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Meehyun Yoon; Koun Choi; Seonghye Yoon; Il-Hyun Jo – Journal of Computer Assisted Learning, 2024
Background: Virtual reality (VR) is becoming increasingly accessible and being utilized in various organizations to meet education and training needs. Despite its potential, research regarding VR applications has focused on measuring the effectiveness of VR programs relative to non-VR programs; consequently, the ways in which VR programs are…
Descriptors: Computer Simulation, Training, Program Effectiveness, Training Methods
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Piia Näykki; Saara Pyykkönen; Jenni Latva-aho; Tuula Nousiainen; Emilia Ahlström; Tapio Toivanen – Journal of Computer Assisted Learning, 2024
Background: In recent years, the use of virtual reality (VR) environments for education has gained interest in research and education. However, little is known about the potential of social VR environments for collaborative learning. Objectives: This study explores pre-service teachers' (PSTs') collaborative learning and role-based drama activity,…
Descriptors: Computer Simulation, Cooperative Learning, Preservice Teachers, Drama
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Hans G. K. Hummel; Rob Nadolski; Hugo Huurdeman; Giel van Lankveld; Konstantinos Georgiadis; Aad Slootmaker; Hub Kurvers; Mick Hummel; Petra Neessen; Johan van den Boomen; Ron Pat-El; Julia Fischmann – Journal of Computer Assisted Learning, 2024
Background: Complex skills, like analytical thinking, are essential in preparing students for future professions. Serious games hold potential to stimulate the online acquisition of such professional skills in an active and experiential way. Objective: Rubrics are proven assessment and evaluation instruments, but were never directly integrated…
Descriptors: Game Based Learning, Scoring Rubrics, Educational Games, Computer Simulation
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Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
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Ronald L. Reyes; Kristina P. Isleta; Jennifer D. Regala; Daisy Mae R. Bialba – Journal of Computer Assisted Learning, 2024
Background: The adoption of virtual laboratories (VLs) has experienced a significant surge, catalysed by the global changes in the educational landscape, notably influenced by the COVID-19 pandemic. Originally supplementary to traditional in-person laboratory experiments, VLs swiftly transitioned into a primary source of hands-on laboratory…
Descriptors: Science Laboratories, Computer Simulation, Educational Technology, Science Instruction
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Kang, Youn Gu; Song, Hae-Deok; Yun, Hyejoo; Jo, Yunseong – Journal of Computer Assisted Learning, 2022
Background: This study aims to establish the mechanism by which virtual reality (VR) media characteristics affect learning transfer in a VR-based job-training environment. The two main determinants of learning transfer are the technology and the learner, but not many studies have considered both factors simultaneously. Objectives: This study aims…
Descriptors: Computer Simulation, Job Training, Transfer of Training, Engineering
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Han, Insook; Shin, Hyoung Seok; Ko, Yujung; Shin, Won Sug – Journal of Computer Assisted Learning, 2022
Background: Immersive VR is still rarely used as an intervention for meeting the affective end goals of student learning despite its positive impact on affection. Also, studies regarding the use of immersive VR as an intervention for affective achievement in broader educational contexts are still lacking. Objectives: This study aimed to examine…
Descriptors: Computer Simulation, Educational Technology, Technology Uses in Education, Program Effectiveness
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Lin, Xiao-Fan; Liang, Zhong-Mei; Chan, Kan Kan; Li, Wenyi; Ling, Xiaolan – Journal of Computer Assisted Learning, 2022
Background: The contextual and interactive learning research was motivated by the need to enhance the healthcare training effect of caregivers of patients with suspected COVID-19 infection during quarantine. However, there is a lack of effective approaches to integrating mobile contextual learning into interactive learning. Objectives: Therefore,…
Descriptors: COVID-19, Pandemics, Telecommunications, Handheld Devices
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Fischer, Julian; Machts, Nils; Bruckermann, Till; Möller, Jens; Harms, Ute – Journal of Computer Assisted Learning, 2022
Background: The professional knowledge of pre-service teachers is highly important for effective and successful teaching. In recent years, many research groups have been engaged in developing simulated classroom environments to capture especially the pedagogical knowledge (PK) of pre-service teachers, neglecting the content-related facets of…
Descriptors: Preservice Teachers, Preservice Teacher Education, Biology, Pedagogical Content Knowledge
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Li, Chen; Ip, Horace H. S.; Wong, Yuen M.; Lam, Wing S. – Journal of Computer Assisted Learning, 2020
According to the census data published by the government in 2016, 92% of the Hong Kong Special Administrative Region population is ethnic Chinese, while the number of ethnic minorities increased significantly by around 70% over the past decade. Enhancing the youth's intercultural sensitivity is becoming critical. Although many of the schools start…
Descriptors: Foreign Countries, Computer Simulation, Sensitivity Training, Cultural Awareness
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Weng, Cathy; Otanga, Sarah; Weng, Apollo; Tran, Khanh Nguyen Phuong – Journal of Computer Assisted Learning, 2020
The purpose of this research was to compare the effectiveness of physical and virtual tangrams on preschool children's learning engagement and achievement. Children listened to an e-storybook narration and solved puzzles individually. The experimental group (N = 31) completed puzzles embedded in the e-storybook using virtual tangrams, while the…
Descriptors: Preschool Children, Computer Simulation, Manipulative Materials, Learner Engagement
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Sebastian, Katharina; Ghose, Tandra; Huff, Markus – Journal of Computer Assisted Learning, 2018
Humans segment naturalistic actions into meaningful units. These are hierarchically organized: multiple fine events are part of a coarse event. We investigated how repeated practice of a virtual sequential assembly task influences learning of coarse and fine assembly steps. In Experiment 1, participants (N = 10) parsed the task into coarse and…
Descriptors: Drills (Practice), Memory, Computer Simulation, Program Effectiveness