2. A brief introduction to research design

This chapter introduces the foundational principles of research design, emphasizing the interplay between data collection and analysis. It provides an overview of the key concepts in operationalizing theoretical constructs into measurable variables and highlights the different scales of measurement—nominal, ordinal, interval, and ratio—along with the distinctions between continuous and discrete variables. The chapter also delves into assessing the reliability and validity of measurements, defining their roles in ensuring consistent and accurate data collection. Additionally, it explores the roles of variables, distinguishing predictors from outcomes, and provides an understanding of the critical differences between experimental and non-experimental research designs. The focus is on equipping readers with tools to critically evaluate existing research rather than designing studies from scratch.

A significant portion of the chapter is dedicated to potential threats to research validity, including confounders, artefacts, history and maturation effects, and biases such as selection and non-response bias. The chapter also addresses specific challenges like experimenter bias, demand effects, and the complexities of interpreting Likert scale data. It outlines methodologies to mitigate these risks, such as randomization and double-blind designs, while acknowledging the inherent limitations of research studies. Concluding with a discussion of the importance of understanding reliability and validity, the chapter reinforces the necessity of sound research design for producing trustworthy and generalizable findings.