Mixed methods in multi-level sampling: a research paradigms teaching and learning case to spur downstream innovation - Zimano, Felistas R.; Chilunjika, Alouis (Inderscience, 2022)
The authors present a condensed use of select probability and non-probability sampling methods in different sampling levels showing the utility of mixed methods (MM) in finite/infinite and heterogeneous/ homogeneous populations. This is based on a Zimbabwe entry points' survey sampling prototype. Findings uphold the efficacy of both MM and multi-level sampling. The researchers uphold the marriage of methodologies in the MM configuration as permitting effective population coverage giving a sample that equitably captures the uniqueness of the population overcoming any disproportionateness that may be occurring in the sampling frame. The methodology consequently eliminates biases imminent in the coverage of a study area. Recommendations include the idea that researchers can utilise this method to ensure that all the various characteristics in a population are captured in their uniqueness. In the quest to promote innovativeness in education, educators can utilise this initiative as a teaching aid to expose learners to a variety of sampling paradigms ingeniously condensed in one place.