RBL-STEM learning activity framework: Improving students' computational thinking skills for solving strong rainbow antimagic coloring and its application scheme to analyzing river erosion using STGNN.

Computational thinking refers to a problem-solving approach that draws on concepts and techniques from computer science to address complex problems and tasks. It is not just limited to computer programming, but it is a fundamental skill set that can be applied to various fields and everyday life. In this era, these skills should be endorsed in the classroom so that the young generation possesses these skills. However, in reality, students' computational thinking skills still need to improve since the learning model applied in the classroom has yet to be able to foster these skills. The indicators of computational thinking consist of problem decomposition, algorithmic thinking, pattern recognition, abstraction and generalization. This paper described the learning activities of RBL-STEM to improve students' computational thinking skills in solving the strong rainbow antimagic colouring (SRAC) problem and its application scheme to analyzing river erosion using spatial, temporal graph neural networks (STGNN). Let G(V(G), E(G)) be a connected, undirected, and simple graph with vertex set V(G) and edge set E(G). By SRAC, we mean that for a bijective function f: V(G)→1,2,...,|V(G)|, the associated weight of an edge uv∈E(G) under f is f(uv)= f(u)+f(v), the function f is called an edge-antimagic vertex labelling if for every edge has distinct weight. If for every two vertices u and v of G, there exists a rainbow u-v geodesic path, then f was called a strong rainbow antimagic labelling of G. This research uses a qualitative narrative approach, starting with developing a prototype of the application scheme in analyzing river erosion using RAC and STGNN and continues with formulating the stage of learning activities in regards with RBL-STEM. The results of this research are in the form of an RBL-STEM learning framework consisting of six stages of learning activities, which have been ready to be used on the RBL-STEM maker space learning materials development for further research. [ABSTRACT FROM AUTHOR]