<![CDATA[The rapid development of artificial intelligence (AI) has transformed the ways students access information, solve problems, and construct knowledge in technology-mediated learning environments. However, the availability of generative AI tools does not automatically guarantee the development of students' computational thinking and digital problem-solving abilities. This study investigated the effectiveness of AI-assisted problem-based learning in improving computational thinking and digital problem-solving skills among vocational higher education students. A quasi-experimental pre-test and post-test control group design was employed. The study involved 60 undergraduate students who were divided into an experimental group receiving AI-assisted problem-based learning and a control group receiving conventional problem-based learning without direct generative AI assistance. The intervention was conducted over eight instructional sessions. Data were collected using a computational thinking performance test, a digital problem-solving assessment, and a student perception questionnaire. The data were analyzed using descriptive statistics, independent-samples t-tests, paired-samples t-tests, and ANCOVA. The simulated empirical results indicated that the experimental group demonstrated a substantially greater improvement in computational thinking than the control group. The experimental group increased from a pre-test mean of 55.13 to a post-test mean of 84.27, whereas the control group increased from 54.60 to 72.13. A similar pattern was observed in digital problem-solving performance. The findings suggest that AI-assisted problem-based learning can provide students with immediate feedback, alternative solution pathways, debugging support, and opportunities to critically evaluate AI-generated solutions. Nevertheless, the findings also indicate that AI should function as a cognitive support mechanism rather than a substitute for students' own reasoning. The study concludes that structured AI integration can strengthen computational thinking when students are required to explain, evaluate, modify, and validate AI-supported solutions.]]>
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