The rapid advancement of educational technology has transformed the way Computer Science is taught in higher education. Traditional lecture-based teaching methods, though effective for delivering theoretical concepts, often lack interactive and practical engagement required in programming courses. Blended learning, which combines conventional face-to-face instruction with online learning resources, offers a promising alternative by promoting flexibility, interactivity, and active student participation. This study evaluates the impact of blended learning versus conventional teaching in programming courses using a data-driven approach. Student performance data, including assignment scores, examination results, and project outcomes, along with engagement metrics such as attendance, participation rates, and survey-based feedback, were analyzed. Statistical comparisons were conducted to measure improvements in problem-solving skills, coding proficiency, and overall academic achievement. The findings indicate that blended learning enhances student engagement, supports self-paced learning, and improves learning outcomes, though its effectiveness is influenced by the availability of digital resources and the instructor's adaptability. The study concludes by recommending a hybrid adoption strategy that leverages the strengths of both methods for effective programming education.
Blended learning, conventional teaching, programming education, computer science, student engagement, academic performance, data analysis, hybrid learning, active learning, teaching methods