As stated in Macalester’s Academic Integrity policy, students are expected to maintain the highest standards of honesty in their college work. Violations of academic integrity are serious offenses. Students found guilty of any form of academic dishonesty — including, for instance, forgery, cheating, and plagiarism — are subject to disciplinary action. The Academic Integrity statement has recently been revised to include the following clauses regarding the usage of AI generative tools:
Cheating is the dishonest or unauthorized use of materials for academic work. Examples of cheating include:
*Having another person, or generative AI tools, do your work for a course (including unauthorized collaboration).
Plagiarism is the unacknowledged use of another person’s or generative AI tools’ work (words, ideas, data, etc.) in a graded or published piece or in a speech.
Always check with your instructor for their stance on the use of generative AI tools.
Have you ever found yourself wondering what exactly counts as cheating and what's fair game when it comes to AI? The three videos created by StudyForge can help you navigate the exciting yet complex world of AI in academics. Watch them now and empower yourself with the knowledge to use AI software ethically and effectively. Let us know if you have any questions or feedback by using the 'Feedback' form on this guide.
"AI-Cademic Integrity - Part 1.” YouTube, 4 Dec. 2023, youtu.be/DVqrJYWet6k?si=dANVabGKE1sFte95.
"AI-Cademic Integrity - Part 2.” YouTube, 4 Dec. 2023,youtu.be/KxLW3PpRrcQ?si=OLGme3Rv4cyezAEL.
"AI-Cademic Integrity - Part 3.” YouTube, 4 Dec. 2023,youtu.be/ec1-haYC3Ko?si=h-XmW0PNMagEVZko
Generative AI natural language processing tools, language models, or chatbots like ChatGPT have been shown to hallucinate, or provide completely unsubstantiated information. Text generated by AI can also seem very confident, so it can be very difficult to ascertain what information generated by AI is trustworthy and what information is not. (To learn more, read about six fake cases created by ChatGPT in the Steven A. Schwartz and Peter LoDuca court case)
Using prompts is the key to use AI tools effectively. The following framework assist you with optimizing the outcomes. Adapted from Jeffrey Zheng on LinkedIn, May 2023
If you like to watch a short video on how to create effective prompts, check this 6 min video out.
The slide is taken form the "ChatGPT Unleashed: What to Expect This Fall and How to Prepare" webinar offered by Alchemy on June 22, 2023 slides.
The MLA’s method for citing sources uses a template of core elements—standardized criteria that writers can use to evaluate sources and create works-cited-list entries based on that evaluation. That new technologies like ChatGPT emerge is a key reason why the MLA has adopted this approach to citation—to give writers flexibility to apply the style when they encounter new types of sources.
You should
cite a generative AI tool whenever you paraphrase, quote, or incorporate into your own work any content (whether text, image, data, or other) that was created by it
acknowledge all functional uses of the tool (like editing your prose or translating words) in a note, your text, or another suitable location
take care to vet the secondary sources it cites
Core Elements
Each entry in the list of works cited is composed of facts common to most works—the MLA core elements. They are assembled in a specific order.
Containers
The concept of containers is crucial to MLA style. When the source being documented forms part of a larger whole, the larger whole can be thought of as a container that holds the source. For example, a short story may be contained in an anthology. The short story is the source, and the anthology is the container.
Learn how to use the MLA practice template to create entries in the list of works cited.
Example:
“Describe the symbolism of the green light in the book The Great Gatsby by F. Scott Fitzgerald” prompt. ChatGPT, 13 Feb. version, OpenAI, 8 Mar. 2023, chat.openai.com/chat.
See examples of Citing Creative Visual Works, Quoting Creative Textual Works, and Citing Secondary Sources Used by an AI Tool on the MLA Guide.
Colucci, A., Weaver, K. D., Voichita, S., & Dai, J. (2023). APA citation style : References Chat GPT. https://lib.uwaterloo.ca/
Colucci, A., Ali, A., Voichita, S., & Dai, J., Weaver, K. (2023). Chicago 17th Manual of Style: References Artificial Intelligence and Chatbots. https://lib.
AI can assist with personalized learning experiences to cater to individual college students' unique needs, learning styles, and preferences. This approach can help students grasp concepts more effectively, stay engaged, and progress at their own pace, fostering a more efficient and satisfying learning journey.
Always feel free to check with professors, preceptors, peers, librarians, and other professionals when you have questions. Asking questions leads to new learning for everyone--building our Mac community of learners.
ChatGPT can assist the research process in the initial stages such as idea generation, research question suggestions, and offering some contextual information. With its ability to connect seemingly unrelated concepts and provide perspectives, it can becomes a useful tool for researchers.
Be mindful of AI's limitations. Check for information accuracy and bias, as well as reliability of the resources. AI is known to "hallucinate" and make up resources that do not exist. Read about six fake cases created by ChatGPT in the Steven A. Schwartz and Peter LoDuca court case. Ask librarians and other professionals to help think through authority, bias, and accuracy of information.
AI-powered language learning apps provide interactive courses personalized to each student's proficiency. Through AI algorithms, these apps assess language skills, adapt content, and offer real-time feedback. Moreover, AI-driven translation tools enable seamless cross-cultural communication and access to international resources by overcoming language barriers.
Make sure to ask your professor about their use of AI policy in each course. Remember that sets of data used to train AI in non-English languages may be much smaller and more prone to bias and/or misinformation.