<![CDATA[The demands of 21st-century education require university students to possess strong critical and innovative thinking skills. However, theoretical learning in higher education remains predominantly conventional, resulting in limited opportunities for students to construct knowledge deeply. This study aims to analyze and evaluate the effectiveness of a deep learning approach in enhancing critical and innovative thinking skills among master's level students. The research employed a convergent parallel mixed-methods design, involving 46 graduate students as research participants. Data were collected using a mixed-form questionnaire consisting of closed-ended and open-ended items, supported by documentation. Quantitative data were analyzed descriptively using percentages, while qualitative responses were interpreted thematically. The results indicate that theoretical learning still lacks variation and consistency, yet 93.5% of students reported that deep learning fosters critical thinking and 87% agreed that it encourages innovative thinking, although only 45.7% frequently apply both during coursework. Students also expect more collaborative, project-based, case-based, and exploratory learning supported by digital media. The study concludes that deep learning is a relevant and potential approach to strengthen critical-innovative thinking skills, addressing existing instructional limitations. This research implies the need for a structured deep learning model to optimize theoretical courses and create more reflective and student-centered learning.]]>
Copyrights © 2025
