Understanding the Fundamental of Quantitative and Qualitative Research Methodology and Techniques

A common phenomenon in research is that many researchers, especially beginners, find it difficult to understand the difference between quantitative and qualitative methodologies, leading to frequent inconsistencies between the methods used and the research objectives. The basic assumption in this study is that the success of the research is highly dependent on mastering the appropriate methodology and techniques according to the characteristics of the data and the problems faced. The main problem arises when researchers do not understand the appropriate data types, variables, and analysis techniques, resulting in less valid research findings that are difficult to apply in practice. Therefore, the purpose of this writing is to provide a clear and systematic understanding so that researchers can choose and apply the appropriate methods, resulting in accurate and relevant findings for the development of science and practice in the field.
First, quantitative and qualitative data are used for research with variable analysis to explain the relationships between factors. The measurement scale determines the appropriate analysis method, while the validity and reliability of the instrument ensure the accuracy and consistency of the data. A comprehensive understanding of this aspect is crucial for ensuring the reliability of research findings and providing a basis for effective decision-making.
Second, the population is the entire research object, while the sample is the portion representing the population selected using probability or non-probability techniques. Data collection instruments such as questionnaires, observations, interviews, tests, and documents must be selected and tested for validity and reliability to ensure accurate and trustworthy data. Instrument trials are important to ensure the measuring tool is appropriate and unbiased. Selecting the right sample and instruments is key to research that is valid and useful for decision-making.
Third, data collection techniques in quantitative research generally include questionnaires, tests, structured observations, and experiments that produce numerical data and can be statistically analyzed, whereas in qualitative research, in-depth interviews, participant observation, documentation, and group discussions are used to collect data in the form of narratives, images, or documents that delve into a deep understanding of social and cultural phenomena. The main strategies for ensuring data quality are triangulation, instrument testing, training data collectors, and complete documentation; all of these aim to maintain the validity, reliability, and ethics of data collection so that research results are accurate, accountable, and support effective decision-making.
Fourth, data analysis in quantitative research involves correlation techniques such as Pearson, Spearman, and Kendall to determine the relationship between variables, as well as simple and multiple linear regression to measure the influence of independent variables on the dependent variable. Interpreting statistical results using correlation coefficients, p-values, and R is crucial for providing scientific and practical meaning. The results are reported using a combination of tables, graphs, and narratives to make the data easy to understand and serve as a basis for effective decision-making. This technique is very important in educational management for formulating evidence-based policies and improving the quality of education.
Summary Quantitative research uses an objective approach, collects numerical data thru questionnaires or experiments, and analyzes it statistically to test relationships between variables and generate generalizable findings. In contrast, qualitative research employs a subjective and interpretive approach, gathering non-numerical data such as interviews, observations, and document analysis to gain an in-depth understanding of phenomena without the goal of generalization. The main differences lie in the objectives, data collection methods, data types, analysis, and final results of the research. Understanding these differences is crucial for researchers to select methods appropriate for their research objectives and nature.