Analysis of Problem-Posing Activity Sequences toward Modeling Thinking Process and Detection of Trap States

Abstract

Problem-posing is well known as an effective activity to learn problem-solving methods. Although the activity is considered to contribute to understanding of the structure of problems, it is not clear how learners could understand it through the activity. The goal of this study is to make it possible to analyze problem-posing activity sequence for enhancing the effectiveness in learning. This paper proposes visualizations of problem-posing activity sequence in MONSAKUN, a learning environment for problem-posing of arithmetic word problems as sentence integration. This system requires that users pose problems not freely but as combinations of given simple sentences and logs problem-posing activity as sequences of them. The sequences are considered to represent the thinking process of learners and reflect their understanding and misunderstanding about the structure of problems. This study expects visualization of the sequences to be helpful to infer learners’ bottlenecks in thinking and misunderstanding behind them. As an example, this paper proposes detection of “trap state” that is a combination of simple sentences many learners tend to make in problem-posing assignments.