Statistical Techniques for Project-based Learning

Abstract

Although present for a long time, project-based learning is still the very focus of researchers because of its potential to improve the learning process. New technologies provide opportunities for a better understanding of the data generated by the learning process. This literature review searches for statistical techniques used in the field of project-based learning and classifies them in line with common classifications found in the field of statistics. The goal is to identify the most common statistical techniques used in the field and explain the way they are applied in the research. The results show that the most often statistical techniques are descriptive statistics and inferential statistics, followed by factor analysis, regression analysis, correlation, and social network analysis. This result arises from the type of research design, which is in most cases quasi-experimental, where researchers try to measure the influence of project-based learning on different dimensions of learning outcomes. This kind of research design usually employs descriptive statistics as a preliminary step, followed by statistical tests.