This volume, which describes the development and experimental testing of a model of how knowledge is acquired (using LISP programming as the domain of interest), will be of value to all cognitive scientists, AI researchers, and cognitive psychologists.
This volume, which describes the development and experimental testing of a model of how knowledge is acquired (using LISP programming as the domain of interest), will be of value to all cognitive scientists, AI researchers, and cognitive psychologists.
Contents: Introduction and Overview. Part I: Cognitive Modeling of Learning. Computational Models of Knowledge Acquisition. The Levels Approach Toward Cognitive Modeling. Learning From Text. Integration With the Acquisition of Knowledge From Cases. Unified Model of Knowledge Acquisition and Experimental Predictions. Part II: Experimental Evaluation. The Influence of Different Learning Goals. The Acquisition of Equivalent Knowledge From Different Types of Study Materials. Material Transformation. The Effect of Prior Knowledge On the Learning From Different Types of Materials. An Experimental Comparison of the Integrated Knowledge Acquisition and the Example Dominance Hypotheses. Part III: Application, Discussion, and Prospects. Instructional Technology and Expert Systems. General Discussion, Conclusions, and Future Directions.
Contents: Introduction and Overview. Part I: Cognitive Modeling of Learning. Computational Models of Knowledge Acquisition. The Levels Approach Toward Cognitive Modeling. Learning From Text. Integration With the Acquisition of Knowledge From Cases. Unified Model of Knowledge Acquisition and Experimental Predictions. Part II: Experimental Evaluation. The Influence of Different Learning Goals. The Acquisition of Equivalent Knowledge From Different Types of Study Materials. Material Transformation. The Effect of Prior Knowledge On the Learning From Different Types of Materials. An Experimental Comparison of the Integrated Knowledge Acquisition and the Example Dominance Hypotheses. Part III: Application, Discussion, and Prospects. Instructional Technology and Expert Systems. General Discussion, Conclusions, and Future Directions.
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