In the dynamic context of e-learning, the reliability of assessment methods is crucial for ensuring academic integrity and accurately measuring educational outcomes. This study explores using Cronbach’s alpha to evaluate the reliability of e-learning assessments, with practical implications for educators and professionals. We adopted a quantitative approach, analyzing test results from a comprehensive end-of-semester examination in a third-year computer science course focusing on database management systems. The course utilized Moodle-based learning management system (LMS) for delivering and assessing various types of questions, including multiple-choice, short answers, and problem-solving tasks, across four student groups, each comprising 30 students. Our methodology centered on calculating Cronbach’s alpha to assess the internal consistency of the test items using a Python script. The results indicated a Cronbach’s alpha of 0.832, signifying a high level of internal consistency. This suggests that the test items effectively measure the intended knowledge constructs, with direct implications for designing and evaluating e-learning assessments. The findings highlight Cronbach’s alpha’s essential role in enhancing the reliability of online assessments, advocating for its continued application in evaluating e-learning environments. This study improves e-learning methodologies by reinforcing the reliability and educational effectiveness of digital assessments, making it directly applicable to educators and professionals. #COMESYSO1120.