The purpose of this research is to produce an e-module of microplastic pollution in the Sengguruh Reservoir based on Problem-based Learning (PBL) that meets the requirements of validity and practicality. This research is a research & development that adapts the Lee & Owen development model. The subjects in this study were two lecturers of material experts and teaching materials experts of the Department of Biology, State University of Malang, one biology teacher of SMAN 1 Gondanglegi, 27 students of class X MIPA SMAN 1 Gondanglegi, and 26 students of class XI MIPA SMAN 1 Gondanglegi. Collecting data using a questionnaire and analysing quantitatively and qualitatively. The percentage results of the validity of the e-module according to the material expert validator are 100% with a very valid category, the percentage of the validity of the e-module according to the validator of media and teaching materials experts is 100%, and the percentage of the validity of the e-module according to biology education practitioners is 95.56%. The criteria for the practicality of the e-module, according to the teacher, is 98.09%, and according to the students, it is 93.40%.
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24 May 2024
THE 6TH INTERNATIONAL CONFERENCE ON MATHEMATICS AND SCIENCE EDUCATION (ICoMSE) 2022: Educational Diversity and the Future of Mathematics and Science Education Research
9–10 August 2022
Malang, Indonesia
Research Article|
May 24 2024
Development of microplastics pollution e-module in Sengguruh reservoir based on problem-based learning
Eka Aghnia Syarif;
Eka Aghnia Syarif
a)
Biology Department, Mathematics and Natural Sciences Faculty, Universitas Negeri Malang
, Malang, East Java, Indonesia
65145
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Agus Dharmawan;
Agus Dharmawan
b)
Biology Department, Mathematics and Natural Sciences Faculty, Universitas Negeri Malang
, Malang, East Java, Indonesia
65145b)Corresponding author: [email protected]
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AIP Conf. Proc. 3106, 030014 (2024)
Citation
Eka Aghnia Syarif, Agus Dharmawan, Sueb Sueb; Development of microplastics pollution e-module in Sengguruh reservoir based on problem-based learning. AIP Conf. Proc. 24 May 2024; 3106 (1): 030014. https://doi.org/10.1063/5.0215242
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