A Systematic Review on Teaching Strategies for Fostering Students’ Statistical Thinking

Abstract

In the 21st century, many people need to learn statistical thinking to be literate. Global crises such as COVID-19, climate change, and IR 4.0 have disrupted economic, employment, and education systems. The global labour market and human capital needs are also evolving fast. New jobs, including those of artificial intelligence experts, data scientists, data engineers, big data developers, and data analysts, are increasing the need for statisticians. These experts are in demand, yet some students and instructors find statistics challenging to grasp. Consequently, a comprehensive evaluation was undertaken to ascertain instructional and educational approaches to augment statistical reasoning, according to the recommendations outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. The publications under examination were published between 2015 and 2023 and were retrieved from the Scopus and Web of Science (WoS) databases. Further review of these articles resulted in eleven themes. The study results show that statistical modelling methods and real-world data are two of the most effective ways to improve statistical thinking. Ultimately, this study led to many ideas to help people learn how to think statistically.