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
Virginia Tech/Myers Lawson School of Construction, United States
Virginia Tech/Myers Lawson School of Construction, United States - ORCID: 0000-0002-9065-4766
Virginia Tech/Myers Lawson School of Construction, United States - ORCID: 0000-0001-9145-4865
Virginia Tech/Myers Lawson School of Construction, United States - ORCID: 0000-0003-2795-6195
Titolo del capitolo
Evaluation of Computer Vision-Aided Multimedia Learning in Construction Engineering Education
Autori
Anthony Yusuf, Adedeji Afolabi, Abiola Akanmu, Johnson Olayiwola
DOI
10.36253/979-12-215-0289-3.23
Opera sottoposta a peer review
Anno di pubblicazione
2023
Copyright
© 2023 Author(s)
Licenza d'uso
Licenza dei metadati
Titolo del libro
CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality
Sottotitolo del libro
Managing the Digital Transformation of Construction Industry
Curatori
Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi
Opera sottoposta a peer review
Anno di pubblicazione
2023
Copyright
© 2023 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press
DOI
10.36253/979-12-215-0289-3
eISBN (pdf)
979-12-215-0289-3
eISBN (xml)
979-12-215-0257-2
Collana
Proceedings e report
ISSN della collana
2704-601X
e-ISSN della collana
2704-5846