A study by a ITiCSE 2001 working group ("the McCracken Group") established that many students do not know how to program at the conclusion of their introductory courses. A popular explanation for this incapacity is that the students lack the ability to problem-solve. That is, they lack the ability to take a problem description, decompose it into sub-problems and implement them, then assemble the pieces into a complete solution. An alternative explanation is that many students have a fragile grasp of both basic programming principles and the ability to systematically carry out routine programming tasks, such as tracing (or "desk checking") through code. This ITiCSE 2004 working group studied the alternative explanation, by testing students from seven countries, in two ways. First, students were tested on their ability to predict the outcome of executing a short piece of code. Second, students were tested on their ability, when given the desired function of short piece of nearcomplete code, to select the correct completion of the code from a small set of possibilities. Many students were weak at these tasks, especially the latter task, suggesting that such students have a fragile grasp of skills that are a prerequisite for problemsolving.

A Contributing Student Pedagogy (CSP) is a pedagogy that encourages students to contribute to the learning of others and to value the contributions of others. CSP in formal education is anticipatory of learning processes found in industry and research, in which the roles and responsibilities of 'teacher' and 'student' are fluid. Preparing students for this shift is one motivation for use of CSP. Further, CSP approaches are linked to constructivist and community theories of learning, and provide opportunities to engage students more deeply in subject material. In this paper we advance the concept of CSP and relate it to the particular needs of computer science. We present a number of characteristics of this approach, and use case studies from the available literature to illustrate these characteristics in practice. We discuss enabling technologies, provide guidance to instructors who would like to incorporate this approach in their teaching, and suggest some future directions for the study and evaluation of this technique. We conclude with an extensive bibliography of related research and case studies which exhibit elements of CSP.

A study by a ITiCSE 2001 working group ("the McCracken Group") established that many students do not know how to program at the conclusion of their introductory courses. A popular explanation for this incapacity is that the students lack the ability to problem-solve. That is, they lack the ability to take a problem description, decompose it into sub-problems and implement them, then assemble the pieces into a complete solution. An alternative explanation is that many students have a fragile grasp of both basic programming principles and the ability to systematically carry out routine programming tasks, such as tracing (or "desk checking") through code. This ITiCSE 2004 working group studied the alternative explanation, by testing students from seven countries, in two ways. First, students were tested on their ability to predict the outcome of executing a short piece of code. Second, students were tested on their ability, when given the desired function of short piece of nearcomplete code, to select the correct completion of the code from a small set of possibilities. Many students were weak at these tasks, especially the latter task, suggesting that such students have a fragile grasp of skills that are a pre-requisite for problemsolving.124

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Abstract.A recent line of work in graph drawing studies Lombardi drawings, i.e., drawings with circular-arc edges and perfect angular resolution at vertices. Little is known about the effects of curved edges versus straight edges in typical graph reading tasks. In this paper we present the first user evaluation that empirically measures the readability of three different layout algorithms (traditional spring embedder and two recent near-Lombardi force-based algorithms) for three different tasks (shortest path, common neighbor, vertex degree). The results indicate that, while users prefer the Lombardi drawings, the performance data do not present such a positive picture.

PeerWise is a system in which students create multiple choice questions and answer those created by their peers. In this paper, we report on some quantitative results which suggest that students who use PeerWise actively perform better in final examinations than students who are not active. We note a significant correlation between performance in written (not just multiple choice) questions and PeerWise activity, suggesting that active use of the system may contribute to deep (and not just drill-and-practise) learning.

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