There
are two types of research designs: descriptive and explanatory research. Descriptive
research design is also known as qualitative research, which aims to answer
questions such as what exists or happens in society. Explanatory research
design, which is known as quantitative research, aims to answer questions such
as why does it exist or happen. In other words, qualitative or descriptive
research aims to answer questions to how something happens, while quantitative
or explanatory research aims to answer why questions.
According to the PDF slides developed by
Tero Mamia, Quantitative research aims at explaining problems, issues, and
results through the use of numbers. It is based on the idea that social
phenomena can be quantified, measured and expressed numerically (Mamia).
Basically the goal of quantitative research is to determine the connection
between independent and dependent variables. A variable is an observable and
measurable unit that can then be used to compare other observable measurable
units. This type of research generates numerical data that can be analyzed by
statistical methods. The numerical data is often collected in the form of
surveys or questions. For example, ERAU survey asks students to rate his or her
teacher’s performance. Typically, these types of surveys have number answers,
such as 5 for very satisfied to 1 very dissatisfied. To my understanding these
numbers or observations are then processed into a data matrix for analysis.
There
are various strengths and weaknesses to quantitative research. Some of the strengths
are: it enables research and description of social structures and processes,
allows for comparisons between variables, gives a description of change, and it
analyses and explains social phenomena dependencies. The weaknesses of
quantitative research are: it simplifies and compresses reality, only
applicable to quantifiable phenomena, and it assumes the researcher has
extensive knowledge on the subject in order to ask the correct questions on the
survey (Mamia).
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