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In this paper we review the literature relating to the psychological/educational study of programming. We identify general trends comparing novice and expert programmers, programming knowledge and strategies, program generation and comprehension, and object-oriented versus procedural programming. (We do not cover research relating specifically to other(More)
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(More)
Threshold Concepts deserve discussion and reflection in Computer Science Education; they provide a conceptual framework intended to re-empower tertiary educators. At this stage, the idea of Threshold Concepts raises plenty of questions, promises renewed learner and teacher engagement, and suggests a means of focusing on the key aspects of a discipline that(More)
We present the results of a survey which focuses on the backgrounds and expectations of a group of CS1 students in the first weeks of semester. When comparing their survey answers to their final grades on the course, we saw some surprising things: the group which indicated an intention to continue in computer science did no better than any other, and the(More)
We present the results of a survey that focuses on the backgrounds and expectations of a group of CS1 students in the first weeks of semester. When comparing their survey answers to their final grades on the course, we saw some surprising things: the group which indicated an intention to continue in computer science did no better than any other, and the(More)
Detecting association rules with low support but high confidence is a difficult data mining problem. To find such rules using approaches like the Apriori algorithm, minimum support must be set very low, which results in a large number of redundant rules. We are interested in sporadic rules; i.e. those that fall below a maximum support level but above the(More)
Discovering association rules efficiently is an important data mining problem. We define sporadic rules as those with low support but high confidence; for example, a rare association of two symptoms indicating a rare disease. To find such rules using the well-known Apriori algorithm, minimum support has to be set very low, producing a large number of(More)
Two issues of related interest are investigated in this paper. The first issue is associated with the statement that " Learning to program is a key objective in most introductory computing courses, yet many computing educators have voiced concern over whether their students are learning the necessary programming skills in those courses " (McCracken et al.(More)