Don't cheat yourself: Scenarios to clarify collusion confusion
Ensuring academic integrity in mathematical tasks presents a unique challenge, for university students and for their assessors, and one that hitherto has been under-examined. Drawing on her twenty years of experience in mathematics education, the recent academic integrity research literature, and on what students say about why misconduct occurs, the author examines this issue head-on. Don’t Cheat Yourself: Scenarios to clarify collusion confusion facilitates intentional consideration of the nature and purpose of assessment in mathematics, and of how some types of interactions between students undermine that purpose. Pertinent and realistic scenarios are provided as prompts for discussion, through which students in mathematical disciplines can come to a better understanding of what constitutes copying and collusion, identify strategies for finding support, be warned of the short and long term consequences of misconduct, and be set up to learn collaboratively and work legitimately.
History
School
- School of Computing, Engineering and Mathematical Sciences