Efficacy of Annotated Video-Based Learning Environment for Drawing Students’ Attention to Construction Practice Concepts

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.