A study of programming learning perceptions and effectiveness under a blended learning model with live streaming: comparisons between full-time and working students

Abstract

ABSTRACT With the rise of big data, artificial intelligence, and other emerging information technologies, an increasing number of students without computer science (CS) backgrounds have begun to learn programming. Programming is considered a complex task for beginners, and instructors find it difficult to quickly address all the problems that students face, especially in the traditional learning environment. This study adopted a blended learning model that integrated conventional face-to-face teaching, asynchronous learning, and live streaming to examine the perceptions and effectiveness of programming learning among students from different degree tracks. The participants were 26 working and 28 full-time students from a university in Taiwan. The results indicated that with code annotations proving an efficient way for working students to review coding knowledge, and flipped courses making videos important for full-time students. Live streaming learning can overcome lab limitations with instant interaction between instructors and learners. The blended model ensures equal programming learning for both groups, while instructors can design learner-centered live streaming environments and innovative learning pedagogy to flip programming.