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This work advances basic research in the areas of learning and training. One product is a conceptual framework, which addresses the ways explicit and implicit knowledge interact to produce skills. This framework suggests that human performance may be controlled by either a subconceptual knowledge base (the implicit mode) or application of a symbolic conceptual model (the explicit mode). A computational cognitive architecture, CLARION, significantly different from other existing cognitive architectures, is developed in this work to capture a range of data related to the interaction. It helps us to explain (and eventually to predict) training and learning processes. The results of the experiments support the theory of the interactions of implicit and explicit learning processes during skill acquisition. The outcomes (data, models, and theories) provide a more detailed, clearer and more comprehensive perspective on skill learning.