Online learning gamification for a course on lawyer affairs

Hui Lin and Zhishi Zhang
Zhejiang Radio & Television University

Zhejiang, China


This paper discusses a gamification model of teaching and independent study for the course on lawyer affairs. This model is primarily designed for part-time students who are trying to pass the judicial examination. Therefore, the tone of the characters and design of the pictures in the game are straightforward and even a little humorous. Following the four principles of gamification, the model has been designed to use a game including four kinds of progressive roles. Student can experience the development from law school student to great lawyers by sequentially levelling up from law school student, to paralegal, to practising lawyer and, finally, to great lawyer. In addition, the four principles of gamification goal, rules, feedback system and voluntary participation are also fully reflected. To achieve the 'goal' of advancing to the next role, students 'voluntarily' complete a series of online tests under 'rules' and get scores which contain the 'feedback' function. At the same time, the game embeds traditional lecture notes, video courseware, a case library, in-class exercises, formative assessment, a mock judicial examination, a mock moot lawsuit and challenging questions and answers, some of which are in the form of online tests, to ensure the integrity and quality of the teaching process. This model is based on constructivism learning theory which claims that knowledge is not acquired through lectures, but through the construction of meaning when digesting learning resources in specific scenarios. In this model, in the different scenarios created by the game, students can not only acquire knowledge, but also get immediate self-evaluation and know their progress on the learning task. This allows students to see the level they are in and how far they are from the next level. Moreover, to ensure that students have continuous self-confidence and motivation in their game-based learning, the game environment is continuously improved based on data analysis of their learning progress.