PREDICTING METRICATION INTENTIONS OF INDUSTRIAL ARTS TEACHERS USING A THEORY OF REASONED ACTION
Abstract
This study investigated the applicability of Ajzen and Fishbein (1980) model for a theory of reasoned action to metrication behaviors of industrial arts teachers and evaluated the extent to which individual differences contribute to the prediction of metrication intentions. Instruments measuring facets of the Ajzen and Fishbein model related to metrication in the classroom were developed by the researcher as a result of an elicitation session involving industrial arts teachers in Indiana. For the main study instruments were administered to 356 high school industrial arts teachers, one per high school in Indiana. Instrument items measured the attitudes toward the act of metrication (A(,act)), perceived likelihood of various consequences of metrication (B(,i)), evaluations of these consequences (e(,i)), the subjective norm (SN), normative beliefs (NB(,i)), motivation to comply (MC(,i)), and metrication intentions (I). Demographic information, metric knowledge, education, and work experience were also assessed. Prediction of intentions and the influence of external variables on the model were tested using stepwise multiple regression. It was concluded that an industrial arts teacher's intentions to perform metrication behavior is predictable from a combination of his/her attitude toward that behavior and his/her subjective norm. Adding external variables to the two predictor components of the Ajzen and Fishbein model improved the prediction of metrication intentions for industrial arts teachers. Both prediction models were significant (p < .01), but in each case a large portion of variance remained unaccounted for. Further study on the sufficiency of the Ajzen and Fishbein model for the prediction of intentions and the application of the model to other resistance areas of concern to industrial education was recommended. Refinement and revision of the study for future metrication research was cited. Further model development and identification of other demographic variables to predict metrication intentions of industrial arts teachers was recommended.
Degree
Ph.D.
Subject Area
Inservice training
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