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Showing 1 to 15 of 81 results Save | Export
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Andrew Kwok-Fai Lui; Sin-Chun Ng; Stella Wing-Nga Cheung – Interactive Learning Environments, 2024
The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…
Descriptors: Grading, Computer Uses in Education, Educational Technology, Artificial Intelligence
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Zhang, Lishan; Huang, Yuwei; Yang, Xi; Yu, Shengquan; Zhuang, Fuzhen – Interactive Learning Environments, 2022
Automatic short-answer grading has been studied for more than a decade. The technique has been used for implementing auto assessment as well as building the assessor module for intelligent tutoring systems. Many early works automatically grade mainly based on the similarity between a student answer and the reference answer to the question. This…
Descriptors: Automation, Grading, Models, Artificial Intelligence
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Ainhoa Alvarez; Mikel Villamañe – Interactive Learning Environments, 2024
Assessment is a key element in any course, and providing students with a balance between formative and summative assessments is crucial. Defining such a process is a complex task for teachers and often entails a great workload. This makes it necessary to have tools to help in the assessment process definition and its monitoring. This paper first…
Descriptors: Open Source Technology, Learning Management Systems, Student Evaluation, College Students
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Sonsoles López-Pernas; Mohammed Saqr; Aldo Gordillo; Enrique Barra – Interactive Learning Environments, 2023
Learning analytics methods have proven useful in providing insights from the increasingly available digital data about students in a variety of learning environments, including serious games. However, such methods have not been applied to the specific context of educational escape rooms and therefore little is known about students' behavior while…
Descriptors: Learning Analytics, Educational Games, Student Behavior, Computer Uses in Education
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Diana P. Zwart; Sui Lin Goei; Johannes E. H. Van Luit; Omid Noroozi – Interactive Learning Environments, 2023
Computer-based virtual learning environments (CBVLEs) have attracted attention as a learning innovation that can foster students' self-efficacy and intrinsic motivation. Research on the instructional design regarding these aspects of learning in a virtual learning environment is rather piecemeal. This study investigates the instructional design of…
Descriptors: Nursing Education, Computer Uses in Education, Student Satisfaction, Instructional Design
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Ilana Dubovi; Idit Adler – Interactive Learning Environments, 2024
Computer-based simulations are highly effective in supporting students' deep conceptual understanding of scientific ideas. However, in the unprecedented era of the COVID-19 outbreak, students around the world experienced an induced state anxiety, which may have affected their engagement with the learning environments and ultimately their academic…
Descriptors: COVID-19, Pandemics, Anxiety, Learner Engagement
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Shamsuzzoha, Ahm; Toshev, Rayko; Vu Tuan, Viet; Kankaanpaa, Timo; Helo, Petri – Interactive Learning Environments, 2021
This study evaluates the use of virtual reality (VR) platforms, which is an integrated part of the digital factory for an industrial training and maintenance system. The digital factory-based VR platform provides an intuitive and immersive human-computer interface, which can be an efficient tool for industrial training and maintenance services.…
Descriptors: Computer Simulation, Industrial Training, Computer Uses in Education, Man Machine Systems
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Kai Guo; Yuchun Zhong; Danling Li; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
This study proposed a novel approach to classroom debates, in which chatbots that are able to engage in argumentative dialogues are adopted to facilitate students' debate preparation. The approach comprised three stages: first, students interacted with a chatbot named Argumate to help them generate ideas; second, students discussed the ideas with…
Descriptors: Foreign Countries, Undergraduate Students, Debate, Persuasive Discourse
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Siu-Cheung Kong; Wei Shen – Interactive Learning Environments, 2024
Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…
Descriptors: Student Characteristics, Predictor Variables, Comprehension, Computation
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Noawanit Songkram; Supattraporn Upapong; Heng-Yu Ku; Narongpon Aulpaijidkul; Sarun Chattunyakit; Nutthakorn Songkram – Interactive Learning Environments, 2024
This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Grade 1
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Bahari, Akbar – Interactive Learning Environments, 2023
The purpose of this systematic review was three-fold: (a) to convey technology-assisted language learning (TALL) affordances that facilitate catering to the nonlinearity and dynamicity of the second language (L2) motivational factors, (b) to identify TALL challenges that inhibit the integration of educational technologies to enhance L2 motivation…
Descriptors: Affordances, Barriers, Technology Uses in Education, Second Language Learning
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Paul Bazelais; Gurinder Binner; Tenzin Doleck – Interactive Learning Environments, 2024
As an important tool for STEM education, online labs have gained significant research attention. However, our understanding of online labs is limited by the inattention to the factors that contribute to the acceptance of online labs. This study adopts the UTAUT model to investigate the salient determinants of use of online labs. We test the…
Descriptors: Foreign Countries, High School Students, College Bound Students, Physics
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Huang, Fang; Teo, Timothy; Scherer, Ronny – Interactive Learning Environments, 2022
As a key variable determining technology acceptance and adoption, the perceived ease of technology use (PEU) has been in the focus of a considerable body of research. This research examined the external factors that influence perceived ease of use, such as computer self-efficacy and perceived enjoyment, but yielded inconsistent findings and…
Descriptors: College Students, Internet, Electronic Learning, Usability
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Yu-Shan Ting; Yu-chu Yeh – Interactive Learning Environments, 2024
To date, few online game-based learning studies have focused on developing children's growth creativity mindset (growth CM). This study, therefore, aimed to develop a game-based learning system to help children develop their growth CM. Additionally, we investigated the relationship between growth CM, hope belief, and creativity self-efficacy after…
Descriptors: Student Attitudes, Goal Orientation, Intervention, Beliefs
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Qing Yu; Bao-min Li; Qi-yun Wang – Interactive Learning Environments, 2024
In recent years, 3D holographic technology (3DHT) has attracted more and more attention from the field of education, bringing new opportunities to reform the delivery of instruction and learning. Whether the application of 3D holographic technology can effectively improve student learning performance has become a pendent issue. In this study, a…
Descriptors: Visual Aids, Technology, Learning Processes, Meta Analysis
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