Data Collection Methods in Social Sciences: A Primer for Novice Researchers and Students

Abstract

Many early researchers and students sometimes face the challenges with the type of data they need and the methods that can help them collect data for their academic research. Some of them often struggle with selecting appropriate data types and methods, leading to delays in research progress. Scientific data collection is one of the most important stages of academic research. Poor data leads to poor and unreliable estimated results that cannot be used for shaping public policy, and helping governments and other stakeholders make informed decisions. Thus, this review aims to equip beginners with tools to design robust studies and complete their research efficiently. This study reviewed the relevant literature on the types of data and the data collection methods in social sciences. The narrative literature review focused on the studies that are relevant to the topic and are published in English. The study used published articles from databases such as ResearchGate, Scopus, Google Scholar, and Web of Science. The findings depicted that data can be categorized based on three main dimensions. These include the Nature of data (Qualitative, quantitative data or Mixed methods) and (Categorical or Continuous), Data source (Primary or Secondary data), Data collection (Cross-sectional, Longitudinal or Time series data). The literature search also showed that the widely used methods of data collection in social sciences include Interviews, Focus Group Discussions, Key Informant Interviews, Observations and Secondary data sources such as Archives, Records and Published documents. In general, researchers should choose the right type of data and data collection method that can answer their research objectives. This will ensure that they collect valid and reliable data that can guide policymakers and the government.