Collaboration, collusion and plagiarism in computer science

1. Collaboration, collusion and plagiarism in computer science Bob Fraser

2. Why Computer Science? • “The computer is a relentlessly unforgiving arbiter of correctness” (Roberts, 2002) • Computer science asks students to find the correct solution or method • Stanford study: 37% of cheating cases are CS, 7% of students are CS (Roberts, 2002)

3. Outline • Collaboration • Collusion • Plagiarism • Mitigating dishonesty

4. Collaboration • Generally to be encouraged • Discussing course material with peers is a primary aspect of active learning • Line must be drawn so that collaboration doesn’t become excessive and negatively affect learning

5. Collusion • Excessive collaboration • Definition is set by the course instructor • From Waterloo’s OAI: • “Clearly indicate if group collaboration is acceptable (and the level of collaboration permitted) or if students must do all work independently.”

6. Plagiarism • Literary theft • Encompasses copying whether the original author is aware of it or not • In computer science, the best solution is often unique, exacerbating the problem • Many honest students err to heavily on the side of caution to avoid plagiarism

7. Where is the line drawn? • Student A doesn't know how to start the assignment and so he asks student B who helps him by showing him his own work. Student A writes up the assignment in his own words but there are some similarities with student B's work. (Barrett & Cox, 2005)

8. Mitigating • Make the rules clear – the onus is on you • Methods: • Appeal to their maturity • Detect & punish cheaters • Emphasize ILOs • Improve tutorials • Regular quizzes

9. Appealing to Maturity “cheating isn't bad because it only hurts you at test time” Palazzo et al. (2010)

10. Detection & Discipline • Students are less likely to cheat if they believe that they may be caught and punished (although zero tolerance is too far) • Many professors have looked the other way for various reasons • Waterloo encourages the use of Turnitin

11. Intended Learning Outcomes • Emphasize the value of the assignment and how it fits in the course • Students who see the purpose and value of their work are less likely to cheat • It may be worthwhile to explicitly state the ILOs on the assignment

12. Conclusions • Students should be encouraged to collaborate • Students should be given a precise definition of what is acceptable behaviour • Courses can be improved to reduce cheating and improve learning

13. Pointers • Bob Fraser->publications • http://www.cs.uwaterloo.ca/~r3fraser/papers/cut902_fraser.pdf • Key References • Barrett, R., & Cox, A. L. (2005). At least they are learning something: the hazy line between collaboration and collusion. Assessment & Evaluation in Higher Education, 30 (2), 107-122. • Palazzo, D. J., Lee, Y.-J., Warnakulasooriya, R., & Pritchard, D. E. (2010). Patterns, correlates, and reduction of homework copying. Phys. Rev. ST Phys. Educ. Res., 6 (1), 010104-1-010104-11. • Roberts, E. (2002). Strategies for promoting academic integrity in CS courses. Frontiers in Education Annual, 3 , F3G14-19. • University of Waterloo Office of Academic Integrity • http://uwaterloo.ca/academicintegrity/index.html