The effect of deep Learning-based practicum with simple tools on improving the science process skills of prospective teacher students

The study aims to determine the effect of deep learning-based practical work using simple tools on improving students' science process skills. The research method employs a quasi-experimental design with a one-shot case study approach. The sample consisted of 43 PGSD FKIP UIR students, with research instruments as observation sheets and questionnaires. The data obtained were analysed using prerequisite tests, specifically normality and hypothesis tests, including the t-test with a significance level 0.05. The normality test results showed that the data were normally distributed with a Sig value of 0.2 > 0.05. The hypothesis test results yielded a Sig value of 0.000 < 0.05, so H0 was rejected and H1 was accepted. The results show a significant improvement in science process skills, including observing, classifying, measuring, and communicating. In conclusion, students' science process skills improve when applying the deep learning-based practical method using simple tools. These findings indicate practical potential that can be used to support effective science learning for prospective teacher students.