A critical goal of many school and training interventions is to provide learners with the strategies and foundational knowledge that will allow them to tackle novel problems encountered under circumstances different than the learning situations. This is also quite often referred to as the ability to transfer learning. Theories of transfer posit that providing learners with ways to make connections between learning experiences and possible transfer tasks, accumulating domain and strategic and knowledge, and encouraging diverse abstractions of concepts might help promote transfer to new situations. Notably missing among these theories is the role various motivational tendencies play in helping promote transfer. This dissertation describes the development of a new theoretical model linking transfer, self-regulation, motivation, and prior knowledge. Based on extensive empirical and theoretical evidence, the model posits that motivation plays an indirect role in promoting transfer of learning exerting its effect through increased self-regulation. This effect, along with a strong direct effect exerted by prior knowledge, describes the major motivational mechanism by which transfer occurs. The theory also proposes an underlying latent variable structure that groups interest, self-efficacy, and goal orientation as major indicators that measure motivation. Similarly, domain and strategic knowledge are posited as dimensions that encompass prior knowledge. Self-regulated learning is made up of a motivational and cognitive component. The cognitive components model key processes of the cognitive architecture that explains the general learning process. An effort to validate this theory through structural equation modeling (SEM) is described. This includes comparisons to alternative models and discussions about methodological issues related to model fit. The dissertation also features in-depth discussions about the appropriateness of the proposed latent structure as well as a comprehensive exposition of the validity of estimated parameters under conditions where model fit is considered unacceptable. The dissertation concludes with a set of derived conclusions and recommendations that advance the theoretical model towards a more encompassing and rigorous methodology calling for the development of more sensitive and adaptive measurement instruments. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]