SIGCSE '99 The proceedings of the thirtieth SIGCSE technical symposium on Computer science education
Introductory programming, criterion-referencing, and bloom
SIGCSE '03 Proceedings of the 34th SIGCSE technical symposium on Computer science education
Development of an instrument to measure stress among software professionals: factor analytic study
SIGMIS CPR '03 Proceedings of the 2003 SIGMIS conference on Computer personnel research: Freedom in Philadelphia--leveraging differences and diversity in the IT workforce
This course has a Bloom Rating of 3.9
ACE '04 Proceedings of the Sixth Australasian Conference on Computing Education - Volume 30
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It has been recognized that it is a challenging problem to deal with the situation where learners have diverse computing backgrounds and the learning content to be covered is also in the broad coverage. In the case, it’s required to devise a sophisticated diagnostic model for applying a proper teaching-learning method. We have drawn a scheme which can be applied to that case efficiently by using clustering algorithms based on web technology. In our approach, we focus on finding out methods for classifying both learners and learning content on the web. To make classification and manipulation of learning content ease, we reorganize learning content in order to have discrete form by introducing the concept of the knowledge unit which is extracted from each topic. Also, to make classification and diagnostic ease, we develop questions to measure them and analyze each question using item response theory (IRT) on the web. From the experiment of students sampled using our method, we show that learners with various backgrounds and the learning content with distribution on the broad range can be categorized effectively into the groups with homogeneous property. Also, we describe how to apply our proposed scheme to the introductory courses at postsecondary level.