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Analyzing pedagogical components using multiple regression

Mia Kalish (Institutional Researcher and Adjunct Faculty, Math & Phys Science, Dona Ana Community College, New Mexico State University, Las Cruces, NM, USA)

On the Horizon

ISSN: 1074-8121

Article publication date: 9 February 2015




The purpose of this paper is to show how one instructor used an integrated collection of technological and cognitive tools that consistently led to student success. Educators today struggle with the need to improve student success in a dynamic and increasingly technological world. Learners need to master more, more quickly and educators need to upgrade their skills to meet these needs.


This vision-based research design focused on the goal that all students can succeed. The design took the non-traditional approach of separating pedagogical models that worked from those that did not. The objectives were achieved by successively improving the pedagogy. The components of the final model were evaluated using multiple regression to determine individual and summative effectiveness.


The pedagogical model designed around the goals of allowing adequate time for scaffolded acquisition and increasing skill development demonstrated consistent student success in the A and B grade range.

Research limitations/implications

A sophisticated knowledge of the issues involved underlies the actualization of this research. The success of the approach will be determined by the author’s ability to enable the method to function on its own.

Practical implications

With the increasing sophistication of teaching and learning tools, opportunities arise for more detailed and complex pedagogical analyses.

Social implications

With improved pedagogies, more students will succeed.


Using Microsoft® Excel® for evaluation of a pedagogical model that is also quantitatively analyzable.



This research that led to the development of this model was covered by institutional review board (IRB) #7422.


Kalish, M. (2015), "Analyzing pedagogical components using multiple regression", On the Horizon, Vol. 23 No. 1, pp. 1-6.



Emerald Group Publishing Limited

Copyright © 2015, Emerald Group Publishing Limited

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