A growing number of demographically diverse, globally-conscious students demand instant access and flexibility when it comes to formal learning. Institutions of higher education are hard pressed to respond, and often cling to old delivery methods and pedagogy. Learner-directed use of Web2.0 applications to locate, organize, and evidence individualized learning could be the bridge between the need for institutional change and implementation of that change. The purpose of this study was to determine how instructor attitudes and traits regarding learner self-direction and theorized covariates affect the instructional interest in, intent to use, and ultimate use of Web2.0 applications in formal learning environments. A conceptual model of these relationships was developed based on existing theory and knowledge in the realms of self-directed adult learning, technology acceptance, and diffusion of innovation. Data were collected from 285 North Carolina community college online instructors to be analyzed as identifiers of the eight latent variables in the conceptual model. Specifically, the latent variables were instructional attitudes toward learner self-direction (SD), instructional technology acceptance (TA), instructor innovativeness (IA), knowledge of Web2.0 applications (KNOW), interest in Web2.0 applications (INT), intent to use Web2.0 applications in online classes (BI), contextual constraints (CC), and current use of Web2.0 applications in online classes (USE). Eight research hypotheses were generated. The conceptual model was tested by analyzing its fit to the data. This process was completed using the principles of structural equation modeling (SEM) which required confirmatory factor analysis on the measurement model and path analysis on the structural model. During this process it was determined there was not enough variability in the data nor was there a level of current use to reach a conclusion about the impact that intent to use Web 2.0 applications has on use of those technologies. As a result the USE variable was dropped from the final model as allowed by SEM path deletion procedures. Once a final model was determined, research hypotheses were retained or rejected based on evaluation against that model. Results included the determination that knowledge of Web2.0 applications can predict instructor interest in those applications and that the interest can predict instructor intent to use Web2.0 applications in online classes. Results also indicated some hypothesized relationships were not significant. Specifically, attitudes and traits related to learner self-direction, instructional technology acceptance, and innovativeness do not significantly predict interest in Web2.0 applications. Similarly, contextual social and facilitative constraints do not significantly predict instructor intent to use Web2.0 technologies. The implications of these findings, in addition to adding empirical evidence to the body of knowledge, highlight areas for professional development, instructional design changes, and institutional changes as well as possibilities for future research.