Deep learning: An alternative English learning approach for college students

Abstract

The Indonesian government has introduced a deep learning approach based on three principles: mindful, meaningful, and joyful learning. This approach is considered essential to address learning challenges by ensuring that education is not only focused on content mastery but also on the application of knowledge in real-life contexts. Learning English as a general course for non-English major university students often faces challenges of low motivation, limited engagement, and lack of perceived relevance. Applying deep learning principles in this context is therefore urgent, as it can help create a more supportive learning atmosphere, enhance student motivation, and strengthen the practical connection between English and students’ real-life needs. This study aims to explore deep learning approach implementation and the impacts for non-English major university students who learn English as general course.  This research employed a qualitative descriptive method using a closed-ended questionnaire based on a Likert scale, distributed to 108 students from three different study programs. The data were analyzed through data reduction, data presentation, and conclusion drawing, validated by source triangulation. The results show that the majority of students perceived that lecturers successfully applied the principles of mindful (90%), meaningful (96%), and joyful learning (95.6%) in the learning process. Students reported increased focus, emotional engagement, relevance of the material to real-life contexts, and higher learning motivation. These findings indicate that the deep learning approach has a significantly positive impact on the effectiveness of English language learning. However, a small portion of students expressed disagreement, suggesting that there is still room for improvement, particularly regarding lecturer readiness and infrastructure support. Therefore, educator training and capacity building are essential steps to ensure the successful implementation of deep learning.