The Use of Integrated Digital Series Image Media with A Deep Learning Approach to Improve Narrative Writing Skills - Eva Oktaviana; Chairunnisa; Maria Ulfa (Universitas Islam Negeri Palopo, 2025)
This research is based on the background of problems in learning to write narrative texts, including the low writing skills of students in paying attention to spelling, vocabulary, and difficulties in developing their ideas to be poured into a narrative text. In addition, based on survey data from the Programme for International Student Assessment (PISA) conducted by the Programme for Economic Cooperation and Development (OECD) in 2022, students' literacy and numeracy skills are still low. The purpose of this study is to improve the ability to write narrative texts using digital series image media through a deep learning approach. The method used is classroom Action Research, with the Kemmis and Mc Taggart models through 2 cycles, each cycle through four stages, namely planning, action, observation and reflection. The data collection technique used a narrative text writing test using digital series image media, observation, interviews and documentation. Meanwhile, the analysis technique uses data triangulation. The research subjects of grade V elementary school students. The results of the study showed that 38% of pre-tests, 78% of the first cycle and 81% of the second cycle. The results of the observation of the first cycle were 80% and the second cycle 90%. It can be concluded that students' narrative writing skills can be improved through digital series drawings through a deep learning approach because the images produced are in accordance with the students' daily lives, making it easier for students to express their ideas.