Pengembangan Perangkat Pembelajaran Rbl-Steam untuk Meningkatkan Keterampilan Metaliterasi Mahasiswa dalam Menyelesaikan Masalah Rainbow Vertex Antimagic Coloring dan Aplikasinya pada Desain Motif Batik Berkearifan Lokal

Abstract

Education is a milestone in the development of every individual's mindset. With the development of the times, it is necessary to adjust in the field of education. One way is by developing learning tools using the research-based learning-STEAM model which aims to improve students' meta literacy thinking skills. The method to be used in this research is a mixed method and the research procedure to be used, namely in the form of 4D development research consisting of the defining stage, the design stage, the development stage, and the dissemination stage. From the device development process, the validation score obtained in each device is 3.6 for RTM (valid), 3.5 for MFI (valid), 3.5 for meta literacy skills test (valid), 3.5 for response questionnaire (valid), 3.5 for implementation observation (valid), 3.4 for activity observation (valid) and 3.56 for the questionnaire (valid). he practicality test of learning devices obtained 3.89 with a percentage of 97.25%. Meanwhile, the effectiveness test is divided into the completeness of the meta literacy skills test with 85% of students completing it, analysis of student activities with 95.5% of activities, and 81.8% for the results of positive student questionnaire responses. The device as a whole meets the criteria of validity, practicality, and effectiveness. Furthermore, the Chi-Square test was conducted. The Chi-Square test results obtained Asymp. Sig. 0.004 <0.05, which means that there is an increase in the distribution of student meta-literacy skill test levels from those who tend to gather at low-medium thinking abilities with 17 low-level students and 10 medium-level students at the pre-test, tend to gather in the medium-high metaliteracy thinking category with 11 medium-level students and 12 high-level students at the post-test. These quantitative results are then corroborated by qualitative analysis of data triangulation which includes phase portraits, NVivo, and Bjorn Wordclouds.