
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Ahmad Kamal Sudrajat; Agung Wijaya Subiantoro; M. Ikhsan Al Ghazi – Journal of Biological Education Indonesia (Jurnal Pendidikan Biologi Indonesia), 2025
Technology development has changed students' characteristics and learning needs. As facilitators of student learning, teachers should be able to use learning technology effectively in their classrooms. This study aimed to examine teacher preferences in using learning technology and explore key factors for using learning technology. This study used…
Descriptors: Foreign Countries, Science Teachers, Biology, Educational Technology
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Himel Mondal – Advances in Physiology Education, 2025
Self-directed learning (SDL) is integral to medical education. It helps in fostering critical thinking, independence, and problem-solving skills. With advancements in technology, digital tools like search engines, interactive content, and large language model (LLM) chatbots have become supplementary tools to traditional materials such as…
Descriptors: Foreign Countries, Medical Education, Medical Students, Physiology
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Jessica Saini; Danielle Brewer-Deluce; Noori Akhtar-Danesh; Anthony N. Saraco; Ilana Bayer; Courtney Pitt; Bruce Wainman – Canadian Journal for the Scholarship of Teaching and Learning, 2023
Pursuant to pedagogical changes necessitated by the COVID-19 pandemic, this study was designed to determine which aspects of an online anatomy course students most preferred and most disliked using Q-methodology. Data were collected in fall 2020 and winter 2021, and 166 student responses were analyzed via by-person factor analysis. Three distinct…
Descriptors: Student Attitudes, Online Courses, Anatomy, COVID-19
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Maribell Reyes-Millán; Patricia Vázquez-Villegas; Luis Alberto Mejía-Manzano; Jorge Membrillo-Hernández – American Journal of Distance Education, 2024
Due to the COVID-19 pandemic, higher education students had to switch to online classes to avoid infections, so universities had to adapt to a situation known as emergency remote education and had to provide digital content to simulate the traditional classroom experience. Now, as we transition from the pandemic, returning to in-person education…
Descriptors: Foreign Countries, Student Attitudes, Preferences, COVID-19
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Chyanna Wee; Lillian Yee Kiaw Wang; Huey Fang Ong – ACM Transactions on Computing Education, 2025
This study presents the development of a student-centric framework for utilizing virtual reality (VR) technologies in education, specifically focusing on enhancing computational thinking skills. While numerous frameworks exist in this domain, they often lack consideration of student preferences, which are integral for fostering learner autonomy.…
Descriptors: Computer Simulation, Educational Technology, Technology Uses in Education, Computation
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Michelle Alvarado; Katie Basinger-Ellis; Behshad Lahijanian; Meserret Karaca; Diego Alvarado – Advances in Engineering Education, 2023
Student preferences for digital learning and the COVID-19 pandemic have increased demand for asynchronous learning activities, including pre-recorded video lectures. However, there are varying recommendations and a lack of data-driven results for how long video lectures should be. This study has two purposes: (1) To determine and understand…
Descriptors: Student Attitudes, Engineering Education, Electronic Learning, Educational Technology
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