Evaluating the impact of a project-based learning framework on overall skill development

With the increasing integration of artificial intelligence (AI) across industries, there is a growing need to transform traditional teaching methods into more innovative, technology-driven, and practice-oriented approaches. Project-Based Learning (PBL) has emerged as an effective pedagogy that promotes active learning, connects theoretical concepts to real-world applications, and enhances critical thinking and problem-solving abilities. This study evaluates the effectiveness of a structured PBL framework implemented through the Technoscope program in an undergraduate engineering context using an integrated assessment approach. Data were collected from 58 to 60 students using a structured questionnaire based on a five-point Likert scale administered before and after the intervention. The instrument was validated using the Content Validity Index (CVI). In addition to student perceptions, project outcomes were assessed through rubric-based evaluation by domain experts to provide complementary performance insights. Descriptive and inferential analyses revealed a significant improvement in student outcomes, with mean scores increasing from 3.4 (SD = 0.7) under traditional teaching methods to 4.5 (SD = 0.4) following PBL implementation. Statistically significant gains were observed across key dimensions, including overall learning experience, conceptual understanding, creativity, and problem-solving skills (p < 0.001), with moderate to large effect sizes. A majority of students reported enhanced creativity (85.7%) and improved understanding of subject content (82.5%), while 60.3% expressed satisfaction with the overall learning experience. The overall mean score of 4.41 (SD = 0.86) indicates high engagement and positive learning experiences. Despite these findings, the results are primarily based on self-reported data and are limited by the absence of a control group and single-institution context. Future research should incorporate objective performance measures, longitudinal designs, and multi-institutional samples to strengthen the evidence base.