Claim Missing Document
Check
Articles

Found 2 Documents
Search

Early Mapping of Student Science Literacy: A Preliminary Study for Tidal Flood Mitigation Learning Innovation Based on Deep Learning and Local Wisdom Azimatul Khusniah; Andin Irsadi; Sudarmin Sudarmin; Novi Ratna Dewi
Journal of Mathematics Instruction, Social Research and Opinion Vol. 5 No. 2 (2026): June
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v5i2.1406

Abstract

This study aims to provide an initial quantitative mapping of coastal students’ science literacy related to tidal flood mitigation, addressing the limited contextual understanding of disaster adaptation in schools. Using a quantitative descriptive survey design, the study involved 360 students from three coastal vocational high schools selected through proportional stratified random sampling. Data were collected through a PISA-based science literacy test and disaster mitigation perception questionnaires, then analyzed using descriptive statistics, One-Way ANOVA, and Pearson correlation tests. The findings showed that students’ overall science literacy was at a moderate level (mean = 68.61). Students demonstrated relatively good data interpretation skills (mean = 76.83), while their ability to explain natural phenomena scientifically remained lower (mean = 62.15). The ANOVA test indicated no significant difference in science literacy among the three schools (p = 0.946). In addition, a very strong positive correlation (r = 0.82) was observed between science literacy and students’ perceptions of disaster resilience. The novelty of this study lies in its integration of coastal disaster literacy mapping with a deep-learning pedagogical approach grounded in local wisdom. These findings provide empirical evidence that science literacy in coastal schools remains insufficiently connected to students’ environmental realities, highlighting the importance of contextual and culturally responsive science learning for disaster mitigation education.
ANALISIS KESENJANGAN PENELITIAN TENTANG PROBLEM-BASED LEARNING BERPENDEKATAN DEEP LEARNING DALAM PEMBELAJARAN SAINS BERMUATAN MITIGASI BENCANA UNTUK MENINGKATKAN LITERASI SAINS Azimatul Khusniah; Andin Irsadi; Ani Rusilowati
Journal of Teaching and Learning Physics Vol. 11 No. 1 (2026): Journal of Teaching and Learning Physics (February 2026)
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/jotalp.v11i1.53707

Abstract

Indonesia has a high vulnerability to disasters, but the integration of disaster education in the curriculum is often still sporadic so that it has an impact on students' low science literacy. Conventional methods are considered inadequate, so a transition to a Problem-Based Learning (PBL) model is needed which is strengthened with a Deep Learning approach. This study aims to analyze and synthesize the current scientific literature landscape regarding the effectiveness of PBL integration with Deep Learning in disaster mitigation science learning. Using  the Systematic Literature Review (SLR) method which refers to the PRISMA 2020 guidelines, this study examines empirical articles from the Scopus database for the period 2015–2025 which were analyzed with the help of VOSviewer. The results show that the current research trend is dominated by the social science education domain with a focus on Active Learning to improve higher level thinking skills (HOTS), but significant methodological gaps were found in the form of a lack of studies that integrate PBL and Deep Learning syntaxin its entirety in the context of science. This study concludes the need for a new conceptual framework that synergizes problem-solving structures with deep information processing to build adaptive and disaster-responsive science literacy.