Three Day Workshop on Research Methodology: Qualitative and Quantitative approach and Data Collection Methods using CAPI

Abstract

The three-day workshop on "Research Methodology: Qualitative and Quantitative approach and Data Collection Methods using CAPI was organized at IIPA from 3rd -5th December. The aim was to orient the research aptitude and analytical skills of the scholars. It imparted scholars with basic concepts, techniques, and skills in the qualitative and quantitative data collection and report writing. CAPI technology for data collection was also part of the workshop. Scholars got an opportunity to learn data analysis through the application of software like SPSS. The workshop ended with the field visit to Gurawra village, Rewari District, India's first fully digital village with Bharatnet. The workshop scheduled in various sections with the motivation to have a meaningful interaction with diverse knowledge and technical understanding. Shri Akhil Bhatnagar, a Software Developer, took the session on CAPI applications. The significant parts of his presentation were as following- Basic Introduction to CAPI, Terms, and Terminology, Objectives, Technology Overview Modules: Mobile app, Server-based Software, MIS. , Features of CAPI: GPS, Photographs, Time Stamp, Audio Recording and Video Recording, Signature Capture, Data Uploading in Real-time, Data Emailing. Unique Features of CAPI: Hold and Resume, Data Preview (Offline and Online model) Data Quality Research: Mandatory Questions, Skip Logic, Data Validation, Data Consistency, and Survey Branching, Data Quality: Logical Checks, Range Checks, Value Checks, Numeric Entries only, Total/ Sub-total. , System Architecture of CAPI, Benefits. Work Flow, Sample Sources of a questionnaire: Upload and Restore of Data Sets, Sample Dashboard. Filling of Questionnaire also there were unfolded some of the benefits of CAPI like; it reduces the time lag between data collection and data analysis. The manual coding of the responses recorded with pen and paper is no longer necessary. Data validation at the time of data collection and the information is ready for statistical analysis as soon as the survey is completed. It reduces the number of coding errors. Surveys can contain validation data that make it impossible to enter values outside a given range. Supervisors may also view and check the collected information as soon as the enumerators finish the interviews, together with possible error reports. Automated routing reduces the incidence of missing data.