In education, a number of quick solutions has been developed, such as AI-detecting functionalities and GPT teach-outs. But as we learn to work around the increasing threat of hard-to-detect plagiarism, we also face new questions: how can we incorporate generative AI into the classroom? Can it be a teaching and learning tool? how can we teach students to interact with AI safely and usefully? how will the advance of generative AI shape our students’ professional futures, and how should teachers respond to that?
- ChatGPT “is a variant of the GPT (Generative Pre-training Transformer) language model, which was developed by OpenAI. GPT models are trained to generate human-like text by predicting the next word in a sequence based on the words that come before it. CHATGPT is specifically designed to be used in chatbots and conversational systems, and it is trained on a large dataset of human conversations to learn how to generate appropriate responses in a variety of contexts. (response from ChatGPT on 1/3/2023). This model is also known as GPT-3.5. Learn more:
- GPT-4: the newest version of OpenAI’s language model systems, officially launched in March 2023. It is a multimodal model, in that it accepts text and images as input. It can only generate text. It has demonstrated much stronger academic performance compared to the GPT-3.5 model. Learn more: OpenAI’s launch announcement on GPT-4.
- The ChatGPT-4 tool based on this model is only available through paid ChatGPT+ subscription at this point ($20/month.)
- Bing: Microsoft’s AI chatbot. After the release of GPT-4, Microsoft officially confirmed that Bing runs on OpenAI’s GPT-4 model.
- As of March 2023, OpenAI introduced support for plugins, including a Bing-based browsing plugin, which helps keep the outputs up-to-date and compensates for the training data behind the models only going up to 2021.
- Dall-E 2: ChatGPT’s visual creation sister, also run by OpenAI. Learn more
- Bard: Google’s AI chatbot. It is available through waitlist, although the wait is usually only a few days. It is still in beta-testing stage and performs with obvious lapses, but appears to evolve constantly.
Teaching and learning in the era of generative AI does not need to be all about damage control. Plagiarism and ethics concerns are real, but on the other hand, the advance of generative AI gives us a special opportunity to focus on the challenges of teaching and work out strong solutions.
Generative AI itself can be a learning tool– as anyone who gets into the tool and starts inputting queries and studying the output knows. Your synapses are firing as you write and read the rapidly generated text. It’s fun, and you’re likely wide awake, judging, speculating, disagreeing, agreeing, and doing all those things that happen when an engaged reader encounters text. These potentials can be used in the classroom.
Some specific suggestions:
- Assignment Strategies: Authentic assessment, formative assessment, assessment add-ons like problem-solving logs, exam wrappers, minute papers, “muddiest point” questions.
- Ask students to use diverse media. Replace an essay or short-answer writing assignment with one that requires students to submit an audio file, podcast, video, speech, drawing, diagram, or multimedia project.
- Create connections to real-world experience that AI will not have. Connect assignments to very recent events or new conversations in the field; to issues specific to the local community, or to discussions that took place in your own classroom. Alternatively, ask your students to find a connection between course concepts/topics and their personal experience or knowledge.
- Ask your students to reflect and plan as part of learning. Reflecting and envisioning a future are two areas where generative AI’s performance remains quite weak. Create space for reflection and sharing after each learning unit. Make reflection and planning a routine part of written assignments that is gradable. Students will not be able to create strong submissions for such tasks using generative AI (also, feel free to tell them just that!)
- For example: instead of the traditional essay, which is now easy to cheat through, assign a multimedia project accompanied by a brief self-reflective essay.
- Incorporate ChatGPT in your assignments. The more familiar your students become with it, including both its strengths and weaknesses, the less likely they will be to use it blindly for generating submissions.
- For example: to develop your students’ critical thinking skills, ask them to generate a ChatGPT response to a question of their own choosing, and then write an analysis of the strengths and weaknesses of the ChatGPT response.
- Teach your students to cite generative AI correctly.
- Use social annotation. For short reading responses, instead of using open-ended questions in Canvas, try social annotation tools that require students to engage with a text along with their classmates. Try Hypothes.is or Perusall, both of which are supported by the University.
- Extend Flipped Learning: Ask students to read, view, and digest material at home, and then apply, demonstrate, and perform in class, individually or in small groups.
For the full list of tips and ideas, go to this page.
Using generative AI to create or enhance the content of submissions when an assignment does not explicitly call or allow for it is academically dishonest, akin to paying a person to write your paper, take your test, or complete your assignment. Here are some tips on preventing and addressing academic dishonesty in the era of generative AI.
- Talk to your students. The first step to addressing the projected or actual academic integrity issues in the classroom is to talk to your students about your expectations for academic honesty.
- Remind your students of the University’s policies.
- Since the University’s policies on academic integrity currently do not include a separate clause on generative AI, add a clarifying statement to your syllabus (sample wording can be found here.)
- Give examples. Be specific and frank about your concerns.
- Raise questions to stimulate reflection: why is academic integrity valuable and important to uphold? What’s the point of pursuing a degree, of taking a class, if you don’t learn?
- See Academic Dishonesty and Student Cheating for additional guidance.
- Make plagiarizing difficult. Use some of the assignment design strategies suggested above and/or here to create assignments that encourage honest work.
- Run your assignment through ChatGPT. If you assign a task that can be solved by ChatGPT/ other generative AI, run it through ChatGPT first. Review the answer you receive, and tell your students about your experience (and that you’ve saved the output). ChatGPT does not produce the same answer each time the same question is posed, but the outputs may still be fairly similar.
- Be on the lookout for AI-produced texts.
- Play around with the tool and get an idea of what kind of prose is produced to the questions you typically ask. Not only will you gain insights on how to better write your assignments, but you may get a sense of the “voice” — or lack of voice — of the tools.
- Make use of AI-detecting tools.
- Watch out for these red flags.
- Always consider students’ writing history and the broader context of the assignment before making a decision. When plagiarism is suspected, talking to the student individually is the easiest first step to addressing the problem.
- Alby, C. (2022, December 17). ChatGPT: Understanding the new landscape and short-term solutions. Google Docs. Retrieved January 4, 2023, from https://docs.google.com/document/d/1ERCgdylG2LyOeL93aWrK6Jf97N_m1qaueN9W4kzO0Rk/edit#.
- Barbaro, M. (Host). (2022, December 16). Did artificial intelligence just get too smart? [Audio podcast episode]. In The Daily. The New York Times Company. Guest: Kevin Roose.
- Marchese, D. (2022, December 26). An A.I. pioneer on what we should really fear. The New York Times. Retrieved January 4, 2023, from https://www.nytimes.com/interactive/2022/12/26/magazine/yejin-choi-interview.html?smid=url-share. Interview with computer scientist Yejin Choi.
- Rudolph, J. et al (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching. Vol. 6, No. 1.
- Pavlik, J. V. (2023). Collaborating With ChatGPT: Considering the Implications of Generative Artificial Intelligence for Journalism and Media Education. Journalism & Mass Communication Educator, 0(0). https://doi.org/10.1177/10776958221149577
- Susnjak, T. (2022). ChatGPT: The End of Online Exam Integrity? Working Paper. http://arxiv.org/abs/2212.09292
- Schmitz, R. (Host). (2022, December 16). Has AI reached the point where a software program can do better work than you? [Audio podcast episode]. In: Morning Edition. National Public Radio. Guest: Ethan Mollick of the University of Pennsylvania. Mollick gives an overview and specific examples of how ChatGPT can be used. For example, he tried it out by asking the program to write a syllabus for him, along with a lecture and a final assignment with a grading rubric.
For additional resources, see AI Writing and Creating Bots (Montclair netID required).
Last Modified: Monday, September 25, 2023 3:24 pmVS
Teaching Resources by Montclair State University Office for Faculty Excellence is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Third-party content is not covered under the Creative Commons license and may be subject to additional intellectual property notices, information, or restrictions. You are solely responsible for obtaining permission to use third-party content or determining whether your use is fair use and for responding to any claims that may arise.