Data collection
Scientific data collection involves gathering and measuring information on variables in a topic. In data collection, a systematic method is designed to help answer the stated research question, test the given hypothesis, and evaluate the research outcome. Data collection is one of the most important steps in research. It helps create and maintain the study’s integrity and results (West et al., 2020).
In data collection, the first thing that helps in maintaining integrity is quality assurance and quality control. Quality assurance is carried out before data collection begins and helps prevent uncertainty in data collection and standardize the protocols in the activity. Quality control occurs throughout the process of data collection (Huebner & Mahdavi, 2019). It deals with error detection and correction during and after the collection of data. Additionally, it identifies the critical response necessary to correct wrongly collected data. There are two major methods of data collection; qualitative and quantitative data collection. Quantitative methods involve things that can be counted, while qualitative deals with factors other than numerical values. Quantitative methods include surveys, questionnaires, and documents, while qualitative methods include interviews, observations, and oral narrations (Fiesler, Beard, & Keegan, 2020).