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SLP3

 

Data Sources and Data Collection Procedures

Introduction: In Module 3 of the Session Long Project, we will delve into the data sources and data collection procedures for our hypothetical research study. Building upon the methodology components chosen in previous modules, we will outline the step-by-step processes involved in data collection, ensuring clarity and comprehensiveness in our approach.

Identifying Data Sources: Describe what types of data sources you could use in your study. Be sure that the sources you choose align with the chosen methodology.

Primary Data Sources:

  • Identify primary sources of data that will directly contribute to answering the research questions. This may include:
    • Surveys
    • Interviews
    • Observations
    • Experiments

Secondary Data Sources:

  • Identify secondary sources of data that may provide additional context or support for the study. This may include:
    • Existing datasets
    • Published literature
    • Government reports
    • Institutional records

Data Collection: Define Population and Sampling Strategy:

Clearly define the target population for the study based on the research objectives.

Determine the appropriate sampling strategy (e.g., random sampling, stratified sampling) and sample size to ensure representativeness and generalizability of findings.

Describe the data collection instruments (e.g., surveys, questionnaires, interviews) tailored to the research questions and methodology.

Define how you would determine that an instrument was valid and reliable. 

Develop chronological steps that could be carried out. These should be step by step and so detailed another researcher could carry out the study. 

Conclusion: In conclusion, Module 3 has provided a detailed overview of the data sources and data collection procedures for our hypothetical research study. By carefully outlining each step of the data collection process, we ensure transparency, rigor, and replicability in our research design. Moving forward, we will proceed to Module 4, where we will focus on data analysis and interpretation. 

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