A data collection technique aims to collect data for research projects. Research projects could be academic, government, or business projects. Data collection can be either qualitative or quantitative, depending on the nature of the research. For your research to be meaningful and have a lasting impact, it is vital to collect quality information. Missing links in data and incomplete information can lead to half-baked hypotheses and results.
There is a huge amount of data available on the Internet due to the increased storage capacity. Big Data is on the rise, and everything is available online about any subject. Social networks, the Internet of things, and scientific experiments are the catalysts for the rise of Big Data. Researchers must be selective while collecting data. They should use smart data collection techniques to avoid unnecessary information.
Following data collection techniques are vital for both qualitative and quantitative research projects. The selection of these data collection techniques depends on the nature of your research problem.
Secondary Data Collection
But, researchers find it difficult to collect relevant data due to the huge volume of data. At the end of this article, you will know about various data collection techniques for a large amount of complex information. Let’s discuss this in detail.
|Data Collection Technique For A Large Amount Of Complex Information|
What Are The Types Of Data Collection?
It is important to be aware of various types of data collection. Data collection falls under two broad categories: Primary and Secondary Data Collection. Experts of dissertation writing services UK will explain the both below;
1. Primary Data Collection
Primary data is the raw information collected by researchers. It is relevant to their research problems and research questions. The researcher collects the original data through experiments, surveys, interview/focus groups, observation, ethnography and archival research. These data collection techniques are useful to collect primary knowledge about a subject area. The data could be further evaluated by doing qualitative or quantitative analysis.
a) Data Collection for Qualitative Research
Data collection for qualitative research does not need quantified data such as numbers or mathematical calculations. The data collection technique for qualitative research is non-quantified. It collects the opinions of people, registers their feelings and emotions. For that purpose, open-ended questions are the most effective.
b) Data Collection for Quantitative Research
Data collection techniques for quantitative research encompass the collection of quantified data. They could be either statistics or numbers which are mathematically deducible. For that purpose, experiments are useful as well as close-ended questions. The most effective data collection technique is the mean median mode. Also correlational, and regression analysis is effective.
2. Secondary Data Collection
Secondary data collection is different from primary data collection. A researcher collects second-hand data relevant to the research problem. The data collection technique in secondary research utilizes books, journal articles, reports and online sources. It is more convenient and cost-effective, but it only helps find gaps in the study. It is more useful for qualitative research. But, there are plenty of books and online journals in libraries and on the Internet. The researchers have to be selective. They should use smart methods to filter the data relevant to their research.
Data Collection Technique
Surveys and Questionnaires
Both quantitative and qualitative methods use surveys and questionnaire data collection techniques. These types of data collection techniques depend upon the following methods.
Questionnaires are a series of questions relevant to the research problem and gather responses from individuals. Researchers use questionnaires in both qualitative and quantitative research methods.
Sampling: An effective data collection technique for collecting a large amount of information
It is impossible to gather information at one time without clearly defining the boundaries. Sampling is a data collection that makes it easier for researchers to gather information through surveys. The researcher must first define a population of interest relevant to the research problem. An effective data collection technique through surveys is to divide the population into sets and subsets. The following methods prove to be effective.
i. Cross-Sectional Survey
A cross-sectional survey assigns the survey to a population sample or the entire population at a single moment.
ii. Repeat-Cross Sectional Survey
Repeat-cross sectional survey assigns the survey to different population samples at different moments.
iii. Longitudinal Survey
Longitudinal survey assigns the survey to the sample of individuals at different time points.
The Survey data collection technique is cost-effective and collects data from a large number of population. If the sample size of the population is large, the researcher can use above mentioned techniques to collect information.
How To Sift Through This Large Information?
Gathering responses from a large number of population can be overwhelming for a researcher. For that purpose, researchers do sampling by using probability methods. The researcher selects important survey respondents to understand social and political demographics. It helps to understand the opinions, attitudes, skills and preferences. The probability method saves time because you will not collect data from the entire population.
Data Collection Techniques For Field Research
Data collection for research requires smart methods. Field research requires a large amount of complex information. It is a qualitative method that yields valuable data for researchers to uncover new social facts. Field Research aims to collect qualitative information. It is based on observing, understanding and interacting with people in their natural settings. Following data collection techniques are necessary for field research.
- Step 1
You cannot do everything on your own. So, it would help if you had a team of skilled researchers to collect data.
- Step 2
Researchers must define the duration of the study, financial limitations and the type of study they want to conduct.
- Step 3
Use sampling methods and probability to sift through a large amount of data.
- Step 4
Use a mixture of surveys, interviews, case studies and observations to collect information.
- Step 5
You cannot collect all the data at one moment. An effective data collection technique is to make inferences through statistical analysis. You can use probability methods for that.
Smart data collection technique is important to manage large amounts of information for a research paper. A researcher must not stray from the original purpose of the research. A researcher should only seek the information relevant to the research problem. The population sampling for surveys and field research should be done through probability methods. It helps to save time without compromising the validity of the data.