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This study begins with a definition of the affective domain and its importance to learning, outlining its impact both in achieving affective behaviors and in facilitating cognitive and psychomotor objectives. The study then develops a model of instructional design that incorporates the affective domain as an integral component. The model combines J. Keller's ARCS (Attention, Relevance, Confidence, Satisfaction) model of motivation for learning with the five-phase military instructional design model (analysis, design, development, implementation, and evaluation). The proposed model provides a framework for organizing instructional principles, strategies, and techniques concerning the affective domain and furnishes a theoretical base to aid in formulating research hypotheses and collecting empirical data. The model is designed to help in providing for systematic consideration of the affective domain in every aspect of the instructional design process, from curriculum planning and design through lesson development, delivery, and evaluation of learning results. Attention to the affective domain is viewed as being particularly important for technology-based instruction that removes teacher/student interaction from the lesson delivery. The study concludes with recommendations for research needed to operationalize the model. (Contains approximately 40 references.) (JDD)

A more comprehensive definition of the variable "interaction" is needed to answer the numerous questions concerning interaction effects in distance learning. This study attempts to qualify the concept of interaction by applying various dimensions such as amount, timeliness, method, spontaneity, and quality. In turn, these dimensions of interaction lend themselves to the creation of a taxonomy for research and evaluation purposes. Background information on instruction, communication, and interaction is provided. The relationship of interaction to other instructional variables, such as instructional strategy and course variables, is outlined. The paper concludes by recommending further research to enhance the interaction taxonomy and the overall body of knowledge relating to distance learning. (Contains 34 references.) (MAS)