Assessing The Assessments: A Case Study on the Relationship Between Theoretical, Continuous, and Practical Evaluations in an Engineering Course

Practice Paper Recommended citation: Walpita Gamage, S., & Richards, A. (2025). Assessing The Assessments: A Case Study on the Relationship Between Theoretical, Continuous, and Practical Evaluations in an Engineering Course. In Kangaslampi, R., Langie, G., Järvinen, H.-M., & Nagy, B. (Eds.), SEFI 53rd Annual Conference. European Society for Engineering Education (SEFI), Tampere, Finland. DOI: 10.5281/zenodo.17631501. This Conference Paper is brought to you for open access by the 53rd Annual Conference of the European Society for Engineering Education (SEFI) at Tampere University in Tampere, Finland. This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License. ASSESSING THE ASSESSMENTS: A CASE STUDY ON THE RELATIONSHIP BETWEEN THEORETICAL, CONTINUOUS, AND PRACTICAL EVALUATIONS IN AN ENGINEERING COURSE S H P W Gamage a,1, A Richards b a The University of South Australia, Mawson Lakes, Australia, https://orcid.org/00000001-9209-9113 b The University of South Australia, Mawson Lakes, Australia, https://orcid.org/00090008-1170-5651 Conference Key Areas: Curriculum Development and Emerging Curriculum Models in Engineering Keywords: Engineering education, Curriculum development, Assessment design, Student performance, Practice-oriented learning ABSTRACT As engineering educators strive to balance theoretical knowledge with practical skills, understanding how assessment formats drive learning outcomes is more important than ever. This study investigates the relationships between different assessment types—CSWA Test (theoretical), Continuous Assessment (quizzes), and Final Drawing (practical)—in a first-year undergraduate engineering course. Using data from 190 students, the study applies descriptive statistics, Pearson correlation analysis, multiple regression modelling, and performance classification to evaluate how these assessments relate to one another and predict student success. Findings reveal that Continuous Assessment has the strongest correlation with Final Drawing performance (r = 0.49) and was the most reliable predictor (β = 0.5689, R² = 0.240, p < 0.001), suggesting that frequent, low-stakes quizzes (continuous assessments) support the development of practical skills. In contrast, the weakest relationship was between CSWA Test and Final Drawing (r = 0.41), indicating that strong theoretical performance does not consistently translate to applied proficiency. These findings highlight the value of continuous assessments and applied learning in engineering education and emphasise the need for tailored support to accommodate diverse student needs. The study offers guidance for curriculum designers and suggests avenues for future research, such as exploring the roles of prior experience and adaptive learning tools in student success. 1 S H P W Gamage [email protected] 1 INTRODUCTION Engineering education is increasingly expected to prepare students not only to understand theoretical principles but also to apply them in real-world problem-solving contexts. However, traditional approaches have often leaned heavily on summative, theory-based assessments such as final exams, which primarily evaluate students’ conceptual understanding and analytical abilities. While these methods have value, they may not fully capture a student’s ability to transfer theoretical knowledge into practical engineering tasks, which is critical in professional settings (Dym et al., 2005; Prince & Felder, 2006). To address this, educational models such as design-based learning (DBL) and active learning (AL) have emerged as powerful alternatives. DBL integrates iterative design challenges into coursework, prompting students to apply engineering principles in real-time problem-solving scenarios (Kolodner, 2002). For example, Hmelo, Holton, and Kolodner (2000) found that students involved in design projects developed a more systematic understanding of complex systems compared to those in traditional learning settings. Mehalik, Doppelt, and Schunn (2008) also found that students engaged in DBL activities demonstrated significant improvements in science concept learning compared to those in scripted inquiry settings (teacher-dominated environments where students follow predetermined procedures to discover predefined answers). This approach has been shown to promote deeper learning, enhance conceptual understanding, and support the development of practical skills (Doppelt, 2003). Similarly, AL encourages student engagement through collaborative activities, real-time feedback, and peer instruction. A meta-analysis by Freeman et al. (2014) reported that AL can reduce failure rates in STEM education by over 10% and significantly improve student achievement. Aligned with these pedagogical innovations, assessment strategies are also evolving. Continuous assessment (CA)—which includes quizzes, assignments, and other formative feedback tools—has been widely recognised as a means of reinforcing learning, promoting retention, and identifying performance gaps early in the learning process (Nicol & Macfarlane-Dick, 2006; Brown et al., 2014; Litzinger et al., 2011). CA supports self-regulated learning and enhances student motivation, particularly in courses that involve complex technical content (Mills & Treagust, 2003). Meanwhile, practical assessments such as engineering drawing and ComputerAided Design (CAD)-based tasks evaluate essential professional skills, including design precision, and visual communication (Sorby, 2009; Chester, 2007). These skills are critical for engineering graduates, yet research shows that many students who perform well in theoretical exams often struggle with these hands-on tasks (Ekwueme, Ekon, & Ezenwa-Nebife, 2015). This disconnect suggests a need to better align assessments with the competencies expected in industry. Despite the growing adoption of innovative pedagogies such as DBL and AL, assessment practices in engineering education have not evolved at the same pace. Much of the current literature explores these instructional strategies in isolation, yet there is limited empirical evidence examining how different types of assessments— namely theoretical exams, continuous assessments, and practical evaluations— interact to influence student performance. While studies have highlighted the benefits of DBL in enhancing systems thinking and conceptual understanding (Hmelo et al., 2000; Mehalik et al., 2008) and the value of continuous assessment in reinforcing learning and engagement (Nicol & Macfarlane-Dick, 2006; Brown et al., 2014), few investigations have quantitatively compared the relationships between these assessment types within the same learning context. Moreover, research often treats theoretical knowledge and practical application as separate domains, with limited attention given to whether performance in one assessment area predicts or aligns with performance in another. As a result, it remains unclear whether success in traditional exams accurately reflects a student's readiness for applied engineering tasks, such as CAD modelling and technical drawing. It is also uncertain whether continuous assessments, which are designed to support learning incrementally, can effectively bridge the gap between conceptual mastery and practical competence. This study seeks to address these gaps by conducting a comparative analysis of student performance across three assessment types—the Certified SolidWorks Associate (CSWA) Test (theoretical), Continuous Assessment (quizzes), and Final Drawing (practical), within a first-year engineering course. By exploring how these assessments relate to each other, the study contributes to a more integrated understanding of how assessment design can support both theoretical understanding and practical skill development. This study is guided by the following research questions: 1. How do different assessment types (CSWA Test, Continuous Assessment, and Final Drawing) correlate with each other in evaluating student performance? 2. To what extent does Continuous Assessment predict success in Final Drawing compared to CSWA Test scores? 3. What are the primary performance patterns among students, and how do they differ between those excelling in theoretical versus practical assessments? Through these questions, the study contributes to a deeper understanding of how assessment design can be optimised to better reflect and support student learning in engineering education, particularly in courses that aim to balance theoretical instruction with hands-on technical competence. 2 CONTEXT AND PRACTICAL WORK 2.1 Background This study focuses on first-year engineering courses designed to develop students’ engineering drawing skills. The course integrates theoretical and practical components to create a comprehensive learning experience. Theoretical instruction is delivered through lectures and tutorials, with lectures primarily involving passive learning and tutorials incorporating critical thinking tasks to foster active engagement. The practical component centres on a design-and-build activity, where students create and manufacture a product, applying engineering principles to produce a functional artifact. Although intermediate steps such as part drawings and machining are not directly assessed, students submit a final set of engineering drawings for evaluation. This hands-on approach highlights the real-world importance of precision and accuracy in technical drawings, enabling students to experience the consequences of imprecise work while developing key problemsolving skills. Assessment in the course includes an invigilated, computer-based drawing exam (the CSWA test, 25% of the final grade), weekly CAD-based quizzes (15% total), a final technical drawing submission (10%), and prototype building, presentations, and other activities (50%, not detailed here). Continuous assessments happen in the first part of the semester, then the CSWA test, then the final drawings, in that order. The quizzes designed to provide immediate feedback to support iterative learning. All 12 quizzes contribute to the grade: six allow unlimited attempts, while the other six are limited to two attempts within a 30-minute window to encourage precision and time management. For each quiz, only the highest score is recorded. 2.2 Methodology This study adopts a quantitative approach to examine the relationships between different assessment types and student performance in a first-year engineering course. The analysis is based on anonymised data from 190 students who completed three key assessments. Descriptive statistics, including mean, median, and standard deviation, were calculated to explore overall performance trends and identify areas where students typically excelled or struggled. Score distributions were visualised using histograms and density plots to gain further insight into the spread and concentration of student performance across each assessment type. Following this, Pearson’s correlation analysis was conducted to assess the strength and direction of the relationships between the CSWA test, continuous assessment quizzes, and the final drawing submission. To further explore the predictive power of theoretical and continuous assessments on practical performance, a multiple regression analysis was conducted. To gain more understanding of student learning profiles, a performance classification approach was also employed. Students were grouped based on a 50% threshold into four categories: 1) those who performed strongly in the CSWA test but poorly in the Final Drawing; 2) those who performed well in the Final Drawing but not in the CSWA test; 3) those who performed well in both; and 4) those who struggled in both areas. This classification helped to highlight differing strengths among students and identify where additional instructional support might be needed. 3 RESULTS AND INSIGHTS The analysis of student performance across CSWA Tests, Continuous Assessment, and Final Drawing reveals key trends in theoretical and practical learning. The distribution of scores (Fig.1) highlights significant variation in student performance. CSWA Test scores were widely distributed, with a substantial number of students scoring below 50%, indicating challenges in theoretical exam performance. Continuous Assessment scores, however, were skewed towards higher values, suggesting that students generally found quizzes more manageable and beneficial for learning retention. In contrast, Final Drawing scores were the lowest, with many students scoring below 50%, reinforcing the difficulty of precision engineering drawing. These findings suggest that students benefit from frequent, structured assessment formats but may require additional instructional support in engineering drawing and CAD-based tasks to bridge the gap between theoretical knowledge and practical application. Fig. 1. Distribution of Scores in Three Assessments The correlation analysis (Table 1) provides insights into the relationships between assessment types. The strongest correlation was observed between Continuous Assessment and Final Drawing (r = 0.49), suggesting that frequent, low-stakes assessments support students in applying engineering concepts practically. The correlation between CSWA Test and Continuous Assessment (r = 0.47) was slightly weaker, indicating that students who perform well in quizzes also tend to do well in theoretical exams. In contrast, the weakest correlation was between CSWA Test and Final Drawing (r = 0.41), reinforcing the notion that theoretical exam success does not necessarily translate to strong engineering drawing performance. Table 1. The pairwise Pearson correlation coefficients Scatter plots (Fig. 2) illustrate these relationships and reveal considerable data dispersion, reflecting moderate correlations and notable variation in individual performance. This variability could be due to additional factors such as learning styles, prior experience, and problem-solving approaches, which influenced student success. CSWA Test (%) Continuous Assessment (%) Final Drawing (%) CSWA Test (%) 1 0.47 0.41 Continuous Assessment (%) 0.47 1 0.49 Final Drawing (%) 0.41 0.49 1 Fig. 2. Scatter Plots Between Each Assessment Components To further analyse student performance, students were classified based on a 50% threshold into four categories (Fig. 3): Strong in CSWA but Weak in Final Drawing (36 students), Strong in Final Drawing but Weak in CSWA (32 students), Strong in Both (48 students), and Weak in Both (74 students). The largest category comprised students who struggled in both assessments, highlighting the need for targeted instructional interventions. A notable trend was that 19% of students performed well in CSWA but struggled in Final Drawing, suggesting that theoretical knowledge alone does not guarantee proficiency in engineering drawing. Conversely, 17% students excelled in Final Drawing but underperformed in CSWA, indicating that some students thrive in applied learning environments but may struggle with theoretical assessments. These findings emphasise the importance of diversified teaching and assessment methods that integrate theoretical instruction with hands-on learning experiences to support different student learning preferences. These findings highlight the importance of differentiated instructional strategies tailored to students’ specific learning needs. For those struggling with Final Drawing, targeted interventions—such as CAD-based design workshops, structured feedback cycles, and step-by-step tutorials incorporating spatial visualisation techniques to support mental modelling—can enhance drawing precision and practical application. Conversely, students who perform well in drawing but face challenges with CSWA Tests may benefit from conceptual reinforcement through problem-solving tasks, interactive simulations, and guided discussions aimed at deepening their understanding of engineering design principles. Fig. 3. Performance Classification of Students (Threshold 50%) To quantify these relationships, regression analysis (Table 2) was conducted to determine the predictive strength of different assessments. The model examining Continuous Assessment and CSWA Test performance resulted in an R² value of 0.225 and a regression coefficient (β) of 0.5413 (p < 0.001), indicating that a 1% increase in Continuous Assessment scores is associated with a 0.54% increase in CSWA Test scores. This suggests that while continuous assessments reinforce theoretical learning, additional factors such as other exam strategies also contribute to CSWA performance. The strongest relationship was observed between Continuous Assessment and Final Drawing, with an R² value of 0.240, β = 0.5689, p < 0.001. This suggests that students who perform well in continuous assessments also tend to excel in practical applications. However, the scatter plot shows considerable variation, meaning that while quizzes reinforce learning, they do not fully guarantee strong engineering drawing performance. A 1% increase in Continuous Assessment scores is associated with a 0.57% increase in Final Drawing scores, making this the most predictive factor for students' practical success, reinforcing the importance of structured, iterative learning in developing applied engineering skills. In contrast, the weakest correlation was found between Final Drawing and CSWA Test scores (R² = 0.169, β = 0.4032, p < 0.001), indicating that strong performance in final engineering drawing does not consistently align with high scores in theoretical assessments. This inconsistency may also reflect external factors, such as students receiving assistance on their final drawing tasks. The data dispersion observed in the scatter plot supports this interpretation, confirming that practical drawing skills alone are not a reliable predictor of theoretical exam performance, and vice versa. These findings highlight the importance of a balanced curriculum that integrates both theoretical problem-solving and hands-on learning experiences. Table 2. Regression Analysis Regression Model Coefficient (𝛽𝛽) 𝑅𝑅2 Value P Value Continuous Assessment vs CSWA 0.5413 0.225 < 0.001 Continuous Assessment vs Final Drawing 0.5689 0.24 < 0.001 Final Drawing vs CSWA Test 0.4032 0.169 < 0.001 4 CONCLUSIONS AND IMPLICATIONS This study examined the relationships between invigilated CSWA Test scores, noninvigilated Continuous Assessment, and Final Drawing performance to evaluate how different assessment types influence student success in a first-year engineering course. The findings highlight the value of continuous, low-stakes assessments in supporting applied learning outcomes. Students performed best in Continuous Assessment but struggled significantly with the Final Drawing task, suggesting that while structured quizzes help reinforce theoretical knowledge, applying that knowledge through precise technical drawings remains a challenge for many. Correlation analysis confirmed that Continuous Assessment had the strongest association with Final Drawing performance (r = 0.49), while the relationship between CSWA and Final Drawing was the weakest (r = 0.41). These patterns, along with high data dispersion, indicate that student performance could be shaped by multiple factors. The results carry several important implications for curriculum design and student support in engineering education. Since Continuous Assessment emerged as the best predictor of applied performance, educators should embed structured, hands-on activities, such as CAD exercises, spatial-visualisation activities, mini design projects, and simulations throughout the term to reinforce theory and build transferable skills. Seventy-four students underperformed across both theoretical and practical tasks, underscoring the need for early, targeted support. Drawing on Hattie and Timperley’s (2007) findings that timely, actionable feedback dramatically accelerates learning, offering remedial CAD workshops, personalised tutorials, and peer-learning cohorts during the first half of semester can help at-risk learners before they face high-stakes assessments. At the same time, balancing assessment modes is crucial. Students who excel at Final drawing but underperform on CSWA tests could gain from more targeted concept‐based quizzes and problem-solving exercises. Conversely, students who are strong in theory would benefit from applied design challenges, ensuring that both analytical reasoning and creative skills are assessed equitably (Cruz, Saunders-Smits, & Groen, 2019). While the study provides valuable insights, it is limited by its focus on a single cohort within one course, which may constrain the generalisability of results. Furthermore, the study did not control for external variables that could affect student performance, and the absence of qualitative data limits understanding of student perspectives. Future research should integrate interviews or surveys to uncover how learners experience different assessment types and examine additional predictors of performance. Moreover, evaluating adaptive, AI-driven tutoring systems (Gligorea et al., 2023) could reveal how real-time feedback and personalised content impact both theoretical understanding and practical skill development. Ultimately, a well-balanced engineering curriculum—combining frequent continuous assessments, structured design tasks, and early personalised support—can bridge the gap between conceptual knowledge and practical competence, fostering greater student engagement and success. ETHICS APPROVAL This research was approved by the Human Ethic Committee, University of South Australia under reference number 206958. REFERENCES Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21(1), 5–31. https://doi.org/10.1007/s11092-008-9068-5 Brown, P. C., Roediger, H. L., & McDaniel, M. A. (2014). Make it stick: The science of successful learning. Harvard University Press. Chester, I. (2007). Teaching for CAD expertise. International Journal of Technology and Design Education, 17(1), 23–35. https://doi.org/10.1007/s10798-006-9015-z