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科学美国人60秒: 中学生作弊被神经网络捕获

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High School Cheaters Nabbed by Neural Network

中学生作弊被神经网络捕获

The English-language version of Wikipedia has almost six million articles. And if you're a cheating student, that's six million essays already written for you, footnotes and all. Except plagiarism isn't really an effective tactic—just plug the text into a search engine and game over. But what about having a ghostwriter at a paper mill compose your final essay?

维基百科英文版有近600万篇文章。如果你是一个作弊的学生,那你已经写了600万篇论文,还有脚注等等。除了剽窃并不是一个真正有效的策略——只要把文本插入搜索引擎,游戏就结束了。但是让造纸厂的代写员来写你的期末论文怎么样?

"Standard plagiarism software cannot detect this kind of cheating."Stephan Lorenzen, a data analyst at the University of Copenhagen. In Denmark, where he's based, ghostwriting is a growing problem at high schools. So Lorenzen and his colleagues created a program called Ghostwriter that can detect the cheats.

“标准剽窃软件无法检测到这种作弊行为。”哥本哈根大学(University of Copenhagen)的数据分析师Stephan Lorenzen说。在他所在的丹麦,代笔在高中越来越成问题。所以洛伦岑和他的同事们创建了一个名为Ghostwriter的程序,可以检测作弊行为。

At its core is a neural network trained and tested on 130,000 real essays from 10,000 Danish students. After reading through tens of thousands of essays labeled as being written by the same author or not, the machine taught itself to tune into the characteristics that might tip off cheating. For example, did a student's essays share the same styles of punctuation? The same spelling mistakes? Were the abbreviations the same?

其核心是一个神经网络,训练并测试了来自一万名丹麦学生的13万篇真实论文。在阅读了成千上万篇被标记为同一作者或非同一作者的文章后,这台机器学会了调整自己,以适应可能引发作弊的特征。例如,学生的作文是否有相同的标点符号?同样的拼写错误?缩写是一样的吗?

By scrutinizing inconsistencies like those, Ghostwriter was able to pinpoint a cheated essay nearly 90 percent of the time. The team presented the results at the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.

通过仔细研究这些前后矛盾之处,代笔写手几乎90%的时间都能找出一篇被骗的文章。研究小组在欧洲人工神经网络、计算智能和机器学习研讨会上展示了研究结果。

There's one more aspect here that could help students. Your high school essays presumably get better over time as you learn to write—and the machine can detect that. "The final idea is to detect students who are at risk because their development in writing style isn't as you'd expect."Teachers could thus give extra help to kids who really need it, while sniffing out the cheaters too.

这里还有一个方面可以帮助学生。随着时间的推移,当你学会写作时,你的高中论文想必会写得更好,而机器可以检测到这一点。“最后一个想法是检测哪些学生面临写作风险,因为他们在写作风格上的发展并不像你想象的那样。”因此,老师可以给那些真正需要帮助的孩子提供额外的帮助,同时也能发现作弊者。

High School Cheaters Nabbed by Neural Network

The English-language version of Wikipedia has almost six million articles. And if you're a cheating student, that's six million essays already written for you, footnotes and all. Except plagiarism isn't really an effective tactic—just plug the text into a search engine and game over.But what about having a ghostwriter at a paper mill compose your final essay?

"Standard plagiarism software cannot detect this kind of cheating."Stephan Lorenzen, a data analyst at the University of Copenhagen. In Denmark, where he's based, ghostwriting is a growing problem at high schools. So Lorenzen and his colleagues created a program called Ghostwriter that can detect the cheats.

At its core is a neural network trained and tested on 130,000 real essays from 10,000 Danish students. After reading through tens of thousands of essays labeled as being written by the same author or not, the machine taught itself to tune into the characteristics that might tip off cheating. For example, did a student's essays share the same styles of punctuation? The same spelling mistakes? Were the abbreviations the same?

By scrutinizing inconsistencies like those, Ghostwriter was able to pinpoint a cheated essay nearly 90 percent of the time. The team presented the results at the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. [Magnus Stavngaard et al., Detecting Ghostwriters in High Schools]

There's one more aspect here that could help students. Your high school essays presumably get better over time as you learn to write—and the machine can detect that. "The final idea is to detect students who are at risk because their development in writing style isn't as you'd expect."Teachers could thus give extra help to kids who really need it, while sniffing out the cheaters too.


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