Utilising smart water monitoring with IoT in science learning with problem-based learning model: Impact on critical thinking skills and the role of learning interest

Abstract

This research explores the impact of integrating smart water monitoring with internet of things (IoT) into 7th-grade science education using the problem-based learning (PBL) model. A quasi-experimental research design with a post-test-only control group is employed to compare the effectiveness of two learning groups: one using the regular PBL model and the other incorporating smart water monitoring through IoT within the PBL framework. The study includes 7th-grade students from two different secondary schools as participants. The independent variables are the regular PBL model and the PBL model with smart water monitoring using IoT. In contrast, the dependent variable is students' critical thinking skills, with prior knowledge and learning interest as covariates. Students utilize an observation worksheet for Water Quality Assessment to observe different types of water and assess their suitability or water quality. The findings reveal that integrating smart water monitoring with IoT in the PBL model significantly positively impacts students' critical thinking skills. The group of smart water monitoring students demonstrated a more considerable improvement in critical thinking skills than those following the regular PBL model. The study highlights the essential role of students' learning interest in developing necessary thinking skills. Students with higher learning interest in the science subject tend to exhibit more significant improvement in critical thinking skills after participating in learning with smart water monitoring or the regular PBL model.