Using educational data mining methods to assess field-dependent and field-independent learners' complex problem solving

The present study investigated the problem-solving performance of 101 university students and their interactions with a computer modeling tool in order to solve a complex problem. Based on their performance on the hidden figures test, students were assigned to three groups of field-dependent (FD), field-mixed (FM), and field-independent (FI) learners, and were instructed to use integrated-format materials and Model-It(A (R)) in order to solve a problem about immigration policy. The results showed that there were significant differences among the three groups of learners in terms of their problem-solving performance. Consequently, the study employed educational data mining (EDM) methods in order to examine how FD and FI learners actually interacted with Model-It(A (R)) in order to solve the problem. The EDM methods provided rich analytical information and details about learners' interactions with the computer tool. Implications for designing effective joint cognitive systems are discussed.