Detecting and preventing “multiple-account” cheating in massive open online courses

Abstract

We describe a cheating strategy enabled by the features of massive open online courses (MOOCs) and detectable by virtue of the sophisticated data systems that MOOCs provide. The strategy, Copying Answers using Multiple Existences Online (CAMEO), involves a user who gathers solutions to assessment questions using a "harvester" account and then submits correct answers using a separate "master" account. We use "clickstream" learner data to detect CAMEO use among 1.9 million course participants in 115 MOOCs from two universities. Using conservative thresholds, we estimate CAMEO prevalence at 1,237 certificates, accounting for 1.3% of the certificates in the 69 MOOCs with CAMEO users. Among earners of 20 or more certificates, 25% have used the CAMEO strategy. CAMEO users are more likely to be young, male, and international than other MOOC certificate earners. We identify preventive strategies that can decrease CAMEO rates and show evidence of their effectiveness in science courses.

Using Multiple Accounts for Harvesting Solutions in MOOCs

“…Thus our conclusion is that they started the course with the intention of earning a certificate dishonestly, but decided to quit for various reasons (for example, our many questions, or the many randomized questions that thwart CAMEO), maybe even moving their CAMEO efforts to somewhere else. This is also consistent with the finding of Northcut et al that CAMEO is more prevalent among users who have many certificates [6].…”

“…The phenomenon of using harvesting accounts was also reported by Northcutt, Ho, and Chuang, who examined multi-ple courses offered by MITx and HarvardX [6]. They coined the term CAMEO (Copying Answers using Multiple Existence Online) for this phenomenon, and we adopt this term.…”

“…The specific method that we have studied, termed CAMEO [6], is based on using multiple accounts to harvest solutions. Our results show that a significant fraction of the certificate earners in our course -about 10%, have used this method to some extent, and that 2.5% of them obtained the majority of their correct answers by using it.…”

A Multimedia Data Mining Framework for Monitoring E-Examination Environment

“…For instance, if only the image is considered, it implies that the two individuals are seen as one by the monitoring system. Also, the problem of integrity especially in an unsupervised environment that occur as a result of weak identity control measure [6].…”

Research on Evaluation System of SPOC Learning Interaction Effect

“…For example, based on the theory of learning target classification, the study of the influence of stent learning theory on the establishment of peer rating system (ARISE) on peer ratings confidence. [1] Secondly, from the monitoring and adjustment of the learning process, intervene in the individual learning process and then enhance the reliability of individual learning effect, the final evaluation of the formation of evaluation and summary evaluation and other multi-dimensional combination, such as GAMEO cheating test algorithm research; Third, from the SPOC learning effect evaluation system to provide constructive guidance to the evaluation system. [2] Above has made many achievements, on the qualitative point of view after the evaluation system with quantitative and other hybrid methods for its test is still a hot research.…”