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

Authors: Felistas R. Zimano; Alouis Chilunjika

Addresses: Politics and Public Management Department, Midlands State University, Zvishavane and Harare Campuses, P. Bag 9055, Gweru, Zimbabwe ' Politics and Public Management Department, Midlands State University, Zvishavane and Harare Campuses, P. Bag 9055, Gweru, Zimbabwe

Abstract: 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.

Keywords: mixed methods; multi-level sampling; probability sampling; finite populations; non-probability sampling; heterogeneous populations.

DOI: 10.1504/IJIIE.2019.102625

International Journal of Innovation in Education, 2019 Vol.5 No.4, pp.323 - 339

Accepted: 07 Mar 2019
Published online: 27 Sep 2019 *

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