The factors that contribute to success and failure in introductory programming courses continue to be a topic of lively debate, with recent conference panels and papers devoted to the subject (e.g. Rountree et al. 2004, Ventura et al., 2004, Gal-Ezer et al., 2003. Most work in this area has concentrated on the ability of single factors (e.g. gender, math background, etc.) to predict success, with the exception of Wilson et al. (2001), which used a general linear model to gauge the effect of combined factors. In Rountree et al. (2002) we presented the results of a survey of our introductory programming class that considered factors (such as student expectations of success, among other things) in isolation. In this paper, we reassess the data from that survey by using a decision tree classifier to identify combinations of factors that interact to predict success or failure more strongly than single, isolated factors.
The factors that contribute to success and failure in introductory programming courses continue to be a topic of lively debate, with recent conference panels and papers devoted to the subject (e.g. Rountree et al. 2004, Ventura et al., 2004, Gal-Ezer et al., 2003. Most work in this area has concentrated on the ability of single factors (e.g. gender, math background, etc.) to predict success, with the exception of Wilson et al. (2001), which used a general linear model to gauge the effect of combined factors. In Rountree et al. (2002) we presented the results of a survey of our introductory programming class that considered factors (such as student expectations of success, among other things) in isolation. In this paper, we reassess the data from that survey by using a decision tree classifier to identify combinations of factors that interact to predict success or failure more strongly than single, isolated factors.
In this article some thoughts on the use of digitised artifacts for teaching visual analysis in Classical art are presented. In order to employ digital images as effective teaching tools it is important to be able to describe your expectations for the media in relation to the learners’ task; to consider how to use the type of presentation (e.g. still photographs or virtual reality) to best advantage; and to identify critical insights students may either obtain (or have diminished) as a result of the media presented to them.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.