The Moodle Learning Management System (LMS) at the State University of Malang is named SIPEJAR (Sistem Pengelolaan Pembelajaran). Researchers apply SIPEJAR synchronously on metal casting learning theory both in traditional learning and problem-based learning models for students of the Diploma-3 Mechanical Engineering, State University of Malang. This study explored the differences in student learning outcomes in metal casting courses between the traditional learning models and problem-based learning using the SIPEJAR in the Diploma-3 Mechanical Engineering. This research used the Quasi-Experimental Design with tests as the data collection technique. Forty students were chosen as research participants and grouped into the experimental group, consisting of 20 students using problem-based learning and 20 students for the control group using traditional learning. The data analysis technique used the T-test to obtain the learning outcomes. The differences in the two learning outcomes were obtained using the T-test, and it showed a significance difference in student learning outcomes in metal casting courses using traditional learning models with problem-based learning using SIPEJAR in the Diploma-3 Mechanical Engineering Study Program. This learning model effectively develops thinking skills, solving problems, finding concepts, applying concepts, and increasing learning outcomes.
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29 June 2022
PROCEEDINGS OF THE 1ST INTERNATIONAL CONFERENCE ON CIVIL ENGINEERING EDUCATION (ICCEE 2021)
12 August 2021
Malang, Indonesia
Research Article|
June 29 2022
Comparison of learning outcomes in metal casting subject using traditional learning model with problem-base learning through SIPEJAR
Tuwoso Tuwoso
Tuwoso Tuwoso
a)
Department of Mechanical Engineering, Faculty of Engineering, Univeristas Negeri Malang
, Indonesia
a)Corresponding author: tuwoso.ft@um.ac.id
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a)Corresponding author: tuwoso.ft@um.ac.id
AIP Conf. Proc. 2489, 030017 (2022)
Citation
Tuwoso Tuwoso; Comparison of learning outcomes in metal casting subject using traditional learning model with problem-base learning through SIPEJAR. AIP Conf. Proc. 29 June 2022; 2489 (1): 030017. https://doi.org/10.1063/5.0093862
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