Research Methodologies Explained

Research Methodologies, sometimes simply written as Methodologies or Methods, is the third section of a standard undergraduate thesis. Generally, this defines the processes and the elements included in order for the research to proceed and reach its completion.

To break it down, this section has a few main sub-sections namely the Approach, the Target, the Data Collection Process, the Data Collection Tool, and the Data Analysis.

The Approach refers to the perspective which information is going to be presented. In turn, this affects the type of data to be collected, as well as the tool and processes used to obtain the data. Mainly, there are two categories for this; Quantitative which means that the data to be collected can be represented with a numerical value, and Qualitative which means that the data to be collected is inclined towards being abstract ideas and such.

The Target refers to the individuals, items, instances, or events which will be analyzed in the study such as the opinion of people towards something, the amount of X in something, or the number of occurrence of something. In essence, this pertains to which would be the source of data for the study. In addition, this also encompasses the amount or volume of targets needed, also known as the sampling size.

The Data Collection Process refers to how such data would be obtained. Depending on the approach and what the target is, there are numerous choices to choose from. This includes the use of survey questionnaires, conduction of interviews, or a combination of both. Other forms are recordings, simulations, focus group discussions, and sometimes even immersions. Selecting which to use is a monumental factor that affects the outcome of the research.

The Data Collection Tool refers to the instrument which will be used for collecting data. This encompasses a wide selection such as questionnaires and evaluation sheets, up to the use of sophisticated equipment to gather information.

Lastly, the Data Analysis refers to how the collected information is going to be processed to make sense of what it means. Commonly this involves treatment ranging from the simplest descriptive statistical treatments up to the most complex algorithms.

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