Flipped Direct Instruction (FDI): Optimization of Practicum Learning Models

Abstract

Selecting an accurate learning model plays a big part in determining the quality of the implemented learning process. The Flipped Direct Instruction (FDI) learning model is introduced as a new learning model to increase the effectiveness of the implementation of learning through practicums. Therefore, the purpose of this study is to examine the effectiveness level of the FDI learning model application. This research is carried out during the Computer Network Installation practical lesson in the July-December 2022 semester at the Electronic Systems Engineering Study Program, Universitas Negeri Padang, Indonesia. This study is conducted using a quasi-experimental design with a control class and an experimental class as the research samples. The Direct Instruction (DI) model was applied in the control class and the FDI model was utilized for the experimental class. This study uses quantitative and primary data types. Data were obtained using test instruments through the application of a pre-test and a post-test. The data is calculated using the N-Gain method to measure the level of effectiveness of the FDI model implementation. In utilizing the N-Gain method, the requirements for the normality test, homogeneity test, and t-test were applied. The results of the research on the implementation of the pre-test for the control class were a value of 36.11 and 34.01 for the experimental class. Whereas for the post-test, a value of 71.27 and 86.80 were the results for the experimental class. The experimental class post-test scores were used in the N-Gain test. The results of the N-Gain test obtained a percentage of 79.11% with a minimum value of 62.76% and a maximum value of 90.89%. The value of 79.11% in the N-Gain value range can be categorized as a notably high outcome. This portrays that the FDI learning model is effective in improving practicum learning outcomes.