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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)
" This publication discusses the many issues surrounding association rules, including security, privacy, and incomplete and inaccurate data. This book also details association rules and their application in various domains, including mobile mining, social networking, and graph mining. " The growing complexity and volume of modern databases make it(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)
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)