Post COVID-19: New breakthroughs and the future of behavioural research data collection

Abstract

Behavioural researchers have been faced with challenges associated with the choice of data collection methods that is timely and cost-effective for all situations. Several studies have examined various means of collecting data while some electronic means of data collection have been explored. However, there is a need for a study that compares the conventional and contemporary data collection methods in terms of profile, perceptions and prospects. Therefore, this study examined the new breakthroughs and the future of behavioural research data collection in post COVID-19 era. The study is underpinned by connectivism learning theory within ex-post facto design with a sample of one hundred and twenty-six (126) behavioural science researchers. Post COVID-19 Data Collection Methods Scale-Forms App (r=0.86) was used, and the data collected were analysed using frequency count and t-test. The findings showed that there were more users of breakthrough methods 47 (37.3%) than conventional 39 (30.9%) and mixed method 40 (31.7%). Conventional methods were less available than new breakthrough methods. There is a significant difference in the perception, challenges and prospects of the conventional and breakthroughs in behavioural research data collection methods, all in favour of new breakthroughs. It is, therefore, recommended that behavioural researchers, as well as other researchers, avail themselves of the opportunities offered by the new breakthrough to advance their research endeavours in post COVID-19 era.

Keywords

• post covid-19
• research
• breakthrough
• data collection
• connectivism learning theory