Application of the Hots-Based Value Clarification Technique (VCT) Learning Model in Viral News to the Domain of Moral Knowing
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Abstract
The research objective was to apply the HOTS-based Value Clarification Technique (VCT) learning model to viral news in the moral knowing domain. The research uses a quantitative approach with quasi-experimental or quasi-experimental methods. The research design is pretest and posttest control group. This research was conducted at SMA Negeri 3 Kuningan. The participants in this study were students in class X MIPA 3 and X MIPA 4, each class consisting of 34 students. Student responses regarding the application of the VCT learning model were interesting, easy to understand, and motivated students in the learning process with the category strongly agreeing with a percentage of 82%, the category agreeing with an average of 54% and the category neutral having the lowest score, namely 4%. Student response to the VCT model is able to meet the challenges of critical thinking in life, has an average highest score of 74% with a category of strongly agreeing 42%, agreeing category 74%, neutral category with a score of 19% and disagreeing with the lowest score of 5%. Based on the analysis with the SPSS program, the average score (mean) achieved by students at the initial moral knowing before being given treatment was 65.17. The average value category of moral knowing in the control class at the initial stage (pre-test) had the lowest score of 34 and the highest score of 70. Furthermore, from the results of the analysis of the SPSS program, the initial average ( mean) moral knowing score of students was 57 .03. The pre-test average category level in the control class is quite low compared to the pre-test results in the experimental class. There is a significant difference in moral knowing between the experimental class and the control class. The average pre-test score for the experimental class was 65.171, and the posttest score increased to 85.371 or an increase of 20.20. Meanwhile, the average pretest score for the control class was 57.029, and the posttest score increased to 69.886 or an increase of 12.86. So there is a difference in the average Domain Moral Knowing the treatment before and after learning that applies the HOTS-based VCT model to the experimental class, has a t value of 25.250 > t table with df (0.05, 35) = 2.03, and a Sig value . = 0.000 which is less than 0.05, meaning that there is a significant difference in the average Domain of Moral Knowing between before and after learning that applies the HOTS-based VCT model. Meanwhile, the control class has calculated t value of 10.694 > t table with df (0.05, 35) = 2.03, and the value of Sig. = 0.000 which is less than 0.05, meaning that there is a significant difference in the average Domain Moral Knowing without learning that applies the HOTS-based VCT model. Learning that applies the HOTS-based VCT model gives better results to Domain Moral Knowing.