The purpose of the study was to examine the effect of e-learning on the academic performance of undergraduate students at Nankai University in China. The study adopted the descriptive research design. Descriptive research design is a type of research design that aims to systematically obtain information to describe a phenomenon, situation, or population. The sample size was 361 students and they were purposively picked. The collection of the data was done using questionnaires. Descriptive and inferential were used to analyze the data. It was found that e-learning is positively and significantly related to academic performance. E-learning is among the expanding areas, particularly in tertiary education. Educational institutions are different in growing nations than in developed nations, like poor quality of education and low chances of attending learning institutions in the local areas because of long distances. E-Learning enhances accessibility to effective learning and therefore boosts the performance of learners. It is easy since learners watch a video documentary in the lecture room. In an E-learning system, learners can interact anytime and from anywhere with various educational materials like messages, audio, pictures, video and more via the internet. The study concluded that e-learning is positively and significantly related to academic performance. The study recommended that both the lecturers and the learners are required to develop a personal interest in the usage of ICT. The use of ICT in schools needs to be made mandatory in tertiary institutions and the lecturers should be provided with good training on the effective use of ICT. There is a need to have a steady power supply to use ICT effectively. It is also recommended that tertiary institutions' management make a consorted initiative to give e-learning environments that will improve learner performances in tertiary institutions and facilitate their self-development initiatives. Keywords: E-Learning, academic performance, Undergraduate Students, Nankai University, China
Read full abstract