Original Research ARTICLE
Exploring multiple goals balancing in complex problem solving based on log data
- 1School of Psychology, Beijing Normal University, China
- 2Collaborative Innovation Center of Assessment towards Basic Education Quality, Beijing Normal University, China
Multiple goals balancing is an important but not yet fully validated dimension of complex problem solving (CPS). The present study used process data to explore how solvers clarify goals, set priorities, and balance conflicting goals. We extracted behavioral indicators of goal pursuit from the log data of 3,201 students on the third subtask of the “Ticket” task in the PISA 2012 CPS test. Cluster analysis was used to identify 10 groups that varied in goal pursuit behavior. Logistics and least-squares regression analysis were used to explore how goal pursuit affected task scores and CPS proficiency. The results showed that competent solvers clarified goals and weighed priorities more effectively. They also made trade-offs between conflicting goals. The importance of theoretically-driven log data analysis and coping strategies in the face of multiple goals conflict scenarios was discussed.
Keywords: Complex Problem Solving, multiple goals balancing, Log data analysis, educational data mining, K-Means cluster analysis
Received: 30 Dec 2018;
Accepted: 12 Aug 2019.
Copyright: © 2019 Ren, Ren, Bai and Luo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Fang Luo, School of Psychology, Beijing Normal University, Beijing, 100875, China, email@example.com