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Showing 1 to 15 of 46 results Save | Export
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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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Kimberly Maslin; Karen Murcia; Susan Blackley; Geoff Lowe – Australian Educational Researcher, 2025
Fostering young children's creativity is a desired outcome of STEM learning experiences. Such experiences often incorporate hands-on activities that encourage agency, curiosity, and experimentation. While educators generally have a good understanding of how to nurture creativity within a physical learning environment, less is known about…
Descriptors: STEM Education, Creativity, Electronic Learning, Learning Experience
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Lianghai Chu – Education and Information Technologies, 2025
The rapid advancement of artificial intelligence (AI) technology has enabled the creation of digital human instructors with human-like visual and verbal characteristics. This study investigates the impact of human likeness on learner satisfaction within e-learning environments, drawing on the "Uncanny Valley" theory and the Experience…
Descriptors: Student Satisfaction, Computer Assisted Instruction, Electronic Learning, Artificial Intelligence
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Chun-Mei Chou; Tsu-Chuan Shen; Tsu-Chi Shen – Education and Information Technologies, 2025
AR-supported instruction has been verified to improve students' problem-solving skills. This study investigated 1041 university students and developed an empirical research model that combined technology acceptance, self-regulation, and AR-supported learning effectiveness with the structural equation model (SEM). At the same time, content analysis…
Descriptors: College Students, Student Attitudes, Computer Attitudes, Adoption (Ideas)
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Diego Airado-Rodri´guez; David Mun~oz de la Pen~a; Isabel Dura´n-Mera´s; Jaime Domi´nguez Manzano; Arsenio Mun~oz de la Pen~a – Journal of Chemical Education, 2022
In this paper, the development of an automatic assessor is presented, both in MATLAB and in Excel, for an analytical exercise. In particular, the emulation of an interlaboratory exercise, using the analytical determination of phosphorus in a dry detergent, carried out in the laboratory by different groups of students, was selected as a case of…
Descriptors: Electronic Learning, Chemistry, Evaluation Methods, Computer Assisted Instruction
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Yavuz Akbulut; Onur Dönmez; Beril Ceylan; Tayfun Firat – Journal of Computing in Higher Education, 2025
Providing pre-training on new material can simplify complex content for learners who may need guidance to understand basic facts and organize their efforts. However, the effect of pre-training on learning outcomes is controversial because it tends to vary by context. Our aim was to investigate the effectiveness of pre-training in reducing…
Descriptors: Training, Cognitive Processes, Difficulty Level, Academic Achievement
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Diane P. Montgomery; Kathy Snow – Journal of Teaching and Learning, 2024
During the COVID-19 pandemic, online learning became the predominant mode of learning for 33 to 54% of students in Canada's three largest school boards. As inclusive practices continue to grow and online learning is now part of the Ontario curriculum, educators need guidance on how to support K-12 students with diverse learning needs in online and…
Descriptors: Student Needs, Usability, Electronic Learning, Student Attitudes
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Hako, Anna Niitembu; Tobias, Elina Ileimo; Erastus, Kleopas – European Journal of Educational Sciences, 2021
The study explored the e-teaching and learning experiences of lecturers amidst the COVID-19 pandemic at one of the University of Namibia satellite campuses. The study sample was 76 selected using the purposive sampling method from the population of 98. The study used a convergent parallel research design within a mixed methods research approach. A…
Descriptors: Foreign Countries, Computer Assisted Instruction, Electronic Learning, College Faculty
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Schwarzenberg, Pablo; Navon, Jaime; Pérez-Sanagustín, Mar – Journal of Computing in Higher Education, 2020
The flipped classroom gives students the flexibility to organize their learning, while teachers can monitor their progress analyzing their online activity. In massive courses where there are a variety of activities, automated analysis techniques are required in order to process the large volume of information that is generated, to help teachers…
Descriptors: Models, Blended Learning, Teaching Methods, Electronic Learning
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Solodka, Anzhelika; Ruskulis, Liliia; Demianenko, Olha; Zaskaleta, Svitlana – Arab World English Journal, 2022
Mobile-assisted language learning (MALL) is a new channel of learning languages. The usage of MALL instructional design integrates mobile devices with educational scenarios of teaching foreign languages. The study explores the central issue of how MALL instructional course design could help students to construct an out-of-class MALL experience.…
Descriptors: Telecommunications, Handheld Devices, Second Language Learning, Student Attitudes
Project Tomorrow, 2018
The Speak Up National Research Project annually polls K-12 students, parents and educators about the role of technology for learning in and out of school. For the past fifteen years, Project Tomorrow's® annual Speak Up Research Project for Digital Learning has provided schools and districts nationwide and around the globe with illuminating…
Descriptors: Electronic Learning, Equal Education, Instructional Effectiveness, Computer Uses in Education
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Lee, Kyungmee; Ardeshiri, Minoo; Cummins, Jim – Technology, Pedagogy and Education, 2016
The aim of this article is to introduce a computer-assisted multiliteracies programme (CaMP) as an alternative approach to English as a Foreign Language (EFL) instruction in order to overcome the educational limitations that are inherent in most EFL settings. In a number of monolingual societies with a dominant language other than English,…
Descriptors: Computer Assisted Instruction, Multiple Literacies, Second Language Instruction, Electronic Learning
Project Tomorrow, 2015
The Speak Up National Research Project annually polls K-12 students, parents and educators about the role of technology for learning in and out of school. For the past twelve years, Project Tomorrow's® annual Speak Up Research Project has provided schools and districts nationwide and throughout the globe with new insights into how today's students…
Descriptors: Electronic Learning, Elementary School Students, Secondary School Students, Computer Uses in Education
Connor, Kenneth A. – Chronicle of Higher Education, 2012
When students complete a lab experiment at home or in a staffed lab on campus, they come to class better able to explain what they have done and why they think the approach is correct, and to provide explanations or questions about any problems they encountered. What is so cool is that the learning experience has all the key aspects of the…
Descriptors: Engineering Education, Engineering, Learning Experience, Computer Assisted Instruction
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Lin, Kan-Min – Computers & Education, 2011
This study explores the determinants of the e-learning continuance intention of users with different levels of e-learning experience and examines the moderating effects of e-learning experience on the relationships among the determinants. The research hypotheses are empirically validated using the responses received from a survey of 256 users. The…
Descriptors: Electronic Learning, Intention, Learning Experience, Information Retrieval
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