Bibliometric Analys Related to Problem Solving Ability in Physics Learning in The Range of 2018 - 2023

Abstract

The existence of several abstract concepts contained in physics learning causes low student skills in solving problems (Problem Solving).  This study aims to examine the number of journal publications, researcher productivity, research trends or topics that are often researched regarding problem solving or problem solving during 2018-2023, top publishers, top articles that are widely cited from the Scopus database through bibliometric analysis using VOSviewer software with the keyword "Problem Solving in Physics Learning". Based on bibliometric analysis, the results obtained based on the metadata obtained show an unstable writing trend from 2018 to 2023. A lot of research was studied related to problem solving in 2022. This study shows that the Division of Applied Mathematics from Brown University, United States is the top publisher. Meanwhile, the top article that is widely cited is an article with the title Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations with the author's name Raissi and the number of citation as many as 2902. In the visualization of the relationship, the keyword problem solving displays most of the clusters in red, as well as in the density visualization display with the keyword problem solving showing clusters with lighter colors. Then the researcher who has the top research productivity is Karniadakis g. e. In density visualization with country variations dominated by Indonesia, the United States, and China, indicated by the lighter cluster color than other countries.