A New Model of Docker-based E-learning in Hadoop
Feng Tuo, Yu Bai, Saiqin Long, Yu Luo, Tao Wang, Renmin Wang, Gang George Yin · 2018
Online programming education is a new trend of E-learning, and there are already some platforms that support online programming tutoring with common programming languages and several software development techniques. However, cloud computing is a practical technology (e.g., Hadoop) with limited platforms support since it takes up a lot of computer resources. In this paper, we construct Hadoop on Educoder with virtualization technologies (such as Docker), it makes online programing with the data processing possible, which makes up for the weaknesses of building environment in local machine or paying for online resources a lot. Furthermore, we design and implement some online programming challenges of cloud computing in Hadoop, including knowledge guidance and evaluation. Educoder records students' programming information during the programming processes, together with the feedback of questionnaires, which can be used to evaluate students' performance in cloud computing programming. The analysis results reveal some interesting observations over the online programming in Hadoop. For example, results show that even they get the same scores, the students with fewer code modifications have better performance. Yet the challenge is more difficult than before, the more they practice, the fewer mistakes of programming details they will make and the more efficient they will be. Therefore, it is necessary to design step by step practice and to emphasize the program details which influence efficiency at the beginning.