Geography Teachers’ Perceptions and Attitudes Toward Paradigm Shifts in Learning Through Deep Learning Approaches

Igna Juli Triana, Ahmad Yani, Rahayuni Tyas Pratiwi

Abstract


This study explored geography teachers’ perceptions and attitudes toward the paradigm shift in learning through the Deep learning approach within Indonesia's Merdeka Curriculum. Using a convergent mixed-methods design, data were collected from 50 geography teachers across West Java through structured questionnaires and open-ended responses. Quantitative data were analyzed using descriptive statistics, while qualitative data were examined through thematic analysis. The results showed that most teachers had positive (56%) or very positive (28%) perceptions of Deep learning, although conceptual understanding remained moderate. Attitudinal responses were even stronger, with 52% of participants exhibiting very positive attitudes, particularly in terms of motivation, collaboration, and willingness to adapt. However, teachers expressed concerns about their readiness, challenges in lesson design, student learning habits, technology integration, and inadequate school infrastructure. Despite these obstacles, the findings suggest a strong professional commitment to adopting Deep Learning approaches, provided that sufficient training and institutional support are available. The study contributes to a deeper understanding of how subject-specific educators respond to curricular innovations and emphasizes the importance of equipping teachers for sustainable implementation. In addition, support from school principals and policymakers is highly expected to create a conducive and equitable learning environment. This research provides important recommendations for the development of educational policies and practices that are able to support meaningful and sustainable learning.

Keywords


Deep Learning; Paradigm Shift in Education; Geography Teachers; Merdeka Curriculum; Teacher Perceptions; Teacher Attitudes

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DOI: https://doi.org/10.17509/gea.v25i2.85964

DOI (PDF): https://doi.org/10.17509/gea.v25i2,%20October.85964.g32738

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