Educational objectives and measurement of outcomes

Daniel F Luecke and Noel F Mcginn

Omega, 1975, vol. 3, issue 6, 717-734

Abstract: Correlation and regression analysis are often used to infer causal relationships in dynamic systems, even though computed on cross-sectional static data. In education these analytic techniques have been used to support assertions that school-controlled variables make little contribution to student learning. Critics of these assertions point to the low quality of the data, but it may be that the techniques themselves are inappropriate for the development of inferences of causality. This study simulated four possible models of dynamic relationships between family and school inputs and achievement outcomes. The models were run for five periods. Data generated were submitted to correlation and regression analysis. Both unique variance and regression coefficient indicators failed to describe reliably causal relationships built into the models. Conclusion: complex systems resist simplistic analyses.

Date: 1975
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