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The Triangulation Algorithmic: A Transformative Function for Designing and Deploying Effective Educational Technology Assessment Instruments

James Edward Osler II*

North Carolina Central University.

Periodicity:April - June'2013
DOI : https://doi.org/10.26634/jet.10.1.2303

Abstract

This paper discusses the implementation of the Tri–Squared Test as an advanced statistical measure used to verify and validate the research outcomes of Educational Technology software. A mathematical and epistemological rational is provided for the transformative process of qualitative data into quantitative outcomes through the Tri–Squared Test as an efficient technique for the rapid testing of software applications designed for the educational setting. The design of fixed-parameter algorithms for software engineering problems can prove to be beneficial to the Educational Technologist who has to efficiently and rapidly evaluate a software tool for deployment. This novel methodology provides elegance and has a wide range of applicability to practically address important and relevant problems in the “trial and error” process of application evaluation. This research is the continuation of a dynamic mixed methods approach that is a transformative process which changes qualitative data into quantitative outcomes through the Tri–Squared statistical measure first introduced in i-manager's Journal of Mathematics

Keywords

Algorithmic Model, Algorithmics, Cartesian Coordinates, Geometric Vectors, Mathematical Models, Meta–Cognitive Analysis, Research Engineering, Triangulation, Trichotomy, Tri–Squared, Tri–Squared Test,And Vectors.

How to Cite this Article?

Osler , J. E. (2013). The Triangulation Algorithmic: A Transformative Function for Designing and Deploying Effective Educational Technology Assessment Instruments. i-manager’s Journal of Educational Technology, 10(1), 46-54. https://doi.org/10.26634/jet.10.1.2303

References

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[6]. Osler, J. E. (2012). Trichotomy–Squared – A novel mixed methods test and research procedure designed to analyze, transform, and compare qualitative and quantitative data for education scientists who are administrators, practitioners, teachers, and technologists. July – September. i-manager's Journal on Mathematics. Vol. 1, No 3.

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