Penerapan Model Blended Learning Tipe Station Rotation dalam Meningkatkan Kemampuan Menulis Kalimat Bahasa Jepang Mahasiswa Pendidikan Bahasa Jepang Semester 4 FKIP UHAMKA
Abstract
The low ability to write Japanese sentences for 4th semester students of Japanese Language Education FKIP UHAMKA and the shift in learning activities during the COVID-19 endemic period which was previously carried out online and now face-to-face learning has begun, educators must create creative learning. One of them is by trying to apply the station rotation type blended learning method. For this reason, the purpose of this study is to describe the improvement in the ability to write Japanese sentences using the application of the station rotation type blended learning model for 4th semester students of the Japanese Language Education Study Program, FKIP UHAMKA. The study used a research design of One Group Pre-test Post-test Design, using the Quasi Experimental method. Data collection techniques were carried out by means of tests (pre test and post test) and questionnaires. Valid and reliable measurements on the pre-test and post-test were carried out by analysis of the validity test and reliability test by the validator. In the data analysis technique using the normality test stage, then testing the hypothesis in the form of a t test (Paired Simple t test) using SPSS 26. While data analysis on the questionnaire uses a Likert scale. Based on the results of calculations on research data, the results of the pre-test score obtained an average (mean) learning outcome of 51.13 while the post-test score obtained a mean value of 74.81. The results of the calculation of the Paired Simple t test with a significance level of 0.05, it is known that the value of Sig (2-tailed) is 0.001 <0.05, it can be concluded that H0 is rejected and Ha is accepted. The results of the study stated that the station rotation type blended learning model can improve the ability to write Japanese sentences. While on the questionnaire data, the results of the questionnaire data analysis stated that all the questions were valid and the application of the station rotation type blended learning was interesting.
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