Students’ Subjective Evaluation: The Relationship between the Implementation of Deep Learning and Improvements in Writing Quality and Motivation

Abstract

This study is motivated by the differences in students’ writing quality despite being in relatively similar learning environments, which are presumed to be related to the implementation of deep learning. The study aims to explore students’ subjective evaluations of deep learning implementation and to analyze its relationship with improvements in writing quality and writing motivation. The research employed a quantitative method with a descriptive approach. Data were collected through a Likert-scale questionnaire distributed to 50 students at Universitas Negeri Makassar using purposive sampling. Data analysis was conducted using percentage index calculations. The results indicate that the implementation of deep learning falls into a very high category (83.1%), characterized by active student engagement, encouragement of critical thinking, and open discussion spaces. This condition shows a positive correlation with improvements in students’ writing quality (81.3%), particularly in the organization of ideas, coherence, and the use of references. In addition, writing motivation also demonstrates a positive trend (78.3%), especially in openness to revision and the ability to overcome writing difficulties, although aspects such as self-confidence and interest in publication remain relatively lower. Thus, deep learning contributes to improving students’ writing quality and motivation; however, these findings are contextual and do not yet indicate a causal relationship.