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Last week at the University of Kentucky (UK), two students' cheating plan proved to have a high margin of error.
Henry Lynch, a 21-year-old UK junior, climbed through his school's ceiling ducts after midnight and dropped into his statistics professors' office. He then unlocked the door for his friend, Troy Kiphuth, to join him in looking for their loot: the final exam.
The students' error? Lynch and Kiputh failed to take into account one important variable: the odds that their professor was still in range.
Around 1:30a.m., John Cain returned to his office after picking up a late-night meal to find the door to his office blocked. When he threatened to call the police, the two students swung the door open and ran down the hall.
Later on, the police questioned Lynch and Kiphuth. Lynch confessed not only that he had attempted to steal the final exam, but that this wasn't an isolated certain event—he had attempted to steal an exam two other times but had been unable to find it.
Lynch claimed there was never a high probability [of] distribution of the exam among his classmates—he only intended to steal it for himself.
What does this mean for the students? Lynch and Kiphuth are being cited with third-degree burglary and UK's Office of Student Conduct will lead a formal investigation to survey the case and determine the best treatment for the students' uncontrolled [cheating] experiment.
Lynch and Kiphuth's break-in is just one sample of many failed attempts at cheating. But there's a causal relation between cheating and getting caught—not even the stealthiest plots are resistant to failure (Blackford, Lexington Herald-Leader, 5/3; .Jaschik, Inside Higher Ed, 5/4; Mele, New York Times, 5/4).
Why do students still risk cheating, even when they know it's risky?
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