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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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Inderscience
2022
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Subjects: | |
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. |
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