Programming pedagogy—a psychological overview
ACM SIGCSE Bulletin
Mooshak: a Web-based multi-site programming contest system
Software—Practice & Experience
Issues of pedagogy and design in e-learning systems
Proceedings of the 2004 ACM symposium on Applied computing
Controversy on how to teach CS 1: a discussion on the SIGCSE-members mailing list
Working group reports from ITiCSE on Innovation and technology in computer science education
Proceedings of the 37th SIGCSE technical symposium on Computer science education
Combating anonymousness in populous CS1 and CS2 courses
Proceedings of the 11th annual SIGCSE conference on Innovation and technology in computer science education
A new paradigm for programming competitions
Proceedings of the 39th SIGCSE technical symposium on Computer science education
Towards the validation of plagiarism detection tools by means of grammar evolution
IEEE Transactions on Evolutionary Computation
Automated Assessment of Programming Assignments
Proceedings of the 3rd Computer Science Education Research Conference on Computer Science Education Research
Student perception and usage of an automated programming assessment tool
Computers in Human Behavior
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Ada has proved to be one of the best languages to learn computer programming. Nevertheless, learning to program is difficult and when it is combined with lack of motivation by the students, dropout rates can reach up to 70%. In order to face up to this problem, we have developed a first-year course for computing majors on programming based on two key ideas: supplementing the final exam with a series of activities in a continuous evaluation context; and making those activities more appealing to the students. In particular, some of the activities are designed as on-line Ada programming competitions; they are carried out by using a web-based automatic evaluation system, the on-line judge. Human instructors remain essential to assess the quality of the code. To ensure the authorship of the programs, a source-code plagiarism detection environment is used. Experimental results show the effectiveness of the proposed approach. The dropout rate decreased from 61% in the autumn semester 2007 to 48% in the autumn semester 2008.