Trap-States Found in Problem-Posing Activity Sequences Based on Triplet Structure Model

Abstract

Problem-posing activities can provide a significant insights into learners' understanding about structure of problem. Finding an interesting pattern in a problem-posing learning environment is crucial to identify an important situation that learner may have difficulty to complete an assignment. This paper expects visualizations of the activity sequences to finding turning points where learners lose a way to reach the goal of an assignment. The activity sequences are considered to represent thinking process of learners and reflect their understanding and misunderstanding about the structure of problems. This paper proposes detection of ``trap-states'' that is an intermediate state of thinking in which learners have difficulty in achieving to the correct answer. As the results from an exercise detection of trap-states from real data, trap-states have found.