Mixed methods in multi-level sampling: a research paradigms teaching and learning case to spur downstream innovation

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 prototyp...

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Bibliographic Details
Main Authors: Zimano, Felistas R., Chilunjika, Alouis
Format: Article
Language:English
Published: Inderscience 2022
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Online Access:https://www.inderscience.com/info/inarticle.php?artid=102625
http://hdl.handle.net/11408/4629
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Summary: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.