A.I. Plagiarism in College Academics
Recently there has been a boom in student reported incidents involving suspected academic misconduct. The misconduct revolves around the accusation by the student’s professor that a report, essay, or academic writing assignment was completed in full or in part by Artificial Intelligence (AI). Many students have used tools such as Grammarly, Chegg, Quill Bot, or similar programs to perform several writing functions. Some programs are even recommended by the college faculty.
Many universities are using AI to grade homework but do not allow students to use AI to write their assignments. Fair?
These functions include suggestions for sentence composition or structural changes in conjunction with spelling and grammar corrections. One of the aspects that have students up in arms is the institutions making the accusations are using AI to grade papers and offer no personable recourse to make restitution with the student who otherwise might have had a stellar academic record up until they were flagged for misconduct. Here are some facts discovered when investigating the AI plagiarism issue and some aspects to consider when writing an academic paper.
· Textual Analysis: AI algorithms analyze the textual content of documents to identify similarities between different pieces of text. This includes identifying identical or slightly modified phrases, sentences, or paragraphs. Textual analysis algorithms are designed to detect patterns that may indicate plagiarism, even if the text has been paraphrased.
· Machine Learning Models: Machine learning models are trained on large datasets of known plagiarized and original content. These models can learn patterns and features indicative of plagiarism. When presented with a new document, the model can analyze its structure, language, and content to assess the likelihood of plagiarism.
· Natural Language Processing (NLP): NLP techniques are used to understand and interpret human language. Advanced NLP algorithms can analyze the semantics, syntax, and context of text to identify similarities and anomalies. This helps in detecting cases where AI-generated content mimics human writing style.
· Fingerprinting and Hashing: Some plagiarism detection systems use fingerprinting and hashing techniques to create unique identifiers for documents. These identifiers, or "fingerprints," are then compared to identify similarities between documents. Even if the text is slightly altered, the fingerprinting process can reveal similarities.
· Cross-Check with Online Sources: Plagiarism detection tools may cross-check submitted documents against a vast database of academic papers, articles, and other online sources. This helps identify instances where students have lifted content directly from existing publications.
The five mentioned methods are just a few ways the software that your professors use to grade your paper flag your assignment for the usage of AI.
It's worth noting that while AI-driven plagiarism detection is effective, it is not foolproof. Some advanced techniques, such as paraphrasing or using translation tools, can still pose challenges. To use the paragraph suggestions that Grammarly or Quill Bot suggest within your academic work, you will still need to do some hard work in making the content your own. That includes reworking the main ideas within the text that align with the topic.
