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            Chapter Evaluation of Computer Vision-Aided Multimedia Learning in Construction Engineering Education

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            Author(s)
            Yusuf, Anthony
            Afolabi, Adedeji
            Akanmu, Abiola
            Olayiwola, Johnson
            Language
            English
            Show full item record
            Abstract
            Due to the practice-oriented nature of construction engineering education and barriers associated with physical site visits, videos are invaluable means to expose students to practical curricula content. Prior studies have investigated various design principles of multimedia pedagogical tools to enhance student learning and reduce cognitive load. These design principles and computer vision techniques can afford the design and usage of a multimedia learning environment with annotated content to teach students construction safety practices. Hence, using subjective and objective measures such as self-reported cognitive load, eye tracking metrics and verbal feedback, this study assesses the effectiveness of a computer vision-aided multimedia learning environment as well as examines variations across students’ demographics. Students were exposed to both annotated and unannotated versions of the learning environment. The annotated version of the learning environment was considered more effective in triggering students’ attention to learning content, but higher cognitive load levels were reported by participants. The same demographic groups that dwelled longer and on more annotated areas of interest also reported higher overall cognitive load. Keeping with individual differences principle of multimedia learning, demographic variations in participants' cognitive load and effectiveness of the learning environment were reported. The study provides implications for instructors in construction engineering programs on effective use of computer vision-aided annotated videos as instructional materials. This study could serve as a benchmark for future studies on artificial intelligence techniques for signaling in multimedia learning. This study reveals the affordances of computer vision-aided multimedia learning in construction engineering education and the need for adaptation of multimedia learning tools to students’ demographics
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/169668
            Keywords
            Computer vision; construction engineering education; demographic differences; multimedia learning; video.; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTV Virtualization
            DOI
            10.36253/979-12-215-0289-3.23
            ISBN
            9791221502893
            Publisher
            Firenze University Press
            Publisher website
            www.fupress.com/
            Publication date and place
            Florence, 2023
            Series
            Proceedings e report,
            Pages
            12
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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