Artificial Intelligence as an Educational Decision Support System in Problem-Based Learning: Critical Thinking, Decision-Making, and Human–AI Collaboration in Higher Education

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• Semantic Scholar2026-08-05 07:15:58
  Artificial Intelligence as an Educational Decision Support System in Problem-Based Learning: Critical Thinking, Decision-Making, and Human–AI Collaboration in Higher Education

  Artificial Intelligence (AI) is increasingly being integrated into higher education to support learning, problem solving, and decision making. Despite growing interest in generative AI technologies, limited empirical evidence exists regarding the use of AI as an Educational Decision Support System (EDSS) within Problem-Based Learning (PBL) environments. This study examined the association between AI-supported PBL and students’ critical thinking competencies, decision-making competencies, and perceptions of Human–AI collaboration in higher education. A mixed-methods quasi-experimental design employing a one-group pretest–posttest approach was adopted. The study involved 32 undergraduate students enrolled in an Optimization Analysis course at a public university in Thailand. Over an eight-week intervention, ChatGPT was integrated as a decision-support partner to assist students in information analysis, alternative generation, evidence evaluation, and decision justification during problem-solving activities. Quantitative data were collected using critical thinking and decision-making competency assessments and analyzed using descriptive statistics and paired-samples t-tests. Qualitative data were obtained through semi-structured interviews and analyzed using thematic analysis. The findings indicated statistically significant improvements in critical thinking competencies (t = 4.16, p = .001, d = 0.61) and decision-making competencies (t = 3.92, p = .001, d = 0.56). Students also reported positive perceptions of AI-supported decision making, particularly in information analysis, evidence evaluation, alternative exploration, and decision justification. Qualitative findings identified four interconnected Human–AI decision-making processes: information analysis, alternative generation, critical evaluation, and evidence-based decision making. The study contributes to the emerging literature on Educational Decision Support Systems by providing evidence that AI-supported Problem-Based Learning may serve as a promising pedagogical approach for supporting higher-order cognitive competencies and responsible Human–AI collaboration in higher education. The findings offer theoretical and practical implications for the design of AI-enhanced learning environments that promote evidence-based reasoning while preserving human judgment and accountability.