Differences in learning motivations of professionals and nonprofessionals participating in two south Mississippi Institutes for Learning in Retirement
This study investigated the differences in learning motivations of (a) professional and nonprofessional, and (b) urban and rural members of two south Mississippi Institutes for Learning in Retirement (ILR) programs in an attempt to expand C. O. Houle's conceptual model of continuing professional education into the retirement years and to determine if the life transitions of the older adult unite the learning orientations of these subpopulations into self-actualizing (growth) motives as part of the maturation process identified y Abraham Maslow. Ninety urban ILR and 60 rural ILR members were recruited. Professional was defined as having completed a bachelor's degree or above and licensure, certification, or registration. Variables were measured quantitatively using Roger Bashier's Education Participation Scale A-Form and qualitatively using open-ended questions on a demographic data survey collected using a one-time cross-sectional assessment of six intact groups at each location. Data were analyzed by multivariate analysis of variance, chi square, and content-thematic coding. Significant findings (.05 level) indicated that nonprofessionals have pluralistic motives while professionals are motivated by intellectual curiosity. Cognitive Interest was the strongest motivator for all persons surveyed followed closely by Social Contact. Rural participants were more likely influenced by all motivational orientations than were urban members. Adventure learning for fun and pleasure was identified as a separate category from qualitative analysis. These findings are similar to the findings of previous research but expand the knowledge of the professional model into the postcareer years as well as providing a clue to learning motives for isolated, disadvantaged older adults who can benefit from expanded availability of programs into difficult to reach areas. These conclusions suggest that the needs of the often hard-to-reach older adult can be met with the ILR model and that additional models to include the underserved elderly populations should be developed.