This study investigates the dynamics of theory and practice in the design of instructional systems, learning events and learning environments, with a view to synthesizing an integrated metamodel as a framework to facilitate effective learning in systems which use computer technology as a tutor, tool, or environment. This framework can be used as a design aid by instructional designers and instructor-designers, or as a tool to examine existing learning events from the viewpoint of learning and instructional-design theory. The research contributes to inquiry into learning theory by an in-depth study of the elements of the framework itself, investigating how they function in different contexts and contents.
Following an extensive literature survey, the researcher synthesizes a concise integrated framework of learning theories and instructional design practice from the cognitive family. This framework, the Hexa-C Metamodel (HCMm), is generated by a process of criterion-based textual filtration through effectiveness criteria, and encompasses the theoretical concepts of constructivism, cognitive learning and knowledge/skills components as well as the practical characteristics of creativity, customization and collaborative learning. Using mainly qualitative ethnographic methods within the contexts of action research and development research, case studies are undertaken, applying the elements of the HCMm as an inquiry toolset to investigate three diverse learning events to determine what they reveal about the practice of effective and motivational learning. The learning events - a computer-based practice environment, an Internet-based course, and a fieldwork project - were selected due to the researcher's close involvement with each intervention. Information from the evaluations of the learning events is then used to further examine in-depth the theories and characteristics which comprise the tool, as well as their interrelationships and ways of implementing them in domains that differ in context and content - distinguishing particularly between well-structured and ill-structured domains.