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Application of the Tri-Square Method in Measuring Changes in Learner Performance: Illustrating Measurement via an Innovative Triostatistics Method and Statistical Procedure

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Title: Application of the Tri-Square Method in Measuring Changes in Learner Performance: Illustrating Measurement via an Innovative Triostatistics Method and Statistical Procedure
Language: English
Authors: Osler, James, Mutisya, Philliph M.
Source: Journal for the Advancement of Educational Research International. Fall 2019 13(1):70-88.
Availability: Association for the Advancement of Educational Research International. email: aaermeetings@gmail.com; Web site: https://rceglie.wixsite.com/website
Peer Reviewed: Y
Page Count: 19
Publication Date: 2019
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Statistical Analysis, Mixed Methods Research, Teacher Effectiveness, Measurement, Process Education, Taxonomy, Teacher Characteristics, Academic Achievement, Learning Strategies
ISSN: 2638-5023
Abstract: Measuring the impact of teaching on learning is necessary for discerning the relative effectiveness of different teaching models and methods. Frequently this determination is restricted to hypothesis testing involving the impact of a single variable on a specific performance measure. The common approach is to compare statistics for a treatment group versus a control group with a specified confidence level in order to accept or reject the hypothesis. While this approach may be adequate for clinical studies it is not very practical for a classroom environment where multiple input and output variables are in play. This paper presents the Tri-Square methodology from "Triostatistics" (Osler, 2014) for studying the interplay between a set of three input and three output variables within a culture or system to look for significance. This is a mixed methods model that can accommodate quantitative and/or qualitative variables. The value of mix methods statistical procedures was illustrated in a 2017 Academy of Process Education Workshop entitled, "Measuring The Impact of Teaching and Learning" conducted at the 2017 Academy of Process Education Conference. The power of the method is illustrated using student data from a recent Recovery Course. This paper illustrates the "PE: L2L" experiences, Triostatistics procedures, the PE philosophy, as well as models of the "Taxonomy of Process Education" first presented in the research article entitled, "AMOVA ["Accumulative Manifold Validation Analysis"]: An Advanced Statistical Methodology Designed to Measure and Test the Validity, Reliability, and Overall Efficacy of Inquiry-Based Psychometric Instruments". The authors provided a series of models from the book "Interactive Statistics Methods" (Osler, 2012) to illustrate the various statistical methods during the PE workshop. That data is provided in this narrative to further illustrate utility of the Tri-Squared methodology.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1252117
Database: ERIC
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  Data: Measuring the impact of teaching on learning is necessary for discerning the relative effectiveness of different teaching models and methods. Frequently this determination is restricted to hypothesis testing involving the impact of a single variable on a specific performance measure. The common approach is to compare statistics for a treatment group versus a control group with a specified confidence level in order to accept or reject the hypothesis. While this approach may be adequate for clinical studies it is not very practical for a classroom environment where multiple input and output variables are in play. This paper presents the Tri-Square methodology from "Triostatistics" (Osler, 2014) for studying the interplay between a set of three input and three output variables within a culture or system to look for significance. This is a mixed methods model that can accommodate quantitative and/or qualitative variables. The value of mix methods statistical procedures was illustrated in a 2017 Academy of Process Education Workshop entitled, "Measuring The Impact of Teaching and Learning" conducted at the 2017 Academy of Process Education Conference. The power of the method is illustrated using student data from a recent Recovery Course. This paper illustrates the "PE: L2L" experiences, Triostatistics procedures, the PE philosophy, as well as models of the "Taxonomy of Process Education" first presented in the research article entitled, "AMOVA ["Accumulative Manifold Validation Analysis"]: An Advanced Statistical Methodology Designed to Measure and Test the Validity, Reliability, and Overall Efficacy of Inquiry-Based Psychometric Instruments". The authors provided a series of models from the book "Interactive Statistics Methods" (Osler, 2012) to illustrate the various statistical methods during the PE workshop. That data is provided in this narrative to further illustrate utility of the Tri-Squared methodology.
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