Examining the Influence of Using First-Person View Drones as Auxiliary Devices in Matte Painting Courses on College Students' Continuous Learning Intention

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Title: Examining the Influence of Using First-Person View Drones as Auxiliary Devices in Matte Painting Courses on College Students' Continuous Learning Intention
Authors: Gu, Chao (ORCID 0000-0002-9810-3168), Sun, Jie (ORCID 0000-0002-5923-9126), Chen, Tong, Miao, Wei, Yang, Yunshuo, Lin, Shuyuan, Chen, Jiangjie (ORCID 0000-0002-2613-0386)
Source: Journal of Intelligence. 2022 10.
Availability: MDPI AG. Klybeckstrasse 64, 4057 Basel, Switzerland. e-mail: indexing@mdpi.com; e-mail: jintelligence@mdpi.com; Web site: https://www.mdpi.com/journal/jintelligence
Peer Reviewed: Y
Page Count: 24
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Art Education, Painting (Visual Arts), Robotics, Aviation Technology, Educational Technology, Student Interests, Intention, Program Effectiveness, Technology Uses in Education, Perspective Taking, Interaction, Visual Perception, Computer Simulation, College Students, Foreign Countries, Trust (Psychology)
Geographic Terms: China
ISSN: 2079-3200
Abstract: In terms of the teaching process of matte painting, it is essential for students to develop a sound understanding of the relationship between virtual and physical environments. In this study, first-person view (FPV) drones are applied to matte painting courses to evaluate the effectiveness of the teaching, and to propose more effective design suggestions for FPV drones that are more suitable for teaching. This provides students with a better learning environment using a digital education system. The results of the study indicate that the flow experience, learning interest, and continuous learning intention of students who use FPV drones in matte painting are significantly greater than those of students who only utilize traditional teaching methods. Furthermore, the technology incentive model (TIM) was developed in this study after being verified by the structural equation model. The results demonstrate that the second-order construct 'technology incentive' comprising perceived interactivity, perceived vividness, and novel experience positively influence students' learning interest and continuous learning intentions under the mediation of flow experience.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1354157
Database: ERIC
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  Data: Examining the Influence of Using First-Person View Drones as Auxiliary Devices in Matte Painting Courses on College Students' Continuous Learning Intention
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  Data: <searchLink fieldCode="AR" term="%22Gu%2C+Chao%22">Gu, Chao</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9810-3168">0000-0002-9810-3168</externalLink>)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Jie%22">Sun, Jie</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5923-9126">0000-0002-5923-9126</externalLink>)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Tong%22">Chen, Tong</searchLink><br /><searchLink fieldCode="AR" term="%22Miao%2C+Wei%22">Miao, Wei</searchLink><br /><searchLink fieldCode="AR" term="%22Yang%2C+Yunshuo%22">Yang, Yunshuo</searchLink><br /><searchLink fieldCode="AR" term="%22Lin%2C+Shuyuan%22">Lin, Shuyuan</searchLink><br /><searchLink fieldCode="AR" term="%22Chen%2C+Jiangjie%22">Chen, Jiangjie</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2613-0386">0000-0002-2613-0386</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Intelligence%22"><i>Journal of Intelligence</i></searchLink>. 2022 10.
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  Data: MDPI AG. Klybeckstrasse 64, 4057 Basel, Switzerland. e-mail: indexing@mdpi.com; e-mail: jintelligence@mdpi.com; Web site: https://www.mdpi.com/journal/jintelligence
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
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  Data: 2079-3200
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  Data: In terms of the teaching process of matte painting, it is essential for students to develop a sound understanding of the relationship between virtual and physical environments. In this study, first-person view (FPV) drones are applied to matte painting courses to evaluate the effectiveness of the teaching, and to propose more effective design suggestions for FPV drones that are more suitable for teaching. This provides students with a better learning environment using a digital education system. The results of the study indicate that the flow experience, learning interest, and continuous learning intention of students who use FPV drones in matte painting are significantly greater than those of students who only utilize traditional teaching methods. Furthermore, the technology incentive model (TIM) was developed in this study after being verified by the structural equation model. The results demonstrate that the second-order construct 'technology incentive' comprising perceived interactivity, perceived vividness, and novel experience positively influence students' learning interest and continuous learning intentions under the mediation of flow experience.
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  Data: 2022
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  Data: EJ1354157
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        PageCount: 24
    Subjects:
      – SubjectFull: Art Education
        Type: general
      – SubjectFull: Painting (Visual Arts)
        Type: general
      – SubjectFull: Robotics
        Type: general
      – SubjectFull: Aviation Technology
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      – SubjectFull: Educational Technology
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      – SubjectFull: Student Interests
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      – SubjectFull: Intention
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      – SubjectFull: Program Effectiveness
        Type: general
      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Perspective Taking
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      – SubjectFull: Interaction
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      – SubjectFull: Visual Perception
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      – SubjectFull: Computer Simulation
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      – SubjectFull: College Students
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Trust (Psychology)
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      – SubjectFull: China
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      – TitleFull: Examining the Influence of Using First-Person View Drones as Auxiliary Devices in Matte Painting Courses on College Students' Continuous Learning Intention
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            NameFull: Sun, Jie
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