Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Civil Engineering
13
10.18260/1-2--37892
https://peer.asee.org/37892
358
Dr. Haroon Stephen is Associate Professor in the Department of Civil and Environmental Engineering at the University of Nevada Las Vegas (UNLV). He is interested in interdisciplinary research of climate change impact and hydrology with specific emphasis on applications of remote sensing and geographic information systems (GIS) and specific focus on safeguarding and improving urban quality of life. He has received university level UNLV Foundation Distinguished Teaching Award (2017) and Alex G. and Faye Spanos Distinguished Teaching Award (2015); Outstanding Teacher Award from the College of Engineering (2014); and Outstanding Teacher Award from the Department of Civil and Environmental Engineering and Construction (2014). Currently, he is lead PI of a $2.5M National Science Foundation project titled “Enhancing Critical Transitions in Civil Engineering Degree”.
Jee Woong Park earned his master’s degree and doctoral degree in civil engineering from Stanford University and Georgia Institute of Technology. He is currently working as an assistant professor within the Department of Civil and Environmental Engineering and Construction at the University of Nevada, Las Vegas.
Cristian Arteaga is a Ph.D. candidate at the University of Nevada Las Vegas, UNLV. In 2015, Cristian received a B.S. in Computer Science from University of Cauca Colombia and in 2017, a M.S. in Civil & Environmental Engineering from UNLV. His current research interests include the application of computational tools and data modeling techniques to traffic and construction safety problems. His work has been published in reputable journals such as the Journal of Safety Science and the Transportation Research Part C Journal.
In engineering, students’ completion of prerequisites indicates an understanding of fundamental knowledge. Recent studies have shown a significant relationship between student performance and prior knowledge. Weak knowledge retention from prerequisite coursework can present challenges in progressive learning. This study investigates the relationship between prior knowledge and students’ performance over a few courses of Statics. Statistics has been considered as the subject of interest since it is the introductory engineering course upon which many subsequent engineering courses rely, including many engineering analysis and design courses. The prior knowledge was determined based on the quantitative and qualitative preparedness. A quiz set was designed to assess quantitative preparedness. The qualitative preparedness was assessed using a survey asking students’ subjective opinions about their preparedness at the beginning of the semester. Student performance was later quantified through final course grades. Each set of data were assigned three categories for grouping purposes to reflect preparedness: 1) high preparedness: 85% or higher score, 2) medium preparedness: between 60% and 85%, and 3) weak preparedness: 60% or lower. Pearson correlation coefficient and T-test was conducted on 129 students for linear regression and differences in means. The analysis revealed a non-significant correlation between the qualitative preparedness and final scores (p-value = 0.29). The data revealed that students underestimated their understanding of the prerequisites for the class, since the quantitative preparedness scores were relatively higher than the qualitative preparedness scores. This can be partially understood by the time gap between when prerequisites were taken and when the course under investigation was taken. Students may have felt less confident at first but were able to pick up the required knowledge quickly. A moderately significant correlation between students’ quantitative preparedness and course performance was observed (p -value < 0.05). Students with high preparedness showed >80% final scores, with a few exceptions; students with weak preparedness also showed relatively high final scores. However, most of the less prepared students made significant efforts to overcome their weaknesses through continuous communication and follow-up with the instructor. Despite these efforts, these students could not obtain higher than 90% as final scores, which indicates that level of preparedness reflects academic excellence. Overall, this study highlights the role of prior knowledge in achieving academic excellence for engineering. The study is useful to Civil Engineering instructors to understand the role of students’ previous knowledge in their understanding of difficult engineering concepts.
Saher, R., & Stephen, H., & Park, J. W., & Arteaga Sanchez, C. D. (2021, July), The Role of Prior Knowledge in the Performance of Engineering Students Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37892
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