Investigation of Progressive Learning within a Statics Course: An Analysis of Performance Retention, Critical Topics, and Active Participation

Author:

Ahmed Naveed1,Park JeeWoong1ORCID,Arteaga Cristian1,Stephen Haroon1ORCID

Affiliation:

1. Civil and Environmental Engineering and Construction, University of Nevada Las Vegas, Las Vegas, NV 89154, USA

Abstract

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.

Funder

National Science Foundation

Publisher

MDPI AG

Subject

Public Administration,Developmental and Educational Psychology,Education,Computer Science Applications,Computer Science (miscellaneous),Physical Therapy, Sports Therapy and Rehabilitation

Reference35 articles.

1. Roy, J., and Wilson, C. (2019). Engineering and Engineering Technology by the Numbers 2019, ASEE.

2. NCES (2020). Undergraduate Enrollment. Condition of Education, U.S. Department of Education, Institute of Education Sciences.

3. Aulck, L., Velagapudi, N., Blumenstock, J., and West, J. (2016). Predicting Student Dropout in Higher Education. arXiv.

4. Chen, Y., Johri, A., and Rangwala, H. (2018, January 7–9). Running out of STEM. Proceedings of the 8th International Conference on Learning Analytics and Knowledge, Sydney, Australia.

5. Factors that determine the persistence and dropout of university students;Casanova;Psicothema,2018

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