Optimal Automated Method for Collaborative Development of University Curricula
نویسنده
چکیده
Aspects of curriculum design automation using semantic analysis of Web texts to develop candidate keywords and voting alternatives, as well as methods of optimal aggregation of individual expert decisions are presented. It is shown how semantics analysis of online texts can help with: generating of initial version of the curriculum; generating of candidate keywords and alternative options for improving the curriculum; building hierarchy of categories of the subject area or domain; detecting the change of domain knowledge state and defining structural knowledge dependencies; monitoring terminology and knowledge base of the subject area or domain. It is shown how the techniques of optimal integration of individual expert decisions in selecting of automatically generated alternatives helps to create the highest quality curriculum.
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