Live
- Bengaluru techie loses Rs 11.8 cr
- Former SC judge Ramasubramanian is new NHRC chief
- Roopasri strives to secure place in hearts of theatre lovers
- TG to showcase T-Culture in big way at Bharat Parv
- Bankers told to be part of Telangana Rising
- ISTS wins ‘Excellence in Women’s Engineering Education’ award
- Hyderabad loses its Shaan-e-Benegal
- Bangladesh requests India to extradite Sheikh Hasina
- Women, elderly register for AAP 's welfare schemes
- Cyber Security Mela -2024 held
Novel artificial intelligence can detect cheating in school assignments
"Our programme identifies discrepancies in writing styles by comparing recently submitted writing against a student's previously submitted work"
Scientists have created an artificial intelligence (AI) system that can accurately identify whether a student wrote their assignment on their own or got it penned by a ghostwriter.
Several studies have shown that cheating on assignments is widespread and becoming increasingly prevalent among high school students. Researchers at the University of Copenhagen in Denmark have been working on ways to detect cheating on assignments through writing analysis by way of artificial intelligence have been underway for a few years.
Based on analyses of 130,000 written Danish assignments, scientists can, with nearly 90 per cent accuracy, detect whether a student has written an assignment on their own or had it composed by a ghostwriter. The problem today is that if someone is hired to write an assignment, anti-plagiarism tools won't spot it, said Stephan Lorenzen, a PhD student at University of Copenhagen.
"Our programme identifies discrepancies in writing styles by comparing recently submitted writing against a student's previously submitted work," Lorenzen said. "Among other variables, the programme looks at word length, sentence structure and how words are used," said Lorenzen. The programme, Ghostwriter, is built around machine learning and neural networks -branches of artificial intelligence that are particularly useful for recognising patterns in images and texts.
The network is trained on large amounts of data to learn from representations of writing styles, which are then compared. When a student submits an assignment, the network compares it against their previous assignments. For each previous assignment, the network provides a percentage score for writing style similarity against the new assignment.
In the end, a weighted average of these scores is calculated using a calculation that also takes other factors, such as delivery time, into account. This final score is presented as a percentage and indicates the similarity between the new assignment and the student's writing style. Ghostwriter's technological foundation can be applied elsewhere in society. For example, the program could be used in police work to supplement forged document analysis, a task carried out by forensic document examiners and others.
