This tutorial and quiz are best viewed on a full-size computer monitor or tablet; it is not recommended to complete on a phone.
Like all colleges and universities, Raritan Valley Community College has a Student Academic Integrity Policy that outlines expectations for students to act with integrity and honesty in completing coursework.
Open the linked PDF document titled "Student Academic Integrity Policy" and read the entire policy. The document will open in a new tab/window. When you finish reading the policy, close that tab/window and return to this page.
The following activities tutorial are designed to get you thinking about some of the temptations to cheat and to consider situations where acting with academic integrity might be difficult or unclear. We'll start by learning about some research behind people's motivations for and likelihood of cheating. In this TedTalk, Dan Ariely describes research experiments he has conducted to determine why people cheat or steal. The video will begin at 4:35 and you should watch until it stops at 8:22.
The following scenarios describe situations where students are put in a position to exercise their academic integrity. Read through the scenario and think about whether what is described demonstrates academic integrity. After each scenario, answer the related quiz questions.
In Biology 101, there are lab groups of four students. Tiesha, Antonio, Sally, and Jim are in a lab group together. They sit at a lab table together in class, work on all labs together, and write group lab reports that get handed in and graded, and everyone in the group gets the same grade. Over spring break, the professor gives a take-home exam with the following instructions:
This mid-term exam will show me what you have learned so far from our lectures and labs. It is a take-home, open-textbook exam. You may use any notes you’ve taken in class, the assigned textbook, and all the materials I have provided to you online in our course page. The exam is due at our first class session after break, or you can upload it to the class page any time before that class meeting. If you submit your exam before 11:59PM Wednesday of spring break, I will provide feedback and return it to you so you can make improvements before it is due.
Tiesha and Jim both submit their exam before Wednesday and get it back with the instructor’s suggestions. They meet in the library to compare his notes. While there, Antonio shows up to work on his exam, which he hasn’t started. He sits down with his lab partners and the three of them discuss the best answers to the exam questions. They each write their own answers and then read them to each other to make sure they sound good.
Consider: Is this ok? Why or why not?
It’s Leslie’s senior year and she is taking Ethics and Morality as an elective. The final assignment is a 10-page research paper on any topic related to what’s been taught in the class. A few semesters ago, Leslie took Introduction to Philosophy and wrote a 9-page paper about the connection between moral behavior and a person’s happiness. She titled that paper, “The Morality of Happiness.” All of the major points in that paper have also been discussed in the class Leslie is now taking. After re-reading the paper, Leslie adds another paragraph to the conclusion to make it 10 pages long. Now that she is a more sophisticated writer, Leslie decides to title this paper, “Don’t Worry, Be Moral: How Happiness and Moral Behavior are Connected.”
Consider: Is this ok? Why or why not?
Watch the following video that describes how generative AI works (video begins at 2:07 and will stop at 4:57).
While generative AI tools, like ChatGPT, can be valuable for certain tasks, there are several concerns you should be aware of. A Student Guide to Navigating College in the Artificial Intelligence Era identifies the following generative AI concerns:
Hallucination | Generative AI can produce inaccurate, misleading or completely false information using a confident voice. |
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Bias | Generative AI can produce output with subtle or blatant biases because of programming and the source training data. |
Mediocre quality | Generative AI struggles iwth context, deeper meanings or emotional tone. Depending on its training data, the output can seem bland or uninspired. Newer AI models are often far superior to older models. |
Intellectual property | Generative AI can be trained on copyrighted material and intellectual property used without consent. |
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No accountability | Generative AI sources are often kept opaque. Private information you input may be shared with others without your knowledge or permission. |
Lack of values | Generative AI programming often doesn't fully consider the consequences or damages that may result from its use. Guardrails for AI stystems are still in development. |
Not current | Some Generative AIs do not capture up-to-date new and information, so their output can be outdated. |
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Resource hungry | AI models are very expensive to develop and th emassive power consumption to train them and respond to the queries can be bad for the environment |
Security risks | AI tools developed by individuals or small operations may not have adequate safeguards to protect privacy and block malware. |
Content above originally appeared in A student guide to navigating college in the artificial intelligence era (2024) by Elon University's Imagining the Digital Future Center, licensed CC-BY-NC 4.0
The Student Academic Integrity Policy you read earlier specifically mentions the use of artificial intelligence as a possible violation of the policy:
Cheating - the use or attempted use of any artificial intelligence . . . in any academic exercise including assignments, quizzes, and tests without the instructor’s permission
Some instructors may include guidance on the use of generative AI in their syllabi. You should always discuss the appropriate use of generative AI with your instructor before using it for coursework.