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Afzali Borujeni, S H, Zare, M and Adelzade Saadabadi, L (2024) Comparison of factors affecting the acceptance of the trenchless technology and open-trench method using ANP and AHP: Case study in Iran. Journal of Construction Engineering and Management, 150(01).
Aghililotf, M, Ramezanianpour, A M, Arbabi, H and Maghrebi, M (2024) Identifying construction managers' challenges: A novel approach based on social network analysis. Journal of Construction Engineering and Management, 150(01).
Alikhani, H and Latifi, M (2024) Evaluation of the healing performance of hot-mix asphalt containing waste steel shavings under different microwave induction healing cycles. Journal of Construction Engineering and Management, 150(01).
Anwer, S, Li, H, Antwi-Afari, M F, Mirza, A M, Rahman, M A, Mehmood, I, Guo, R and Wong, A Y L (2024) Evaluation of data processing and artifact removal approaches used for physiological signals captured using wearable sensing devices during construction tasks. Journal of Construction Engineering and Management, 150(01).
Arowoiya, V A, Oke, A E, Ojo, L D and Adelusi, A O (2024) Driving factors for the adoption of digital twin technology implementation for construction project performance in Nigeria. Journal of Construction Engineering and Management, 150(01).
D'Orazio, M, Bernardini, G and Di Giuseppe, E (2024) Improving sustainable management of university buildings based on occupancy data. Journal of Construction Engineering and Management, 150(01).
Da Silva, W O P, Farias, B A, Monteiro, I B, Pegorini, V, Casanova, D and Bisconsini, D R (2024) Development of global quality index of unpaved roads. Journal of Construction Engineering and Management, 150(01).
Ding, S, Hu, H, Chai, Z and Wang, W (2024) Secure and formalized blockchain-IPFS information sharing in precast construction from the whole supply chain perspective. Journal of Construction Engineering and Management, 150(01).
Garcia-Lopez, N P and Fischer, M (2024) Managing on-site production using an activity and flow-based construction model. Journal of Construction Engineering and Management, 150(01).
Jalloul, H, Choi, J, Manheim, D, Yesiller, N and Derrible, S (2024) Incorporating disaster debris into sustainable construction research and practice. Journal of Construction Engineering and Management, 150(01).
Koc, K, Budayan, C, Ekmekcioǧlu, Ö and Tokdemir, O B (2024) Predicting cost impacts of nonconformances in construction projects using interpretable machine learning. Journal of Construction Engineering and Management, 150(01).
Leung, M Y, Wei, X and Ojo, L D (2024) Developing a value-risk management model for construction projects. Journal of Construction Engineering and Management, 150(01).
Liu, Y, Wang, X, Guo, S, Shi, X and Wang, D (2024) Analyzing the optimization of subsidies for PPP urban rail transit projects: A choice between passenger demand, vehicle kilometer, or an improved efficiency-oriented framework. Journal of Construction Engineering and Management, 150(01).
Miao, K, Lou, W, Schonfeld, P and Xiao, Z (2024) Optimal earthmoving-equipment combination considering carbon emissions with an indicator-based multiobjective optimizer. Journal of Construction Engineering and Management, 150(01).
Ning, X, Zhai, F, Xia, N and Hu, X (2024) Protecting the ego: Anticipated image risk as a psychological deterrent to construction workers' safety citizenship behavior. Journal of Construction Engineering and Management, 150(01).
Olayiwola, J, Yusuf, A, Akanmu, A, Gonsalves, N and Abraham, Y (2024) Efficacy of annotated video-based learning environment for drawing students' attention to construction practice concepts. Journal of Construction Engineering and Management, 150(01).
- Type: Journal Article
- Keywords: annotated videos; cognitive load; construction engineering education; demographic differences; practice concepts
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-13778
- Abstract:
To enhance students' learning of construction practice, instructors use videos as multimedia pedagogical tools to bring practical experience into the classroom. However, cognitive load levels, individual differences, and multimedia design principles are important considerations in the effective use of videos for instruction. Therefore, this study investigates the effectiveness of an artificial intelligence (AI)-annotated video in guiding students' attention to important construction practice concepts. Students were exposed to both annotated and unannotated videos illustrating construction safety practices. Eye tracking metrics and self-reported cognitive load were collected as students interacted with both learning environments. The effectiveness of the videos in drawing students' attention were compared. The AI-annotated video was considered effective and the variations across individual differences were reported. No significant difference was observed in the cognitive loads of both learning environments. This study provides an understanding of the extent to which learners of different demographic characteristics allocate attention to signaled practice concepts. This study also illustrates the impact of the signaled concepts on learners' cognitive loads. This study contributes to existing theories by elucidating how practice knowledge could be adapted to meet construction engineering students' learning needs.
Salih, F, Eissa, R and El-Adaway, I H (2024) Data-driven analysis of progressive design build in water and wastewater infrastructure projects. Journal of Construction Engineering and Management, 150(01).
Zhong, B, Shen, L, Pan, X, Zhong, X and He, W (2024) Dispute classification and analysis: Deep learning-based text mining for construction contract management. Journal of Construction Engineering and Management, 150(01).