Propensity score matching (PSM) has been used to estimate causal effects of treatment, especially in studies where random assignment to treatment is difficult to obtain. The main purpose of this article is to provide some practical guidance for propensity score sample matching, including definitions, procedures, decisions on each step, and methods of statistical analysis. The authors also implemented PSM in the data analysis of a study that examines factors affecting middle school students' technology-integrated science learning. Procedures of PSM are demonstrated and some cautions and tips for researchers in the field of education are included as well.