When students attempt multiple-choice questions (MCQs) they generate invaluable\ninformation which can form the basis for understanding their learning behaviours. In\nthis research, the information is collected and automatically analysed to provide customized,\ndiagnostic feedback to support students� learning. This is achieved within a web-based system,\nincorporating the snap-drift neural network based analysis of students� responses to\nMCQs. This paper presents the results of a large trial of the method and the system which\ndemonstrates the effectiveness of the feedback in guiding students towards a better understanding\nof particular concepts.
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