An Adaptive Learning Strategy Scheme for Role Playing Learning

Abstract

Traditionally, the assessment of the advanced knowledge about science such as problem solving or inquiry process is a challenging issue. In this paper, we aim to develop a Role Playing Learning platform called "The Banana Farm" to support the assessment of the nature science learning with collaborative fruit planting and marketing scenario. To support the assessment for inquiry process, our idea is to design the learning platform based on the multi-stage graph model in which the stages of vertices represent the student's actions and decision making during the assessment. Thus, the paths chosen to perform can be seemed as the science inquiry processes of them. Since the actions of the same stage may be executed several times, the model is extended to have self edge. Besides, the environmental status and the effectiveness of the learning objects are also extended by the working status and constraint rules in each stage. Thus, the extended Modified Multi-stage Graph (MMG) is proposed to support the assessment of inquiry process by the portfolio paths chosen in different stages. Next, the portfolio is collected for the collaborative behavior mining to discover the students' frequent collaborative action and interaction patterns during the learning. Combining with the characteristics of students, the assessment of teams with different learning strategy and behavior patterns can be obtained. Finally, the experiment on 40 junior high school students has been done and the findings were presented.