Abstract

Cheating in introductory programming classes (CS1) is a well-known problem. Many instructors seek methods to prevent such cheating. Some methods are time-consuming or don’t scale to large classes. We experimented with several low-effort commonly-suggested methods to reduce cheating: (1) Discussing academic integrity for 20-30 minutes, several weeks into the term, (2) Requiring an integrity quiz with explicit do’s and don’ts, (3) Allowing students to withdraw program submissions, (4) Reminding students mid-term about integrity and consequences of getting caught, (5) Showing tools in class that an instructor has available (including a similarity checker, statistics on time spent, and access to a student’s full coding history), (6) Normalizing help and pointing students to help resources. Because counting students actually caught cheating is not objective (being influenced by how much effort is spent in detecting and investigating, and how an instructor subjectively decides cheating has occurred), we developed two automated coding-behavior metrics that may suggest how much cheating is happening. We compared those metrics for terms before and after the intervention.  The results show substantial student behavior improvements when applying those low-effort methods. In our Fall 2021 comparison, time spent programming increased from 6 min 56 sec, to 11 min 6 sec, for a 60% increase. And, the percent of students with suspiciously similar programs dropped from 33% to 18%, for a 45% decrease. 

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