The development of RBL-stem learning materials to improve student’s computational thinking skills in solving b-coloring problems for intercropping farming

Aula Zahrotin Magfiroh 1, *, Dafik 2 and Arika Indah Kristiana 3

1 Department of Postgraduate Mathematics Education, Faculty of Teacher Training and Education, University of Jember, Indonesia.
2 Department of Postgraduate Mathematics Education, PUI-PT Combinatorics and Graphs, CGANT, Faculty of Teacher Training and Education, University of Jember, Indonesia.
3 Department of Mathematics, Faculty of Mathematics and Natural Science, University of Jember, Indonesia.
 
Research Article
World Journal of Advanced Research and Reviews, 2024, 24(02), 1885–1892
Article DOI: 10.30574/wjarr.2024.24.2.3542
 
Publication history: 
Received on 06 October 2024; revised on 17 November 2024; accepted on 19 November 2024
 
Abstract: 
Research-Based Learning can be studied with a STEM approach, in RBL students will find a problem that requires solving, problem solving skills are very important in learning. One of these mathematical thinking skills is computational thinking skills. b-coloring is one of the concepts of graph theory. b-Coloring is widely applied in various fields, one of which we can apply to intercropping agriculture. The development of RBL-STEM learning materials to improve students' computational thinking skills in this research meets the criteria of being valid, practical and effective. The validity score is 3.87. The results of observing learning implementation were 3.71 with a percentage of 92.75%, and student responses were 91.62% positive, thus meeting practical criteria. Based on the test results, researchers found that 97.50% of students completed the test so they met the effective criteria. Quantitative analysis includes pretest and posttest data processing, where normality tests and paired sample t tests are carried out. Based on the normality test, it can be concluded that the pretest and posttest scores are normally distributed, because the p-value is greater than 0.05, namely 0.051 and 0.17. Next, a paired sample difference test (paired sample t-test) was carried out which showed a p-value of 0.000. These results show that there is a significant increase in students' computational thinking abilities after taking part in the learning.
 
Keywords: 
Research Based Learning; Science Technology Engineering Mathematics; Computational Thinking Skills
 
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