Data-driven problem solving and students' critical thinking in a problem-based learning environment.

摘要

This case study employed a data-driven problem solving system entitled ActionOrganizer as an instrument to investigate two research questions that focus on students' changing thinking processes. Twenty-two Chinese college students were required to solve a problem based on a given scenario. Through using ActionOrganizer, participants completed three weekly assignments, in which they could incorporate their thinking skills. The theoretical foundations were constructed by the theories of metacognition, critical thinking, problem-based learning (PBL), and data-driven systems. Since ActionOrganizer embodied the principles of PBL, instructional technology principles, and the characteristics of data formation, ActionOrganizer had the potential to help students record, organize, and manage their changing thinking.;This study collected data from a survey (the AOPS), an optional questionnaire (OQ), three group interviews, and twenty-two students' ActionOrganizer assignments. For Question ;The major findings for Question ;This study defines the indicators of critical thinking to be inquiry, analysis, inference, and decision-making as a group of inquiry skills, and uses this definition to establish codes to explore participants' thinking patterns when they responded to each ActionOrganizer stage. Kuhn's inquiry model and Barrows' PBL model were the major models that supported the interpretation of the findings in this study.