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Showing 1 to 15 of 32 results Save | Export
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Fatih Balaman; Muhammet Bas – Interactive Learning Environments, 2023
This study is aimed to develop a scale that measures university students' perception of using e-learning platforms by using the Technology Acceptance Model (TAM). The sample consisted of 636 university students. The Exploratory Factor Analysis (EFA) results revealed 5-factors on a 6-items scale. The five factors that were revealed on the EFA…
Descriptors: Electronic Learning, Computer Attitudes, College Students, Usability
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Asselman, Amal; Khaldi, Mohamed; Aammou, Souhaib – Interactive Learning Environments, 2023
Performance Factors Analysis (PFA) is considered one of the most important Knowledge Tracing (KT) approaches used for constructing adaptive educational hypermedia systems. It has shown a high prediction accuracy against many other KT approaches. While, the desire to estimate more accurately the student level leads researchers to enhance PFA by…
Descriptors: Algorithms, Artificial Intelligence, Factor Analysis, Student Behavior
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Joseph Hin Yan Lam; Shelley Xiuli Tong – Interactive Learning Environments, 2023
Despite the increasing popularity of online learning in elementary and primary schools, it is unclear to which extent that students' attitudes toward online learning influence their learning progress and outcomes. In this study, the Online Learning Attitude Questionnaire (OLAQ) was developed and validated to measure students' online learning…
Descriptors: Elementary School Students, Child Caregivers, Foreign Countries, Measures (Individuals)
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Diem Thi Ngoc Hoang; Huy Phung; Nhi Tran – Interactive Learning Environments, 2023
With the increasing significance of technology use in both daily life and education, the digital native assessment scale (DNAS) [developed by Teo, T. (2013). An initial development and validation of a Digital Natives Assessment Scale (DNAS). Computers & Education, 67, 51-57.] has been widely used as a tool to investigate the digital nativeness…
Descriptors: Digital Literacy, Preservice Teachers, Foreign Countries, Likert Scales
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Li, Na; Zhang, Xiaojun; Limniou, Maria – Interactive Learning Environments, 2023
Although virtual learning environments (VLEs) have long been forecasted to accelerate the educational revolution, their adoption by teachers and students has not always been as effective as is expected over the years. This challenges universities that extensively investigated educational technologies. Stakeholders are keen to understand the…
Descriptors: Educational Technology, Technology Uses in Education, Technology Integration, Adoption (Ideas)
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Bhagat, Kaushal Kumar; Cheng, Chia-Hui; Koneru, Indira; Fook, Fong Soon; Chang, Chun-Yen – Interactive Learning Environments, 2023
The aim of this study was to develop a scale to measure students' blended learning course experience. A total of 792 undergraduate students from Malaysia participated in this study. Exploratory factor analysis (EFA) was employed to evaluate the factor structure of the scale. As a result of EFA, three factors with 19 items that explained 68.06% of…
Descriptors: Blended Learning, Evaluation Methods, Course Evaluation, Student Attitudes
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Watcharapol Wiboolyasarin; Nattawut Jinowat; Kanokpan Wiboolyasarin; Ruedee Kamonsawad – Interactive Learning Environments, 2024
A three-dimensional virtual world (henceforth, 3DVW) is a novel phenomenon with enormous potential as a virtual community for broadening meaningful life experiences. Previous 3DVW research, however, has not addressed the determinants that influence L2 students' expectations. The primary goal of this study was to employ a combination of exploratory…
Descriptors: Computer Simulation, Technology Uses in Education, Preservice Teachers, Second Language Learning
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Lihui Sun; Zhen Guo; Danhua Zhou – Interactive Learning Environments, 2024
Coding ability has become an essential digital skill for young children. The graphical programming environment is valuable carrier for cultivating children's coding ability. The purpose of this study is to develop a coding ability test for children, to conduct a graphic coding intervention, and to further explore the impact of multiple factors on…
Descriptors: Programming, Skill Development, Intervention, Student Experience
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Lee, Chwee Beng – Interactive Learning Environments, 2018
With the rapid developments in emerging technologies and the emphasis on technologies in learning environments, the connection between technologies and meaningful learning has strengthened. Developing an understanding of the components of meaningful learning with technology is pivotal, as this may enable educators to make more informed decisions…
Descriptors: High School Students, Measures (Individuals), Test Construction, Technology Uses in Education
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Bagriacik Yilmaz, Ayse; Karatas, Serçin – Interactive Learning Environments, 2018
The aim of this study was to develop a measurement instrument which is compatible with literature, of which validity and reliability are proved with the aim of determining interaction perceived by learners in online learning environments. Accordingly, literature review was made, and outline form of the scale was formed with item pool by taking 14…
Descriptors: Foreign Countries, College Students, Likert Scales, Computer Mediated Communication
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Angeli, Charoula; Schwartz, Neil H. – Interactive Learning Environments, 2016
Two hundred and eighty undergraduates from universities in two countries were asked to read didactic material, and then think and write about potential solutions to an ill-defined problem. The writing was conducted within a synchronous or asynchronous computer-mediated communication (CMC) environment. Asynchronous CMC took the form of email…
Descriptors: Asynchronous Communication, Synchronous Communication, Computer Mediated Communication, Foreign Countries
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Pribeanu, Costin; Balog, Alexandru; Iordache, Dragos Daniel – Interactive Learning Environments, 2017
Augmented reality (AR) technologies could enhance learning in several ways. The quality of an AR-based educational platform is a combination of key features that manifests in usability, usefulness, and enjoyment for the learner. In this paper, we present a multidimensional model to measure the quality of an AR-based application as perceived by…
Descriptors: Computer Simulation, Educational Technology, Measurement, Educational Quality
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Zhang, Min; Liu, Yupei; Yan, Weiwei; Zhang, Yan – Interactive Learning Environments, 2017
Users' continuance intention plays a significant role in the process of information system (IS) service, especially virtual learning community (VLC) services. Following the IS success model and IS post-acceptance model, this study explores the determinants of users' intention to continue using VLCs' service from the perspective of quality,…
Descriptors: Virtual Classrooms, Intention, College Students, Student Surveys
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Sharma, Sujeet Kumar; Sarrab, Mohamed; Al-Shihi, Hafedh – Interactive Learning Environments, 2017
The growth of Smartphone usage, increased acceptance of electronic learning (E-learning), the availability of high reliability mobile networks and need for flexibility in learning have resulted in the growth of mobile learning (M-learning). This has led to a tremendous interest in the acceptance behaviors related to M-learning users among the…
Descriptors: Test Construction, Test Validity, Measures (Individuals), Surveys
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Jeong, Hye In; Kim, Yeolib – Interactive Learning Environments, 2017
This study investigated kindergarten teachers' decision-making process regarding the acceptance of computer technology. We incorporated the Technology Acceptance Model framework, in addition to computer self-efficacy, subjective norm, and personal innovativeness in education technology as external variables. The data were obtained from 160…
Descriptors: Teacher Attitudes, Technological Literacy, Self Efficacy, Guidelines
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