Detecting and prosecuting contract cheating with evidence \u2013 a \u201cDoping Test\u201d approach

Pauli Alin

doi:10.1007/s40979-020-00056-4

Abstract

Contract cheating – outsourcing student assignments for a fee – presents a growing threat to the integrity of higher education. As contract cheating is based on students purchasing assignments that are original (albeit not created by the student), traditional plagiarism detection tools remain insufficient to detect contract cheating. Part of the problem is that proving contract cheating is difficult. As a result, instructors may find it hard to prosecute students (i.e. put them through university academic dishonesty proceedings). To help address the problem, this conceptual paper builds upon extant scholarship on contract cheating and argues that a novel evidence-based approach is needed. Such an approach should allow instructors to detect and prosecute cases of contract cheating effectively and efficiently. The paper then presents an outline of such an approach and calls it the “Doping Test” approach as it mimics some aspects of doping testing in professional sport.

Highlights

IntroductionOnline-based learning management systems (like Blackboard or Canvas) are increasingly popular in higher education – some studies have reported that 99% of universities use them (Dahlstrom et al 2014)
Online-based learning management systems are increasingly popular in higher education – some studies have reported that 99% of universities use them (Dahlstrom et al 2014)
Following the Doping Test model with appropriate document templates to record actions at each stage, the instructor could be freed from the constant thinking about the possibility of contract cheating and how to best approach each potential case, possibly in more or less ad hoc fashion each time

Summary

Introduction

Online-based learning management systems (like Blackboard or Canvas) are increasingly popular in higher education – some studies have reported that 99% of universities use them (Dahlstrom et al 2014). While the learning management systems help faculty and instructors better manage the courses they teach 2018), they allow 100% online submission of student work. As a result, these systems make it difficult to reliably identify academic dishonesty: when student work is submitted only online, the instructor may not be able to verify who really did it (Dawson and Sutherland-Smith 2018; Malesky et al 2016). The purpose of this paper is to provide a conceptual model for identifying academic dishonesty. The model is intended to help instructors and advance academic literature on academic dishonesty. Building on extant scholarship on contract cheating, this conceptual paper suggests a novel evidence-based approach of identifying and prosecuting cheating company using students in face-to-face courses.

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