Transformational Research Engineering:Research Design Metrics for In–Depth AndEmpowering K–12 Teacher Professional Development

James Edward Osler II*
North Carolina Central University
Periodicity:June - August'2013


This paper discusses the implementation of the Tri–Squared Test as an advanced statistical measure used to verify and validate the research outcomes. This type of statistical measure is ideal for teachers professional development as educators can create and validate instruments for educational settings. The initial research investigation published in i-manager's Journal on School Educational Technology determined that these types of research on academic programs provide an active solution that validates in–depth educational researches by teachers to positively impact the educational settings. The research methodology used in this paper further validates the outcomes of an initial study that used Meta–Cognitive Analysis followed up by an in–depth Tri–Squared Test on that same area to determine the reliability of educator–based investigative inquiry. This advanced approach to data analysis is a transformative mixed methods research design that involves the in–depth comparison and transformation of qualitative outcomes into quantitative data.


9thGrade Freshman Academies, Algorithmic Model, Algorithmics, At–Risk, Cartesian Coordinates, Centers, Center Models, Drop–Out, 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). Transformational Research Engineering: Research Design Metrics for In–Depth And Empowering K–12 Teacher Professional Development.i-manager’s Journal on School Education Technology, 9(1), 43-60.


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