A New Teaching Pattern and Evaluation System of Knowledge Point Puzzle in Massive Online Computer Courses

In the context of the rise of massive online courses, it has become an important research goal to study the design methods of course content and course structure, to adapt to the personalized needs of many teaching objects of massive online learning. Based on the theory of "Learning Customized of MOOC (LC-MOOC)", and taking the course of "Database Technology and Program Design" as an example, this paper has proposed a "Knowledge Point Puzzle" course system structure. With the combination of "Learning Roadmap", "Mind Mapping" and other guiding frameworks, each puzzle corresponds to a module in the development of a database application system so that the learners are able to combine knowledge fragments to form a personalized course system. The teaching route of Knowledge Point Puzzles enables learners to grasp the hierarchical structure of knowledge points as a whole, clearly understand the internal relationship between the puzzles, gradually unlock the new puzzle module in the learning process, associate the next level of knowledge points, and construct the whole knowledge structure of the course in a progressive way. In addition, this paper also introduces the "self-evaluation" + "mutual evaluation" course evaluation system to guide learners' learning trends in the form of process evaluation.