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Ziqing Peng; Yan Wan – Education and Information Technologies, 2024
Understanding preferences surrounding artificial intelligence (AI) and human teaching assistants (TAs) helps managers improve AI TAs, effectively deploying AI and human TAs, and providing better services to learners. The literature has explored how AI TAs' characteristics affect students' use intention, neglecting students' comparative behaviors…
Descriptors: Artificial Intelligence, Teaching Assistants, Student Attitudes, Anxiety
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Adi Perry-Kates; Anat Cohen – Journal of Computer Assisted Learning, 2025
Background: In light of the growing need to understand interactive learning effectivity and especially post-COVID 19 pandemic constraints, the key question is how to develop interactive videos in order to get the most effective results. Objectives: This research aims to explore the pedagogical benefits of interactive video with branching…
Descriptors: Video Technology, Interaction, Instructional Effectiveness, Teaching Methods
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Yinglin Liu; Rui Li; Yue Diao; Meixue Hou; Hua Yuan; Xiuying Zhang – Education and Information Technologies, 2025
Virtual reality (VR) technology has been widely used in nursing laboratory courses to effectively making up for the shortcomings of traditional teaching. However, challenges such as cell phone addiction, negative emotions, and reduced communication between teachers and students still exist during the application process, which makes it difficult…
Descriptors: Undergraduate Students, Learning Processes, Preferences, Nursing Students
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Chunpeng Zhai; Santoso Wibowo; Lily D. Li – Smart Learning Environments, 2024
The growing integration of artificial intelligence (AI) dialogue systems within educational and research settings highlights the importance of learning aids. Despite examination of the ethical concerns associated with these technologies, there is a noticeable gap in investigations on how these ethical issues of AI contribute to students'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Cognitive Ability, Decision Making
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Schmid, Regina; Pauli, Christine; Petko, Dominik – Educational Technology Research and Development, 2023
A growing number of schools have recently been changing their culture of teaching and learning towards personalized learning. Our study investigates how schools use digital technology to facilitate and promote personalized practices. Based on the answers of a student questionnaire from 31 lower-secondary schools with a personalized learning policy…
Descriptors: Technology Uses in Education, Individualized Instruction, Technology Integration, Secondary School 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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Santhi Muttipoll Dharmarajlu – Journal of Educators Online, 2025
This study aims to assess students' preferences for using print books versus ebooks. For this study, 160 students were selected by using a descriptive cross-sectional survey design. The data collected were analyzed using descriptive and inferential statistics. The results show that the duration of time students spent per day reading print books…
Descriptors: Textbooks, Printed Materials, Electronic Books, Student Attitudes
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Kristen Petrizzo; Jessamyn Moxie – Journal of American College Health, 2025
Background: Lesbian, gay, bisexual, transgender, queer, and others (LGBTQ+) students experience more negative sexual health outcomes than their cisgender, heterosexual peers and do not have access to relevant sex education. This denial necessitates comprehensive sex education in college for LGBTQ+ students. Objective: Given the rise of online…
Descriptors: LGBTQ People, Preferences, Sex Education, College Students
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Binbin Zhao; Rim Razzouk – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of…
Descriptors: Music Education, Higher Education, Teaching Methods, Matrices
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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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Patricia Feubli; Douglas MacKevett; Jürg Schwarz – Journal of Computer Assisted Learning, 2024
Background: This research paper presents a cross-sectional study that examinefs the preferences of students for hybrid teaching and learning scenarios. Unlike previous studies that merely describe hybrid scenarios, this research prioritizes them, offering evidence-based findings for informed policy decisions. Methods: The data collection method…
Descriptors: Blended Learning, Preferences, Foreign Countries, Educational Environment
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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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Stela-Marina Kostaki; Michalis Linardakis – Education and Information Technologies, 2025
The current study explores the preferences of primary school teachers on the characteristics of Information and Communication Technologies (ICT)-based teaching via Discrete Choice Models (DCM). These models analyze the preferences of teachers towards alternatives that are formed by different characteristics. In this study we examined the…
Descriptors: Elementary School Teachers, Teacher Attitudes, Preferences, Teaching Methods
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Gayane Sedrakyan; Simone Borsci; Asad Abdi; Stéphanie M. van den Berg; Bernard P. Veldkamp; Jos van Hillegersberg – Journal of Research in Innovative Teaching & Learning, 2025
Purpose: This research aims to explore digital feedback needs/preferences in online education during lockdown and the implications for post-pandemic education. Design/methodology/approach: An empirical study approach was used to explore feedback needs and experiences from educational institutions in the Netherlands and Germany (N = 247) using a…
Descriptors: Feedback (Response), Electronic Learning, Preferences, Online Courses
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