Comparative Study on AutoCAD and Revit: Student Proficiency and Perception across Academic Levels

This study examines students' proficiency in AutoCAD and their perceptions of Revit within engineering programs, exploring variations across academic levels and the impact of demographic factors. Using IBM SPSS Statistics (version 27), descriptive and inferential statistical techniques were applied, including means, standard deviations, independent samples t†tests, correlation analysis, and multiple regression. Findings indicate no statistically significant differences in AutoCAD proficiency or Revit perception between first†and second†year students, suggesting that additional academic experience alone does not affect skill level or perception. A positive correlation was observed between AutoCAD proficiency and Revit perception, implying that a strong foundation in AutoCAD enhances students' confidence and openness to learning advanced software like Revit. Regression analysis further revealed that gender and academic major did not significantly predict AutoCAD proficiency or Revit perception. The high Cronbach’s Alpha (0.988) indicates strong internal consistency in the measurement scale, validating the reliability of the findings. These results highlight the importance of structured, progressive curriculum design that reinforces foundational CAD skills, facilitating smoother transitions to advanced tools and better preparing students for industry requirements. The study emphasizes the need for continuous skills reinforcement to enhance software adaptability and professional readiness in technical fields.