Complementing the theoretical concepts taught in the classroom with practice has been known to enhance students' contextual understanding of the subject matter. Exposing students to practical knowledge is crucial as employers are expressing discontent with the skills of newly hired graduates. In construction education, site visits have been identified as one of the most effective tools to support theory with practice. While site visits allow students to observe construction projects and engage with field personnel, numerous barriers limit its use as an effective educational tool. For instance, there are safety, cost, schedule, and weather constraints, in addition to the logistics of accommodating large class sizes. As a result, instructors employ videos of construction projects as an alternative to physical site visits. However, videos alone are insufficient to draw students' attention to essential practice concepts. Annotations can be used to attract students' attention to practical knowledge while reducing distractions and assumptions. Leveraging on the recent progress in computer vision techniques, this study presents an AI-annotated video learning tool that instructors can utilize to equip students with practice knowledge when there is limited access to physical construction sites. First, this study investigated the construction practice concepts that industry practitioners would want students to know when engaging them in site visits. Afterward, the design and development of the AI-annotated learning tool were guided by the identified practice concepts, cognitive theory of multimedia learning, and dual coding theory. To determine if the learning tool can call students' attention to annotated practice concepts in videos, a usability evaluation was conducted. Finally, this research investigated the influence of individual differences that could contribute to how learners notice practice concepts in videos. This study contributes to the body of knowledge by identifying what construction professionals notice about their work and what they would like students to notice about construction practice. This study reveals that annotations of learning contents in construction videos can direct students' focus to the annotated contents, thereby contributing to the cognitive theory of multimedia learning and dual coding theory. By leveraging machine learning classification algorithms, this research identified the extent to which individual differences such as gender, academic program, and cognitive load can be detected from the ways students notice information in construction videos. Results from this research provide opportunities for researchers to further advance the potential of annotated videos in the construction domain and other fields that employ video as a learning tool. / Doctor of Philosophy / Instructors often support classroom teaching with practical experiences to enhance students' understanding. This is especially important as employers are expressing discontent with the skills of fresh graduates. In construction engineering education, taking students to construction sites to observe the processes and operations is one of the common ways of providing students with these practical experiences. However, barriers such as safety concerns, cost, schedule, weather constraints, and the logistics of accommodating large class sizes make it challenging to engage students in construction site visits. Owing to these barriers, instructors utilize construction site videos instead of physical site visit experiences. Despite the benefits of using videos to teach, research has shown that presenting videos only to students might not be sufficient for learning as relevant and irrelevant information are usually present in videos. Therefore, calling out relevant information in videos would enable students to focus on them, enhancing their learning. To this end, this study presented a video-based learning tool that instructors can utilize to provide students with site visit experiences. In the environment, important information are called out using boundary boxes and texts. To achieve this, first, the study identified the practical knowledge that industry experts would want students to know about construction sites. Then, the identified information was annotated in construction videos via the guidance of learning theories such as the cognitive theory of multimedia learning and dual coding theory. A usability evaluation was conducted to test if students could notice the annotated contents in the video. Afterward, individual differences such as gender, academic program, and mental workload that could contribute to how students would notice annotated information in construction videos were investigated. The study contributes to the practical concepts learners need to acquire to prepare them for the workforce. Additionally, this study proved that annotating important information in videos can direct student attention to those contents. Furthermore, to make learning environments flexible for different learners, this study identified the extent to which individual differences such as gender, academic programs, and cognitive loads can be recognized from the way learners notice annotated contents of videos. Finally, the outcomes of this study would make it possible for other researchers to further advance the potentiality of teaching with annotated videos in the construction domain and other related fields.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/113138 |
| Date | 11 January 2023 |
| Creators | Olayiwola, Johnson Tumininu |
| Contributors | Myers-Lawson School of Construction, Akanmu, Abiola Abosede, Gao, Xinghua, Murzi Escobar, Homero Gregorio, Afsari, Kereshmeh |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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