Date of Award


Document Type


Degree Name

Doctor of Education (EdD)


Human Resource Education and Workforce Development

First Advisor

Joe W. Kotrlik


The objectives of this study were to: determine the housing practices of the Louisiana Cooperative Extension Service housing audience and of the general public (for use in program planning); determine if significant differences existed between the housing practices of the general public and the Extension housing topic audiences (for accountability and impact assessment); and, determine if household characteristics are significant predictors of housing practices. The research procedure utilized a "comparison group" design. Data were collected in 1984 from matched random samples of the Extension housing audience and the general public of Louisiana. Over 800 telephone interviews were completed by Extension Home Economics in 21 randomly selected parishes. Analysis of covariance was used at the.05 level to test for significant differences between the general public and the Extension topic audience subgroups. Stepwise multiple regression was used at the.05 level to develop models of the household characteristics which predicted housing practices. On a statewide basis, housing education efforts prior to 1984 had a significant positive impact upon adoption of practices and knowledge of participants in all housing topics included in this study except space-efficient design and contrasting precautions. The most substantial effect was in the adoption of energy-efficient design features, though participants' homes were still not close to recommended standards. The remaining housing topics included in this study are home selection, home finance, energy cost, cost-cutting construction methods, remodeling value analysis, kitchen design, home maintenance and home repairs. All the regression models of housing practices on household characteristics were statistically significant. In each case, household characteristics accounted for under one-fourth of the variance of housing practices. The strongest prediction models (R$\sp2$ $<$.20) were those determined for the dependent variables: contracting, home selection, energy-efficient design, and energy cost.