Digital application of science literacy measurement tools: Implementation of deep learning in shaping student sustainability literacy

Abstract

Sustainability literacy is a crucial topic because it supports the achievement of Sustainable Development Goals (SDGs). However, it is often not a priority for prospective elementary school teachers, who tend to understand this concept primarily from a theoretical perspective. This study aims to assist students in bridging the gap between theory and real-world practice through the implementation of a digital-based Science Literacy Measurement Tool supported by a deep learning approach. The research employs a quantitative method, utilizing a quasi-experimental design with a non-equivalent control group. The study involves 65 students from the Elementary School Teacher Education Study Program at Universitas Esa Unggul, selected through purposive sampling techniques. Data collection utilized a sustainability literacy questionnaire, supplemented with student responses, to illustrate the results of the sustainability literacy scale analysis and to categorize students accordingly. The results indicate that the Science Literacy Measurement Tool, which employs deep learning techniques, significantly aided students in enhancing their understanding of sustainability. Approximately one-third of the students demonstrated leadership in sustainability initiatives. These findings suggest that deep-learning digital tools can help students learn more about science and encourage them to take on leadership roles, thereby creating more opportunities in sustainability education. The implication is that integrating deep learning into science instruction could strengthen students' critical thinking, ecological awareness, and sense of responsibility for the environment. This learning model is worthy of consideration for wider implementation in schools, as it can help shape a more environmentally conscious generation.