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Previous research has demonstrated a link between prior knowledge and student success in engineering courses. However, while course-to-course relations exist, researchers have paid insufficient attention to internal course performance development. This study aims to address this gap—designed to quantify and thus extract meaningful insights—by examining a fundamental engineering course, Statics, from three perspectives: (1) progressive learning reflected in performance retention throughout the course; (2) critical topics and their influence on students’ performance progression; and (3) student active participation as a surrogate measure of progressive learning. By analyzing data collected from 222 students over five semesters, this study draws insights on student in-course progressive learning. The results show that early learning had significant implications in building a foundation in progressive learning throughout the semester. Additionally, insufficient knowledge on certain topics can hinder student learning progression more than others, which eventually leads to course failure. Finally, student participation is a pathway to enhance learning and achieve excellent course performance. The presented analysis approach provides educators with a mechanism for diagnosing and devising strategies to address conceptual lapses for STEM (science, technology, engineering, and mathematics) courses, especially where progressive learning is essential. 

The number of buildings is increasing day by day. The next logical footstep is tackling challenges regarding scarcity of resources and sustainability, as well as shifting focus on existing building structures to renovate and retrofit. Many existing old and heritage buildings lack documentation, such as building models, despite their necessity. Technological advances allow us to use virtual reality, augmented reality, and mixed reality on mobile platforms in various aspects of the construction industry. For these purposes, having a BIM model or high detail 3D model is not always necessary, as a simpler model can serve the purpose within many mobile platforms. This paper streamlines a framework for generating a lightweight 3D model for mobile platforms. In doing so, we use an existing structure’s site survey data for the foundation data, followed by mobile VR implementation. This research conducted a pilot study on an existing building. The study provides a process of swiftly generating a lightweight 3D model of a building with relative accuracy and cost savings.