A Blended Teaching Procedure of Spatial Statistics Course based on the Knowledge Map Analysis of Teaching Methods of Science.

The era of big data has brought increasing attention to spatial statistics due to the vast amounts of spatially-referenced data from sources such as remote sensing, GPS tracking, and social media. However, traditional spatial statistics courses are often teacher-centered, leading to students struggling with the concepts and lacking practical application skills. This article presents a knowledge map analysis of science education teaching methods and proposes a novel teaching procedure for the spatial statistics course. Bibliometrics and scientific mapping techniques were employed to analyze citation data from the Web of Science (WOS) and China National Knowledge Internet (CNKI) from 2000 to 2022. The study identified the research status and development trends of science teaching methods and proposed a blended teaching approach based on an intelligent problem library, combining multiple methods and online teaching materials, to enhance students' learning outcomes. This research offers valuable insights into effective teaching methods, emphasizing the need to adapt strategies to specific course requirements. It also highlights the usefulness of R and VOSviewer software in conducting knowledge map analyses of teaching methods in science education. Although further testing is necessary to determine the effectiveness of the proposed reform, this study has significant implications for science education.