Improving Students' Environmental Literacy Through a Deep Learning-Based Contextual Teaching and Learning Model - Syaripah Rahma; Mar’atus Solikha; Asrianty Mas’ud (FKIP - Universitas Riau, 2026)
This study aims to analyze improvements in students’ environmental literacy through a deep learning-based Contextual Teaching and Learning (CTL) model applied to environmental change curriculum. The primary issue underlying this study is the low level of environmental literacy among students, which results in a lack of environmentally conscious attitudes and behaviors. The study employed a quasi-experimental method with a non-equivalent control group design. The research subjects consisted of an experimental class using the deep learning-based CTL model and a control class without the use of the deep learning-based CTL model. Research instruments included an essay test and a questionnaire to measure environmental literacy before and after the intervention. The results showed that the experimental class experienced an increase of 44.12% with an N-Gain value of 0.65, which falls into the moderate category, while the control class experienced an increase of 19.88% with an N-Gain value of 0.27, which falls into the low category. These findings indicate an improvement in students’ environmental literacy following the implementation of the deep learning-based CTL learning model on environmental change content.