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Chih-Hsing Liu; Jeou-Shyan Horng; Sheng-Fang Chou; Tai-Yi Yu; Yung-Chuan Huang; Yen-Ling Ng; Jun-You Lin – Interactive Learning Environments, 2024
The current study provides an integrated comprehensive analysis of mediation-moderation models to understand 567 tourism and hospitality students' viewpoints by exploring multidisciplinary contributions relevant to the big data and new technology application bodies of literature. The results show that self-efficacy was the primary motivation…
Descriptors: Foreign Countries, College Students, Tourism, Hospitality Occupations
Chi-Tung Chen; Chih-Ming Chen; Hsiao-Ting Tsai – Interactive Learning Environments, 2024
This study utilised the instant semantic analysis and feedback system (ISAFS) to assist learners in the online discussion learning activities of socio-scientific issues (SSIs) and to document their learning process behaviours for behavioural analyses. The aim was to understand the learners' discussion behaviours during the ISAFS assisted learning…
Descriptors: Behavior Patterns, Electronic Learning, Discussion, Instructional Effectiveness
Chou, Yi-Shiuan; Hou, Huei-Tse; Chang, Kuo-En; Su, Chien-Lun – Interactive Learning Environments, 2023
This study proposed a cognitive-based game mechanism based on the revised Bloom's taxonomy of cognitive processing dimensions. Moreover, a mobile Chinese history educational game, Void Broken: The Qing Dynasty, was developed based on the cognitive-based game mechanism to promote learners' cognitive thinking in history learning. This empirical…
Descriptors: Cognitive Processes, Handheld Devices, Electronic Learning, Thinking Skills
Yang, Tzu-Chi; Chen, Sherry Y. – Interactive Learning Environments, 2023
Individual differences exist among learners. Among various individual differences, cognitive styles can strongly predict learners' learning behavior. Therefore, cognitive styles are essential for the design of online learning. There are a variety of cognitive style dimensions and overlaps exist among these dimensions. In particular, Witkin's field…
Descriptors: Student Behavior, Educational Technology, Electronic Learning, Cognitive Style
Yu-Yin Wang; Yu-Wei Chuang – Interactive Learning Environments, 2024
A review of the literature shows that much academic effort has been expended studying information system usage and information technology adoption. However, these theories/models based on psychological research are not specific to the virtual reality context and may not fully capture the nature of virtual reality-based learning system (VR-BLS)…
Descriptors: Computer Simulation, Electronic Learning, Technology Uses in Education, Learning Management Systems
Chang, Jui-Hung; Chiu, Po-Sheng; Lai, Chin-Feng – Interactive Learning Environments, 2023
In recent years, governments have paid much more attention to online learning platforms. This study establishes a high-performance agricultural digital learning platform (hereafter referred to as the Platform), in an attempt to (1) achieve learning diversity, improve users' learning ability and willingness to learn, and unblocking…
Descriptors: Online Courses, Educational Technology, Agricultural Education, Electronic Learning
Sherry Y. Chen; Chia-Yi Tseng; Chao-Yang Cheng – Interactive Learning Environments, 2023
This study proposed a three-tier test to help students learn English grammar. To reduce students' anxiety, game-based learning was incorporated into the three-tier test, where personalization was also implemented to accommodate students' different needs. More specifically, we developed a Personalized Entertaining Three-Tier Test (PET3), which…
Descriptors: English (Second Language), Language Tests, Grammar, Game Based Learning
Chih-Ming Chen; Ming-Chaun Li; Cheng-Kai Liao – Interactive Learning Environments, 2023
Computer supported collaborative writing (CSCW), due to the potential to enhance online collaborative writing performance, has received more and more attention in educational settings in recent years. However, the lack of social presence results in learners not being able to construct group awareness to reduce participation rate and even appear…
Descriptors: Electronic Learning, Interaction, Collaborative Writing, Group Behavior
Wu, Sheng-Yi; Wang, Shu-Ming – Interactive Learning Environments, 2023
Efficient collaborative learning relies on productive interaction among learners. Previous studies have suggested that group gender composition might affect the group dynamics. While previous studies have generally focused on the learning performance of different gender groups, relatively little effort has been devoted to scrutinising the learning…
Descriptors: Cooperative Learning, Social Media, Grouping (Instructional Purposes), Cognitive Processes
I-Fan Liu; Hui-Chun Hung; Che-Tien Liang – Interactive Learning Environments, 2024
With the rise of big data, artificial intelligence, and other emerging information technologies, an increasing number of students without computer science (CS) backgrounds have begun to learn programming. Programming is considered a complex task for beginners, and instructors find it difficult to quickly address all the problems that students…
Descriptors: Programming, Student Attitudes, Blended Learning, Video Technology
Lai, Horng-Ji – Interactive Learning Environments, 2017
The purpose of this study was to investigate the decisions of civil servants to use Web 2.0 applications while engaging in online learning. The participants were 439 civil servants enrolled in asynchronous online learning programs, using an e-learning portal provided by Taiwan's Regional Civil Service Development Institute. The participants…
Descriptors: Government Employees, Web 2.0 Technologies, Behavior Theories, Electronic Learning
Huang, Anna Y. Q.; Lu, Owen H. T.; Huang, Jeff C. H.; Yin, C. J.; Yang, Stephen J. H. – Interactive Learning Environments, 2020
In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model,…
Descriptors: Academic Achievement, Data Use, Learning Analytics, Classification
Wu, Sheng-Yi; Chen, Sherry Y.; Hou, Huei-Tse – Interactive Learning Environments, 2016
Concept maps can be used as a cognitive tool to assist learners' knowledge construction. However, in a concept map-based online discussion environment, studies that take into consideration learners' manipulative actions of composing concept maps, cognitive process among learners' discussion, and social knowledge construction at the same time are…
Descriptors: Concept Mapping, Computer Mediated Communication, Teaching Methods, Cognitive Processes
Yu, Fu-Yun – Interactive Learning Environments, 2022
An online system leveraging self-explanation was developed. The theoretical basis and design principles guiding the development of the system were explicated. Four evaluation studies were conducted to assess the student-generated explanations component accompanying student-generated questions (SQG) and the embedded designs. The analyzed data…
Descriptors: Integrated Learning Systems, Teaching Methods, Peer Relationship, Computer Mediated Communication
Hsu, Chung-Yuan; Chiou, Guo-Li; Tsai, Meng-Jung – Interactive Learning Environments, 2019
This study was to investigate the role of students' game self-efficacy in their game performance as well as in their visual behavior distributions and transfer patterns during their gameplay. A total of 48 university students were recruited for participating in a gameplaying task while wearing with an ASL Mobile Eye eye-tracker. After the…
Descriptors: Game Based Learning, Self Efficacy, Eye Movements, Attention

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