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Uun Hariyanti; Wu-Yuin Hwang; Rio Nurtantyana; Herman Dwi Surjono; Irma Nuur Rochmah; Anh Hoang; Muhammad Irfan Luthfi; Muhamad Trio Maulana Putra – Interactive Learning Environments, 2024
Authentic contextual learning (ACL) with mobile apps near home became prevalent and promising due to the COVID-19 pandemic since students were asked to learn near home without going to school. However, learning with mobile apps may cause problematic issues, such as anxiety and acceptance of either students or parents. This study aims to…
Descriptors: Anxiety, Telecommunications, Handheld Devices, Computer Oriented Programs
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Shenglin Cao; Juan Chu; ZuoChen Zhang; Liyan Liu – Interactive Learning Environments, 2024
VR technology is being widely used in education due to it's a sense of immersion, real-time interaction, and ability to stimulate imagination. However, there is a lack of research comparing students at different stages. This study used a quasi-experimental design involving 73 fourth-grade and 86 eighth-grade students in two schools in northwest…
Descriptors: Computer Simulation, Technology Uses in Education, Instructional Effectiveness, Elementary School Students
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Di Zhang; Gwo-Jen Hwang; Shih-Ting Chu – Interactive Learning Environments, 2024
When encountering difficulties in conventional educational games, learners seldom self-regulate to discover and organize the learning content in the game environment. With the development of the human-computer interaction technology, computer agents are gradually being applied to educational games to provide personalized guidance or support to…
Descriptors: Intelligent Tutoring Systems, Educational Games, Technology Uses in Education, Academic Achievement
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Meishar-Tal, Hagit; Shonfeld, Miri – Interactive Learning Environments, 2019
This study took place in a school which adopted a "paperless classroom" policy. The purpose of the study was to examine whether students who learn in a paperless classroom really prefer reading and writing on computers rather than on paper and whether their preferences differ according to contextual conditions and personal differences.…
Descriptors: Preferences, Classroom Environment, Computer Uses in Education, Printed Materials
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Hung, Cheng-Yu; Sun, Jerry Chih-Yuan; Liu, Jia-Yin – Interactive Learning Environments, 2019
This study aimed to investigate the effect of flipped classrooms integrated with massive open online courses (MOOCs) and game-based learning on the learning motivation and learning outcomes of students from different backgrounds (in terms of gender, grade, self-confidence indicators in mathematics, and roles played in the game-based learning…
Descriptors: Blended Learning, Online Courses, Game Based Learning, Instructional Effectiveness
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Ma, Min-Yuan; Wei, Chun-Chun – Interactive Learning Environments, 2016
The reading development of children depends on various sensory stimuli, which help them construct reading contexts and facilitate active learning and exploration. This study uses sensory stimuli provided by picture books using various forms of media to improve children's concentration performance. We employ picture books using four forms of media:…
Descriptors: Comparative Analysis, Attention Control, Elementary School Students, Grade 6
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Hsieh, Ya-Hui; Lin, Yi-Chun; Hou, Huei-Tse – Interactive Learning Environments, 2016
Well-designed game-based learning can provide students with an innovative environment that may enhance students' motivation and engagement in learning and thus improve their learning performance. The purpose of this study was to examine the relationships among elementary school students' flow experience and learning performances. We also…
Descriptors: Foreign Countries, Elementary School Students, Educational Games, Learning Processes
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Chen, Chih-Ming; Wang, Jung-Ying; Chen, Yong-Ting; Wu, Jhih-Hao – Interactive Learning Environments, 2016
To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system (CDRAS). In…
Descriptors: Reading Strategies, Prediction, Models, Quasiexperimental Design