A neuromathematical model of human information processing and its application to science content acquisition

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Abstract
The rate of information processing during science learning and the efficiency of the learner in mobilizing relevant information in long‐term memory as an aid in transmitting newly acquired information to stable storage in long‐term memory are fundamental aspects of science content acquisition. These cognitive processes, moreover, may be substantially related in tempo and quality of organization to the efficiency of higher thought processes such as divergent thinking and problem‐solving ability that characterize scientific thought. As a contribution to our quantitative understanding of these fundamental information processes, a mathematical model of information acquisition is presented and empirically evaluated in comparison to evidence obtained from experimental studies of science content acquisition. Computer‐based models are used to simulate variations in learning parameters and to generate the theoretical predictions to be empirically tested. The initial tests of the predictive accuracy of the model show close agreement between predicted and actual mean recall scores in short‐term learning tasks. Implications of the model for human information acquisition and possible future research are discussed in the context of the unique theoretical framework of the model.