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Using AI ethically in writing assignments

The use of generative artificial intelligence in writing isn’t an either/or proposition. Rather, think of a continuum in which AI can be used at nearly any point to inspire, ideate, structure, and format writing. It can also help with research, feedback, summarization, and creation. You may also choose not to use any AI tools. This handout is intended to help you decide.

A starting point

Many instructors fear that students will use chatbots to complete assignments, bypassing the thinking and intellectual struggle involved in shaping and refining ideas and arguments. That’s a valid concern, and it offers a starting point for discussion:

Turning in unedited AI-generated work as one’s own creation is academic misconduct .

Most instructors agree on that point.  After that, the view of AI becomes murkier. AI is already ubiquitous, and its integrations and abilities will only grow in the coming years. Students in grade school and high school are also using generative AI, and those students will arrive at college with expectations to do the same. So how do we respond?

Writing as process and product

We often think of writing as a product that demonstrates students’ understanding and abilities. It can serve that role, especially in upper-level classes. In most classes, though, we don’t expect perfection. Rather, we want students to learn the process of writing. Even as students gain experience and our expectations for writing quality rise, we don’t expect them to work in a vacuum. They receive feedback from instructors, classmates, friends, and others. They get help from the writing center. They work with librarians. They integrate the style and thinking of sources they draw on. That’s important because thinking about writing as a process involving many types of collaboration helps us consider how generative AI might fit in.   

Generative AI as a writing assistant

We think students can learn to use generative AI effectively and ethically. Again, rather than thinking of writing as an isolated activity, think of it as a process that engages sources, ideas, tools, data, and other people in various ways. Generative AI is simply another point of engagement in that process. Here’s what that might look like at various points:

Early in the process

• Generating ideas . Most students struggle to identify appropriate topics for their writing. Generative AI can offer ideas and provide feedback on students’ ideas.  
• Narrowing the scope of a topic . Most ideas start off too broad, and students often need help in narrowing the scope of writing projects. Instructors and peers already do that. Generative AI becomes just another voice in that process.
• Finding initial sources . Bing and Bard can help students find sources early in the writing process. Specialty tools like Semantic Scholar, Elicit, Prophy, and Dimensions can provide more focused searches, depending on the topic.
• Finding connections among ideas . Research Rabbit, Aria (a plug-in for Zotero) and similar tools can create concept maps of literature, showing how ideas and research are connected. Elicit identifies patterns across papers and points to related research. ChatGPT Pro can also find patterns in written work. When used with a plugin, it can also create word clouds and other visualizations.
• Gathering and formatting references . Software like EndNote and Zotero allow students to store and organize sources. They also save time by formatting sources in whatever style the writer needs.
• Summarizing others’ work . ChatGPT, Bing and specialty AI tools like Elicit do a good job of summarizing research papers and webpages, helping students decide whether a source is worth additional time.
• Interrogating research papers or websites . This is a new approach AI has made possible. An AI tool analyzes a paper (often a PDF) or a website. Then researchers can then ask questions about the content, ideas, approach, or other aspects of a work. Some tools can also provide additional sources related to a paper.
• Analyzing data . Many of the same tools that can summarize digital writing can also create narratives from data, offering new ways of bringing data into written work.
• Finding hidden patterns . Students can have an AI tool analyze their notes or ideas for research, asking it to identify patterns, connections, or structure they might not have seen on their own.
• Outlining . ChatGPT, Bing and other tools do an excellent job of outlining potential articles or papers. That can help students organize their thoughts throughout the research and writing process. Each area of an outline provides another entry point for diving deeper into ideas and potential writing topics.
• Creating an introduction . Many writers struggle with opening sentences or paragraphs. Generative AI can provide a draft of any part of a paper, giving students a boost as they bring their ideas together.

Deeper into the process

• Thinking critically . Creating good prompts for generative AI involves considerable critical thinking. This isn’t a process of asking a single question and receiving perfectly written work. It involves trial and error, clarification and repeated follow-ups. Even after that, students will need to edit, add sources, and check the work for AI-generated fabrication or errors.
• Creating titles or section headers for papers . This is an important but often overlooked part of the writing process, and the headings that generative AI produces can help students spot potential problems in focus.
• Helping with transitions and endings . These are areas where students often struggle or get stuck, just as they do with openings.
• Getting feedback on details . Students might ask an AI tool to provide advice on improving the structure, flow, grammar, and other elements of a paper.
• Getting feedback on a draft . Instructors already provide feedback on drafts of assignments and often have students work with peers to do the same. Students may also seek the help of the writing center or friends. Generative AI can also provide feedback, helping students think through large and small elements of a paper. We don’t see that as a substitute for any other part of the writing process. Rather, it is an addition.

Generative AI has many weaknesses. It is programmed to generate answers whether it has appropriate answers or not. Students can’t blame AI for errors, and they are still accountable for everything they turn in. Instructors need to help them understand both the strengths and the weaknesses of using generative AI, including the importance of checking all details.

A range of AI use

Better understanding of the AI continuum provides important context, but it doesn’t address a question most instructors are asking: How much is too much ? There’s no easy answer to that. Different disciplines may approach the use of generative AI in very different ways. Similarly, instructors may set different boundaries for different types of assignments or levels of students. Here are some ways to think through an approach:

• Discuss ethics . What are the ethical foundations of your field? What principles should guide students? Do students know and understand those principles? What happens to professionals who violate those principles?
• Be honest . Most professions, including academia, are trying to work through the very issues instructors are. We are all experimenting and trying to define boundaries even as the tools and circumstances change. Students need to understand those challenges. We should also bring students into conversations about appropriate use of generative AI. Many of them have more experience with AI than instructors do, and adding their voices to discussions will make it more likely that students will follow whatever guidelines we set.  
• Set boundaries . You may ask students to avoid, for instance, AI for creating particular assignments or for generating complete drafts of assignments. (Again, this may vary by discipline.) Just make sure students understand why you want them to avoid AI use and how forgoing AI assistance will help them develop skills they need to succeed in future classes and in the professional world.
• Review your assignments . If AI can easily complete them, students may not see the value or purpose. How can you make assignments more authentic, focusing on real-world problems and issues students are likely to see in the workplace?
• Scaffold assignments . Having students create assignments in smaller increments reduces pressure and leads to better overall work.
• Include reflection . Have students think of AI as a method and have them reflect on their use of AI. This might be a paragraph or two at the end of a written assignment in which they explain what AI tools they have used, how they have used those tools, and what AI ultimately contributed to their written work. Also have them reflect on the quality of the material AI provided and on what they learned from using the AI tools. This type of reflection helps students develop metacognitive skills (thinking about their own thinking). It also provides important information to instructors about how students are approaching assignments and what additional revisions they might need to make.
• Engage with the Writing Center, KU Libraries , and other campus services about AI, information literacy, and the writing process. Talk with colleagues and watch for advice from disciplinary societies. This isn’t something you have to approach alone.

Generative AI is evolving rapidly. Large numbers of tools have incorporated it, and new tools are proliferating. Step back and consider how AI has already become part of academic life:  

• AI-augmented tools like spell-check and auto-correct brought grumbles, but there was no panic.
• Grammar checkers followed, offering advice on word choice, sentence construction, and other aspects of writing. Again, few people complained.
• Citation software has evolved along with word-processing programs, easing the collection, organization, and formatting of sources.
• Search engines used AI long before generative AI burst into the public consciousness.

As novel as generative AI may seem, it offers nothing new in the way of cheating. Students could already buy papers on the internet, copy and paste from an online site, have someone else create a paper for them, or tweak a paper from the files of a fraternity or a sorority. So AI isn’t the problem. AI has simply forced instructors to deal with long-known issues in academic structure, grading, distrust, and purpose. That is beyond the scope of this handout, other than some final questions for thought:

Why are we so suspicious of student intentions? And how can we create an academic climate that values learning and honesty?

(Updated July 2024)

Other AI-Related Materials

• Helping Students Understand the Biases in Generative AI
• Maintaining Academic Integrity in the AI Era
• AI as a Tutor on Research Projects

Additional resources

Research on ai and writing.

Ai.llude: Encouraging Rewriting AI-Generated Text to Support Creative Expression , by David Zhou and Sarah Sterman. Proceedings of the 2024 ACM Conference on Creativity and Cognition (28 May 2024).

AI and Its Consequences for the Written Word , by Thomas Helstrom. Frontiers in Artificial Intelligence 6 (4 January 2024).

AI and Writing Classrooms: A Study of Purposeful Use and Student Responses to the Technology , by Laura Dumin. Teaching and Generative AI , Beth Buyserie and Travis N. Thurston, eds., chapter 8. Utah State University, 2024.

AI vs. Human-Authored Texts: A Multidimensional Comparison , by Tony Berber Sardinha. Applied Corpus Linguistics 4 (April 2024).

ChatGPT: A Powerful Technology Tool for Writing Instruction , by Sarah W. Beck and Sarah R. Levine. Phi Delta Kappan 105 (28 August 2023).

ChatGPT Is Bullshit , by Michael Townsen Hicks, James Humphries, and Joe Slater.  Ethics and Information Technology  26 (2024).

Embracing AI in English Composition: Insights and Innovations in Hybrid Pedagogical Practices , by James Hutson, Daniel Plate, and Kadence Berry.  International Journal of Changes in Education  1 (2024):19-31.

Exploring an AI-based Writing Assistant's Impact on English Language Learners , by John Maurice Gayed, May Kristine Jonson Carlon, Angelu Mari Oriola, and Jeffrey S. Cross. Computers and Education: Artificial Intelligence  3 (2022).

Improving Writing Feedback for Struggling Writers: Generative AI to the Rescue? , by Anya S. Evmenova, Kelley Regan, Reagan Mergen, and Roba Hrisseh.  TechTrends  (14 May 2024).

The Use of ChatGPT in Creative Writing Assistance , by Svitlana Fiialka, Zoia Kornieva, and Tamara Honcharuk.  XLinguae: European Scientific Language Journal 17 (January 2024) 

Generative AI in Academic Writing

What this handout is about.

You’ve likely heard of AI tools such as ChatGPT, Microsoft Copilot, Perplexity, or others by now. These tools fall under a broad, encompassing term called generative AI that describes technology that can create new text, images, sounds, video, etc. based on information and examples drawn from the internet. Some AI tools are free or offer free tiers, while others require a subscription and payment. In this handout, we will focus on potential uses and pitfalls of generative AI tools that generate text.

Before we begin: Stay tuned to your instructor

Instructors’ opinions on the use of AI tools may vary dramatically from one class to the next, so don’t assume that all of your instructors will think alike on this topic. Consult each syllabus for guidance or requirements related to the use of AI tools. If you have questions about if/how/when it may be appropriate to use generative AI in your coursework, be sure to seek input from your instructor before you turn something in for a grade. You are always 100% responsible for whatever writing you chose to turn in to an instructor, so it pays to inquire early.

Note that when your instructors authorize the use of generative AI tools, they will likely assume that these tools may help you think and write—not think or write for you. Keep that principle in mind when you are drafting and revising your assignments. You can maintain your academic integrity and employ the tools with the same high ethical standards and source use practices that you use in any piece of academic writing.

What is generative AI, and how does it work?

Generative AI is an artificial intelligence tool that allows users to ask it questions or make requests and receive quick written responses. It uses Large Language Models (LLMs) to analyze vast amounts of textual data to determine patterns in words and phrases. Detecting patterns allows LLMs to predict what words may follow other words and to transform the content of its corpus (the textual data) into new sentences that respond to the questions or requests. Using complex neural network models, LLMs generate writing that mimics human intelligence and varied writing styles.

The textual data used to train the LLM has been scraped from the internet, though it is unclear exactly which sources have been included in the corpus for each AI tool. As you can imagine, the internet has a vast array of content of variable quality and utility, and generative AI does not distinguish between accurate/inaccurate or biased/unbiased information. It can also recombine accurate source information in ways that generate inaccurate statements, so it’s important to be discerning when you use these tools and to carefully digest what’s generated for you. That said, the AI tools may spark ideas, save you time, offer models, and help you improve your writing skills. Just plan to bring your critical thinking skills to bear as you begin to experiment with and explore AI tools.

As you explore the world of generative AI tools, note that there are both free and paid versions. Some require you to create an account, while others don’t. Whatever tools you experiment with, take the time to read the terms before you proceed, especially the terms about how they will use your personal data and prompt history.

In order to generate responses from AI tools, you start by asking a question or making a request, called a “prompt.” Prompting is akin to putting words into a browser’s search bar, but you can make much more sophisticated requests from AI tools with a little practice. Just as you learned to use Google or other search engines by using keywords or strings, you will need to experiment with how you can extract responses from generative AI tools. You can experiment with brief prompts and with prompts that include as much information as possible, like information about the goal, the context, and the constraints.

You could experiment with some fun requests like “Create an itinerary for a trip to a North Carolina beach.” You may then refine your prompt to “Create an itinerary for a relaxing weekend at Topsail Beach and include restaurant recommendations” or “Create an itinerary for a summer weekend at Topsail Beach for teenagers who hate water sports.” You can experiment with style by refining the prompt to “Rephrase the itinerary in the style of a sailor shanty.” Look carefully at the results for each version of the prompt to see how your changes have shaped the answers.

The more you experiment with generative AI for fun, the more knowledgeable and prepared you will be to use the tool responsibly if you have occasion to use it for your academic work. Here are some ways you might experiment with generative AI tools when drafting or exploring a topic for a paper.

Potential uses

Brainstorming/exploring the instructor’s prompt Generative AI can help spark ideas or categories for brainstorming. You could try taking key words from your topic and asking questions about these ideas or concepts. As you narrow in on a topic, you can ask more specific or in-depth questions.

Based on the answers that you get from the AI tool, you may identify some topics, ideas, or areas you are interested in researching further. At this point, you can start exploring credible academic sources, visit your instructor’s office hours to discuss topic directions, meet with a research librarian for search strategies, etc.

Generating outlines AI tools can generate outlines of writing project timelines, slide presentations, and a variety of writing tasks. You can revise the prompt to generate several versions of the outlines that include, exclude, and prioritize different information. Analyze the output to spark your own thinking about how you’d like to structure the draft you’re working on.

Models of genres or types of writing If you are uncertain how to approach a new format or type of writing, an AI tool may quickly generate an example that may inform how you develop your draft. For example, you may never have written—a literature review, a cover letter for an internship, or an abstract for a research project. With good prompting, an AI tool may show you what type of written product you are aiming to develop, including typical components of that genre and examples. You can analyze the output for the sequence of information to help you get a sense of the structure of that genre, but be cautious about relying on the actual information (see pitfalls below). You can use what you learn about the structures to develop drafts with your own content.

Summarizing longer texts You can put longer texts into the AI tool and ask for a summary of the key points. You can use the summary as a guide to orient you to the text. After reading the summary, you can read the full text to analyze how the author has shaped the argument, to get the important details, and to capture important points that the tool may have omitted from the summary.

Editing/refining AI tools can help you improve your text at the sentence level. While sometimes simplistic, AI-generated text is generally free of grammatical errors. You can insert text you have written into an AI tool and ask it to check for grammatical errors or offer sentence level improvements. If this draft will be turned into your instructor, be sure to check your instructor’s policies on using AI for coursework.

As an extension of editing and revising, you may be curious about what AI can tell you about your own writing. For example, after asking AI tools to fix grammatical and punctuation errors in your text, compare your original and the AI edited version side-by-side. What do you notice about the changes that were made? Can you identify patterns in these changes? Do you agree with the changes that were made? Did AI make your writing more clear? Did it remove your unique voice? Writing is always a series of choices you make. Just because AI suggests a change, doesn’t mean you need to make it, but understanding why it was suggested may help you take a different perspective on your writing.

Translation You can prompt generative AI tools to translate text or audio into different languages for you. But similar to tools like Google Translate, these translations are not considered completely “fluent.” Generative AI can struggle with things like idiomatic phrases, context, and degree of formality.

Transactional communication Academic writing can often involve transactional communication—messages that move the writing project forward. AI tools can quickly generate drafts of polite emails to professors or classmates, meeting agendas, project timelines, event promotions, etc. Review each of the results and refine them appropriately for your audiences and purposes.

Potential pitfalls

Information may be false AI tools derive their responses by reassembling language in their data sets, most of which has been culled from the internet. As you learned long ago, not everything you read on the internet is true, so it follows that not everything culled and reassembled from the internet is true either. Beware of clearly written, but factually inaccurate or misleading responses from AI tools. Additionally, while they can appear to be “thinking,” they are literally assembling language–without human intelligence. They can produce information that seems plausible, but is in fact partly or entirely fabricated or fictional. The tendency for AI tools to invent information is sometimes referred to as “hallucinating.”

Citations and quotes may be invented AI responses may include citations (especially if you prompt them to do so), but beware. While the citations may seem reasonable and look correctly formatted, they may, in fact, not exist or be incorrect. For example, the tools may invent an author, produce a book title that doesn’t exist or incorrectly attribute language to an author who didn’t write the quote or wrote something quite different. Your instructors are conversant in the fields you are writing about and may readily identify these errors. Generative AI tools are not authoritative sources.

Responses may contain biases Again, AI tools are drawing from vast swaths of language from their data sets–and everything and anything has been said there. Accordingly, the tools mimic and repeat distortions in ideas on any topic in which bias easily enters in. Consider and look for biases in responses generated by AI tools.

You risk violating academic integrity standards When you prompt an AI tool, you may often receive a coherent, well written—and sometimes tempting—response. Unless you have received explicit, written guidance from an instructor on use of AI generated text, do not assume it is okay to copy and paste or paraphrase that language into your text—maybe at all. See your instructor’s syllabus and consult with them about how they authorize the use of AI tools and how they expect you to include citations for any content generated by the tool. The AI tools should help you to think and write, not think or write for you. You may find yourself violating the honor code if you are not thoughtful or careful in your use of any AI generated material.

The tools consume personal or private information (text or images) Do not input anything you prefer not to have widely shared into an AI generator. The tools take whatever you put in to a prompt and incorporate it into its systems for others to use.

Your ideas may be changed unacceptably When asked to paraphrase or polish a piece of writing, the tools can change the meaning. Be discerning and thorough in reviewing any generated responses to ensure the meaning captures and aligns with your own understanding.

A final note

Would you like to learn more about using AI in academic writing? Take a look at the modules in Carolina AI Literacy and the UNC Libraries’ Student Guide to AI Literacy . Acquainting yourself with these tools may be important as your thinking and writing skills grow. While these tools are new and still under development, they may be essential tools for you to understand in your current academic life and in your career after you leave the university. Beginning to experiment with and develop an understanding of the tools at this stage may serve you well along the way.

Note: This tip sheet was created in July 2023. Generative AI technology is evolving quickly. We will update the document as the technology and university landscapes change.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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A new tool helps teachers detect if AI wrote an assignment

Janet W. Lee

Several big school districts such as New York and Los Angeles have blocked access to a new chatbot that uses artificial intelligence to produce essays. One student has a new tool to help.

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Integrating AI into assignments

Main navigation.

Here we offer strategies and perspectives on integrating AI tools into assignments and activities used to assess student learning.

Creating your course policy on AI

• An effective syllabus works to motivate learning, define goals, explain course structure, and provide support to students as they learn.
• Be clearly stated and specific
• Clarify the context or conditions of allowable AI use
• Explain processes and consequences for non-compliance
• Have a thoughtful pedagogic rationale in support of student learning
• Connect to support resources
• Show support for student well-being

Outcomes for this module

In this module, we will analyze activities and assignments used for assessing learning, provide student-centered perspectives, and offer strategies for developing assessment activities and assignments that integrate student use of generative AI chatbots.

After completing this module, you should be able to:

• Describe why your assessment activities are meaningful to learners.
• Identify and clarify the learning objectives of your assessment activities.
• Identify relevant strategies that can be applied to assessment activities in your course.
• Empathize with student perspectives on using AI in course assessment activities.

Warm-up with a metacognitive exercise

As you begin to explore, think about what you already know and the opinions you may already hold about the educational aspects of AI chatbots. This metacognitive exercise can help you identify what you want to explore and what you already understand. Making connections to what you already know can deepen your learning and support your engagement with these modules.

Begin with the prompt, “Describe an assignment or assessment activity that integrated technology in a way that was effective and engaging for your learning,” and respond to the poll below.

Unpacking your assessment activities and assignments

When designing or adapting an activity or assignment used to assess learning, whether you integrate AI or not, we encourage you to consider two questions: why is this meaningful, and what are students supposed to learn from it?

Define why it is meaningful

Students can learn better when they are motivated and can make meaningful connections to coursework (Headden & McKay, 2015). We might assume that students’ motivations focus on their grades, but that assumption does not provide the full picture, and when applied in isolation it is not likely to sustain deep learning. Articulating what makes an activity meaningful, motivational, and memorable for students can help you create an engaging activity or assignment that enhances student learning and motivation.

Concerning AI chatbots, perhaps the activity or assignment addresses AI in ways that prepare students for future careers, enhance their social connections, or touch upon broader issues they care about. We encourage you to talk with your students about what they find meaningful to inform the design of your activities and assignments. What leads them to want to engage?

Also, reflect on why the assignment is meaningful to you. Is it simply convenient to implement (and standard in your experience as a student and teacher) or does it connect to something deeper in your pedagogy? Perhaps the assignment reinforces the norms and values that you share with other professionals in your discipline, allows you to connect with students in more meaningful ways, builds foundational skills for other parts of the curricula, or explores emergent opportunities and challenges with AI for your field.

Define what students are intended to learn

Next, identify and clarify the underlying learning objectives of the assignment or activity. The objective should describe the observable skills or behaviors students will have learned to perform after completing the activity. Clearly articulated learning objectives can help you develop activities that support learning and assessments that accurately measure student learning.

When thinking about AI chatbots and how they impact writing, you might ask yourself, “What are the underlying learning objectives being addressed through writing?” Instructors may assign writing tasks to assess how students engage with content. In the past, teachers could assume with good reason that a student producing coherent writing must have engaged with the content to generate writing that makes sense. However, we might also question this assumption about the automatic connection between coherent writing and deep engagement. The advent of generative AI has certainly exacerbated this.

Do you ask your students to write to demonstrate and reinforce content knowledge? Do they write to analyze and critique a position? Do they write to formulate arguments and cite evidence? Do they write as a form of creative expression? When you think about the available options, you can likely develop many ways for students to learn and demonstrate these skills with or without writing. Ultimately, honing in on the underlying learning objectives can help you integrate generative AI tools into an assignment.

Students can benefit from understanding how AI works and the educational opportunities and challenges that it presents. Consider offering the content in the modules in this guide to your students as supplemental reading or as part of a class activity.

Strategies for implementing AI into activities and assignments

As you think through how you might address or integrate AI tools in an assessment activity or assignment, we encourage you to consider a range of possibilities related to the specific aims of your course and the needs of your students. Here we offer a variety of pedagogical strategies for you to consider. We present these strategies in the context of students using AI chatbots, but they also apply to contexts without AI. Remember why your assignment is meaningful in relation to your learning objectives to help you select appropriate strategies.

Leverage multiple modalities

Consider ways to diversify when and where you assess student learning and the formats students use to express what they’ve learned.

Use more in-class assignments

Strategies like the flipped classroom model assign lecture content as homework and use the in-class time for learning activities (Lage et al., 2000). You can use this in-class time to integrate more low-stakes assessment activities during which you can better guide students toward using AI in ways that support learning.

Multiple modes of expression

Students may differ in how they can best articulate what they know. Using multiple modalities of expression, such as having students complete assignments that require speaking or graphic representations instead of only written text, stands out as an established strategy within the Universal Design for Learning framework that could apply here. While chatbots primarily generate written text, other AI tools can generate music, graphics, and video. You can thus create assessment activities that integrate multiple modalities at once.

For example, if you are assessing students’ understanding of cultural exchange in the ancient world, students might create a mind map or timeline to visually represent important trends, events, or concepts covered in the assigned readings. AI might then be used to generate images of artifacts, portraits, or cityscapes based on historical descriptions.

Make grading practices clear

Consider ways to clarify for students how they are being graded and what is expected of them.

Require robust citation

Have students learn about and adopt more robust citation practices, especially if they use AI tools for writing. You might begin with conversations about what plagiarism entails and why ethics matter in higher education and your discipline. Then connect students to resources on citation and documentation .

If you and your students decide to use AI tools, you can find style guidelines about citing AI-generated text for APA style and MLA style . These guidelines advise writers to cite the AI tool whenever they paraphrase, quote, or incorporate AI-generated content, acknowledge how they used the tool (for brainstorming, editing, and so on), and vet secondary sources generated by AI. For example, students could include citations for AI in the Works Cited section of their work and also include a statement describing why and how they used AI chatbots.

Establish and communicate clear assessment criteria

Try to bring assessment activities, learning objectives, and evaluation criteria into alignment. For example, if your objectives and assessments center around students proposing a solution to an open-ended problem, then the evaluation criteria might touch upon the feasibility, impact, or comprehensiveness of the proposed solutions. The criteria can vary a lot depending on your content and course, but your students benefit when you communicate these criteria and the purpose and reasoning behind them (Allen & Tanner, 2006).

For example, when integrating AI chatbots into a writing task for students, you might put more weight on the quality of their ideas and the validity of cited sources and less weight on structure, grammar, and word choice. You might then create a rubric that you discuss with students in advance so they have a clear understanding of what will guide you in assessing their work.

Assess learning throughout the course

Consider ways to assess student learning throughout your course as opposed to assessing mostly at the end of the course.

Emphasize the process

You may be able to more effectively assess student learning during the different stages of the process as opposed to assessing learning based on their finished work (Xu, Shen, Islam, et al., 2023). Whether or not students use AI tools, they can benefit from segmenting a large project into smaller components with multiple opportunities for feedback and revision. Also, consider how you might adjust grading criteria or grade weights to put more emphasis on the process.

For some steps in the thinking process, such as brainstorming ideas, formulating a position, and outlining a solution, allowing students to use AI tools might benefit their process. For example, you might have students begin with low-stakes free-writing, such as brainstorming, then use AI chatbots to explore possible areas for further investigation based on the ideas students generate through their exploratory writing. Students might then critique and revise the AI-generated ideas into an outline.

Leverage formative feedback

Teachers provide formative feedback to students throughout the learning process to stimulate growth and improvement. Formative feedback can help students identify misunderstandings, reinforce desirable practices, and sustain motivation (Wylie et al., 2012). You and the teaching team might provide feedback directly to students or you might facilitate students giving feedback to each other. You might then assess how students follow up on feedback they receive.

You can use AI tools to inform your feedback to students or generate feedback directly for students. AI tools could provide instant, individualized feedback efficiently and frequently, supplementing the feedback provided by your teaching team. For example, you might share your existing assignment, rubric, and sample feedback with the chatbot and give it instructions on when and how to give feedback. Importantly, you should review feedback generated by chatbots for accuracy and relevance. Refine and save the prompts that work best. You might later share the prompts you’ve developed with students so they may use them to generate feedback themselves.

Make assignments more meaningful

Consider how you might make your assignments more relatable and meaningful to your students.

Personalize assessments

When done thoughtfully, connecting assessments to the personal experiences, identities, and concerns of students and their communities can help to motivate and deepen learning (France, 2022). You might also connect assignments to contexts specific to Stanford, your course, or your specific group of students.

With AI, you or your students might generate practice questions on topics that came up during a specific class discussion or generate analogies for complex concepts based on their interests and backgrounds. You might ground an assessment activity in local contexts, such as having your engineering students propose a plan to improve Lake Lagunita.

Use real-world assessment tasks

Assignments that leverage real-world problems, stakeholders, and communities that students are likely to engage with in their work lives can be motivational and valid ways of evaluating a student’s skills and knowledge (Sambell et al., 2019).

For example, students might work with real (or AI-simulated) business or community partners to develop a prototype product or policy brief. Students might have more time to work with those stakeholders and refine their proposal concepts if they can use AI tools to assist with time-consuming tasks, such as summarizing interview transcripts, writing a project pitch statement, or generating concept images.

AI itself might provide a relevant topic of study for your course. For example, you might examine AI as part of a discussion in a course about copyright and intellectual property law. Or you might analyze AI companies such OpenAI or Anthropic as case studies in a business course.

Assess more advanced learning

Consider ways you might assess more advanced or wider-ranging learning goals and objectives.

Emphasize metacognitive reflection

Metacognitive reflection activities, where students think about what and how they learn, can help students improve their learning (Velzen, 2017). You might use polls, discussion activities, or short writing exercises through which students identify what they already know about the topic, what they learned, what questions remain, and what learning strategies they might use for studying.

AI chatbots can help guide the reflection process like this reflection tool being developed by Leticia Britos Cavagnaro at Stanford d.school . Or perhaps students complete some activities with AI, then reflect on how it benefits or hinders their learning, and what strategies they might use to best leverage AI for learning.

Prioritize higher-order thinking

While students should develop mastery over foundational skills such as understanding concepts, identifying key characteristics, and recalling important information, practicing higher-order thinking skills, such as solving complex problems, creating original works, or planning a project, can deepen learning. For example, you might frame student essays as a defense of their views rather than a simple presentation of content knowledge. You might adjust assessment criteria to prioritize creativity or applying skills to new contexts.

Prioritizing higher-order thinking can encourage students to use AI tools to go beyond simply generating answers to engaging deeply with AI chatbots to generate sophisticated responses. Students could conduct preliminary research to find reliable sources that verify or refute the claims made by the AI chatbots. AI chatbots might then generate feedback, provide prompts for further reflection, or simulate new contexts.

Putting it all together

Here we offer a practical example: first, a typical assignment as usually designed, and then how you could enhance the assignment with some strategies that integrate AI chatbots.

When thinking about your course, start with small changes to one assignment and steadily expand upon them. Try to use AI chatbots for your other work tasks to build your fluency. Talk with students and colleagues about how the changes to your course work out concerning student engagement and learning. When integrating AI into an existing assignment, begin with an assignment that already has clearly defined learning objectives and rationale. Begin by using AI or other technology to supplement existing parts of the process of completing the assignment.

More examples of AI assignments

• AI Pedagogy Project from metaLAB (at) Harvard
• Exploring AI Pedagogy from the MLA-CCCC Joint Task Force on Writing and AI
• TextGenEd: Continuing Experiments, January 2024 Collection from WAC Clearinghouse

Example of an assignment without AI

Currently, your students in an epidemiology course write essays summarizing the key concepts of an academic article about the socio-determinants of diabetes . This assessment activity has meaning because it focuses on a foundational concept students need to understand for later public health and epidemiology courses. The learning objective asks students to describe why socio-economic status is a strong predictor for certain diseases. Students write a five-page essay about a disease that can be predicted by socio-economic status including at least three additional citations. Students complete the essay, which counts for 30% of the final grade, before the final exam.

An example of an assignment that integrates AI

Using some of the strategies in the above sections, you might redesign this assignment to integrate the use of AI chatbots. Keep in mind that you would likely make small changes to a major assignment over multiple quarters. Consider some of the ideas below.

A meaningful assignment

The redesigned assessment activity carries more meaning to students because they might have personal experience of some communities adversely affected by these kinds of diseases, and public health issues like this intersect with other social injustices that students have expressed concern about.

Learning objectives

The objectives of the assessment activity include that students will be able to:

• Describe how this disease affects particular communities or demographics
• Explain the difference between correlation and causality regarding socioeconomic status and the disease
• Propose a public health intervention that could help to address this issue

Assignment elements with AI

Students generate explanations of medical terminology in the selected articles to aid with reading comprehension. They generate several analogies for the core concept that apply to their own life experiences and communities. Students share these analogies in a Canvas forum graded for participation. Instructors provide general feedback in class.

Informed by the article, students then prompt a chatbot with biographical stories for two fictional characters from communities they care about incorporating differing socio-economic factors. Then they guide the chatbot in generating a dialogue or short story that illustrates how the two characters could have different health outcomes that might correlate with their socio-economic status. Students might use AI image generators for illustrations to accompany their stories. Students submit the work via Canvas for evaluation; the teacher shares exemplars in class.

Using an AI chatbot prompt provided by the instructor, students explore possible ideas for public health interventions. The provided prompt instructs the chatbot only to help students develop their ideas rather than suggesting solutions to them. With the aid of the chatbot, the students develop a public health intervention proposal.

Assignment elements without AI

Students discuss the differences between correlation and causation, critically analyze the generated characters and stories, and address any biases and stereotypes that surfaced during the activity. You facilitate the discussion with prompts and guidelines you developed with the aid of AI chatbots. Students write an in-class metacognitive reflection that you provide feedback on and grade for completion.

Students draw posters that summarize their proposed intervention. They critique and defend their proposals in a classroom poster session. Students complete a peer evaluation form for classmates. You evaluate the posters and their defenses with a grading rubric that you developed with the aid of an AI chatbot.

Students write an in-class reflection on their projects summarizing what they have learned over the length of the project, how the activities aided their learning, and so on. This is submitted to Canvas for grading and evaluation.

Student-centered perspective on using AI for learning

When thinking about integrating generative AI into a course assignment for students, we should consider some underlying attitudes that we, the authors, hold as educators, informed by our understanding of educational research on how people learn best. They also align with our values of inclusion, compassion, and student-centered teaching. When thinking through ways to integrate AI into a student assignment, keep the following perspectives in mind.

AI is new to students too

Like many of us, students likely have a wide range of responses to AI. Students may feel excited about how AI can enhance their learning and look for opportunities to engage with it in their classes. They may have questions about course policies related to AI use, concerns about how AI impacts their discipline or career goals, and so on. You can play a valuable role in modeling thoughtful use of AI tools and helping students navigate the complex landscape of AI.

Work with students, not against them

You and your students can work together to navigate these opportunities and challenges. Solicit their perspectives and thoughts about AI. Empower students to have agency over their learning and to think about AI and other technologies they use. Teaching and learning are interconnected and work best in partnership. Approach changes to your teaching and course to empower all students as literate, responsible, independent, and thoughtful technology users.

Look at AI and students in a positive light

Education as a discipline has repeatedly integrated new technologies that may have seemed disruptive at first. Educators and students typically grapple with new technology as they determine how to best leverage its advantages and mitigate its disadvantages. We encourage you to maintain a positive view of student intentions and the potential of AI tools to enhance learning. As we collectively discover and develop effective practices, we encourage you to maintain a positive and hopeful outlook. We should try to avoid assuming that most students would use generative AI in dishonest ways or as a shortcut to doing course assignments just because some students might behave this way.

Assess and reinforce your learning

We offer this activity for you to self-assess and reflect on what you learned in this module.

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• Course and Assignment (Re-)Design , University of Michigan, Information and Technology Services
• ChatGPT Assignments to Use in Your Classroom Today , University of Central Florida

Works Cited

Allen, D., and Tanner, K. (2006). Rubrics: Tools for Making Learning Goals and Evaluation Criteria Explicit for Both Teachers and Learners. CBE - Life Sciences Education. 5(3): 197-203.

Ashford-Rowe, K., Herrington, J., & Brown, C. (2014). Establishing the critical elements that determine authentic assessment. Assessment & Evaluation in Higher Education, 39. https://doi.org/10.1080/02602938.2013.819566&nbsp ;

Bijlsma-Rutte, A., Rutters, F., Elders, P. J. M., Bot, S. D. M., & Nijpels, G. (2018). Socio-economic status and HbA1c in type 2 diabetes: A systematic review and meta-analysis. Diabetes/Metabolism Research and Reviews, 34(6), e3008. https://doi.org/10.1002/dmrr.3008&nbsp ;

CAST. (n.d.). UDL: The UDL Guidelines. Retrieved January 22, 2024, from https://udlguidelines.cast.org/&nbsp ;

Exploring AI Pedagogy. (n.d.). A Community Collection of Teaching Reflections. Retrieved January 22, 2024, from https://exploringaipedagogy.hcommons.org/&nbsp ;

France, P. E. (2022). Reclaiming Personalized Learning: A Pedagogy for Restoring Equity and Humanity in Our Classrooms (2nd ed.). Corwin.

Headden, S., & McKay, S. (2015). Motivation Matters: How New Research Can Help Teachers Boost Student Engagement. Carnegie Foundation for the Advancement of Teaching. https://eric.ed.gov/?id=ED582567&nbsp ;

Hume Center for Writing and Speaking. (n.d.). Documentation and Citation. Retrieved January 22, 2024, from https://hume.stanford.edu/resources/student-resources/writing-resources… ;

Lage, M. J., Platt, G. J., & Treglia, M. T. (2000). Inverting the Classroom: A gateway to creating an inclusive learning environment. Journal of Economic Education, 31(1), 30-43.

metaLAB (at) Harvard. (n.d.). The AI Pedagogy Project. Retrieved January 22, 2024, from https://aipedagogy.org/&nbsp ;

MLA Style Center. (2023, March 17). How do I cite generative AI in MLA style? https://style.mla.org/citing-generative-ai/&nbsp ;

Office of Community Standards. (n.d.). What Is Plagiarism? Retrieved January 22, 2024, from https://communitystandards.stanford.edu/policies-guidance/bja-guidance-… ;

Sambell, K., Brown, S., & Race, P. (2019). Assessment to Support Student Learning: Eight Challenges for 21st Century Practice. All Ireland Journal of Higher Education, 11(2), Article 2. https://ojs.aishe.org/index.php/aishe-j/article/view/414&nbsp ;

The WAC Clearinghouse. (n.d.). January 2024. Retrieved January 22, 2024, from https://wac.colostate.edu/repository/collections/continuing-experiments… ;

U-M Generative AI. (n.d.). Course and Assignment (Re-)Design. Retrieved January 22, 2024, from https://genai.umich.edu/guidance/faculty/redesigning-assessments&nbsp ;

Van Velzen, J. (2017). Metacognitive Knowledge: Development, Application, and Improvement. Information Age Publishing. https://content.infoagepub.com/files/fm/p599a21e816eb6/9781641130240_FM… . ISBN 9781641130226. 

Wylie, E. C., Gullickson, A. R., Cummings, K. E., Egelson, P., Noakes, L. A., Norman, K. M., Veeder, S. A., ... Popham, W. J. (2012). Improving Formative Assessment Practice to Empower Student Learning. Corwin Press.

Xu, X., Shen, W., Islam, A. A., et al. (2023). A whole learning process-oriented formative assessment framework to cultivate complex skills. Humanities and Social Sciences Communications, 10, 653. https://doi.org/10.1057/s41599-023-02200-0  

Yee, K., Whittington, K., Doggette, E., & Uttich, L. (2023). ChatGPT Assignments to Use in Your Classroom Today. UCF Created OER Works, (8). Retrieved from https://stars.library.ucf.edu/oer/8  

You've completed all the modules

We hope that you found these modules useful and engaging, and are better able to address AI chatbots in your teaching practice. Please continue to engage by joining or starting dialogues about AI within your communities. You might also take advantage of our peers across campus who are developing resources on this topic.

• Institute for Human-Centered Artificial Intelligence
• Accelerator for Learning
• Office of Innovation and Technology , Graduate School of Education

We are continuing to develop more resources and learning experiences for the Teaching Commons on this and other topics. We'd love to get your feedback and are looking for collaborators. We invite you to join the Teaching Commons team .

Learning together with others can deepen the learning experience. We encourage you to organize your colleagues to complete these modules together or facilitate a workshop using our Do-it-yourself Workshop Kits on AI in education. Consider how you might adapt, remix, or enhance these resources for your needs. 

If you have any questions, contact us at [email protected] . This guide is licensed under  Creative Commons BY-NC-SA 4.0 (attribution, non-commercial, share-alike) and should be attributed to Stanford Teaching Commons.

For students: What you need to know about proper AI writing tool use (part 1 of 2)

Commemorating the International Day of Action for Academic Integrity: Championing academic integrity in the age of AI

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We chose to write this blog post about proper use of AI writing tools with student needs in mind, because so many of the resources out there for students are published by AI companies themselves. We can’t overlook students, because you are the most important part of the discussion around academic integrity. In fact, academic integrity requires student understanding and participation; for example, the International Day of Action for Academic Integrity on October 18, 2023 purposely includes student involvement.

Understanding academic integrity and proper AI writing tool use helps you avoid plagiarism and misconduct. Participation in discussions around academic integrity and proper AI writing tool use makes it so you have a say in your own learning goals and create a good culture around learning at your school.

We’re going to divide this blog post up into several sections; we’ll begin with the definition of academic integrity, then getting more specific about AI and its relationship to academic integrity, and finally providing some information about proper AI writing tool use (and misuse). In doing so, the intent is to help you understand the ways in which students can use AI properly and avoid academic dishonesty.

First, what is academic integrity?

Oftentimes, folks define academic integrity as what it is not (i.e., not plagiarizing, not contract cheating, not engaging in AI writing misconduct, and not cheating in general), but then students miss out on what it is supposed to be.

The word “academic integrity” focuses on a commitment to honesty , trust , fairness , respect , responsibility , and courage .

An authoritative definition of academic integrity can be found at the International Center of Academic Integrity (ICAI) , which was founded in 1992 by leading researchers. (Did you know there is an entire cohort of academics whose focus is primarily about academic integrity)? Don McCabe is credited as the person who popularized the term “academic integrity.” In 1999, the Center identified and described the “ fundamental values of academic integrity ” as honesty, trust, fairness, respect, and responsibility, and in 2014 added the sixth value of courage. Academic integrity, per the ICAI, is a commitment to these values ( Turnitin, 2023 ).

The values of academic integrity can be described in the following ways:

• Honesty : be truthful, give credit, and provide facts
• Trust : provide transparency, trust others, give credence
• Fairness : apply rules consistently, engage with others equitably, and take responsibility for our own actions
• Respect : receive feedback willingly, accept others’ thoughts, and recognize the impacts of our own words and actions on others
• Responsibility : follow institutional rules and conduct codes, engage in difficult conversations, and model good behavior
• Courage : take a stand to address wrongdoing, be undaunted in defending integrity, and endure discomfort for something you believe in ( ICAI, 2020 )

The above values, when put into action, display academic integrity.

What do AI writing tools have to do with academic integrity?

AI writing tools and their relationship to academic integrity is a top subject of discussion these days, spurred by the release of ChatGPT in late 2022 by a company called OpenAI. ChatGPT was a huge advancement in Artificial Intelligence, producing responses very, very close to human speech. It can generate replies to short answer questions, and provide essay-length responses.

These advances in AI caused a lot of alarm in the education community (and elsewhere; for instance, the writer and actor unions (WGA and SAG-AFTRA) went on strike in Hollywood, with one of their main concerns being AI-generated work ). While educators (academic leaders and faculty) have broadened their discussions around AI writing tools like ChatGPT and accepted that AI is here to stay, the initial (and ongoing) fear is that students will use these tools and represent their output as their own original work. In other words, teachers are afraid that students will use ChatGPT to cheat.

How do you use generative AI tools with academic integrity? Let’s roll it back up to those values of academic integrity as it pertains to AI writing tools.

AI and the value of honesty

Honesty is about being truthful, fact-based, and giving credit to the person who came up with the ideas. If you disclose your use of AI writing tools by citing AI, then you’re using AI writing tools with integrity. However, if you do not attribute work written by AI writing tools and instead claim the work as your own, then you are violating academic integrity.

AI and the value of trust

Are you providing transparency in your work? This means that if you’re using AI writing tools to brainstorm or help with writing structure, you should be clear about your actions. Doing so builds trust with your instructor. Hiding any work you’ve done with the help of AI violates trust.

AI and the value of fairness

Fairness means that everyone is working with the same resources and consistency, and that we take responsibility for our own actions. When you submit work to your instructor, you are taking responsibility for the content and claiming it as your own original work. Is an AI writing tool giving you an unfair advantage over others? For instance, if you’re working on an assignment and the rules are not to use AI, and you might be one of a few (or the only one) using AI to complete an assignment; this is a shortcut solution that disregards fairness.

AI and the value of respect

Receiving feedback and recognizing the impact of your words and actions on other folks are ways to show respect. Improper use of AI (e.g., when it’s not allowed on an assignment) flouts learning, which disrespects the instructor and your cohort’s efforts. While generative AI tools can be useful to help you understand a topic or structure your thoughts, using them to write extensive parts of work for you, especially when it’s not allowed or required for part of the assignment, is academic misconduct.

AI and the value of responsibility

This value is pretty clear, as responsibility is about following codes of conduct and modeling good behavior. If you’re using AI writing tools with the blessing of your instructor, then you’re following instructions. If you’re using AI writing tools secretly and in defiance of rules, then you’re not only breaking rules, you’re not modeling good behavior.

AI and the value of courage

Courage is about standing up for what’s right, defending integrity, and in some cases, enduring discomfort for what you believe in. Learning isn’t always easy, but the end result is valuable. Resisting the temptation to use AI writing tools when they’re not allowed or making sure to always attribute AI-generated text is simply an act of courage. Maybe that line is a bit cringey, but you’ll find that standing your ground and staying the course on learning is brave.

How can I use AI properly?

Responsible AI use follows the tenets of academic integrity. (Additionally, you may want to refer to your school or university policy on proper AI use, if one exists. The following are some general suggestions to supplement your school’s code of conduct).

AI is a toolkit for solving problems, like calculators for math calculations. When used correctly, it can be an aid for learning and fostering thinking skills. But when we become dependent on technology, it’s easy to skip steps in learning and end up in a place where you aren’t able to do things on your own. Additionally, ChatGPT doesn’t always provide accurate information; you will need to double check everything, including sources, that ChatGPT offers. In some ways, they are calculators; in other ways, they are inaccurate calculators, so you need to understand the basics of what you are trying to say. The following are ways to make sure you are using AI properly in your work.

Acknowledge the use of AI in your work

Any writing that generative AI provides has to be cited. The current guidelines for citing AI are still being developed. For most referencing styles, there are no specific directions for citing ChatGPT or other generative AI ( University of Queensland ). This makes things a bit more complicated.

However, there are interim guidelines for citing AI in different citation formats. The University of Queensland provides some information on citing AI in APA, AGLC, Chicago, and MLA formats.

For instance, in APA format, you might want to cite AI in the following way:

In-text citation :

Author of generative AI model, Year of version used

(OpenAI, 2022)

Reference list or works cited :

Author of AI model used. (Year of AI model used). Name of AI model used (Version of AI model used) [Type or description of AI model used]. Web address of AI model used

OpenAI. (2022). ChatGPT (December 20 version) [Large language model]. https://chat.openai.com/

The full transcript of a response can be included in an appendix or other supplementary materials.

For MLA, AI citations may look like this:

(Short form Title of source)

(“Compare and contrast the setting”)

Reference list or work cited :

“Title of source” prompt. Name of AI Tool, version, Company, Date content was generated, General web address of tool.

“Compare and contrast the settings of Italy and Britain in A Room With a View by E.M. Forster” prompt. ChatGPT, 1 Jan version, OpenAI, 14 September, 2023, chat.openai.com/chat .

Chicago style

The Chicago Manual of Style also provides guidance on how to cite ChatGPT or any other generative AI. Again, however, these guidelines are evolving and may change, but for now, these are some examples of how to cite AI in Chicago style:

Numbered footnote or endnote :

1. Text generated by ChatGPT, OpenAI, September 14, 2023, https://chat.openai.com/chat.

If the prompt hasn’t been included in the text, it can be included in the note :

1. ChatGPT, response to “Why are hydrocarbons thought of as scaffolds for functional groups?” OpenAI, September 14, 2023.

Acknowledging the use of AI when there are no referencing guidelines or if you’ve used AI at all:

Even if there are no referencing guidelines for a citation format or if you used AI writing tools at any point in your writing process, you should still acknowledge any use of AI that you’ve used to help complete your assignment. According to Latrobe University, one example of an acknowledgment looks like the following: Whilst/While the writing is my own and I take responsibility for all errors, ChatGPT was used to create the initial section structure for this essay.

Furthermore, AI writing tools can’t accurately cite their own sources (and thus, often plagiarize material, so it may show up in similarity detection like Turnitin Feedback Studio). So you also need to double check ChatGPT’s sources, as they may be wrong or completely made up. Those sources, too, need to be cited.

Using AI to help you study

Another proper use for AI is to study; AI tools can be used to:

• Generate practice quizzes or flashcards to help you prepare for exams
• Tutor yourself to improve your language skills
• Interact with virtual tutors
• Create study guides
• Summarize a recorded lecture
• Conduct research and find key points on a particular subject or topic
• Evaluate mathematical problems, lines of computer code, and complex formulas
• Brainstorm ways to start a new project
• Stimulate your thinking and develop new ideas
• Inspire you to ask questions you might not otherwise consider
• Request study strategies
• Encourage your AI tool to motivate you
• Ask AI to help you manage your study time by analyzing your schedule and suggesting the best study periods ( Latrobe University, 2023 ; EuroEducation, 2023 ; Chen, The New York Times, 2023 )

That said, The New York Times says there’s “One warning to keep in mind: When studying, it’s paramount that the information is correct, and to get the most accurate results, you should direct A.I. tools to focus on information from trusted sources rather than pull data from across the web” ( Chen, 2023 ).

If you’re in doubt, Turnitin has an Ethical AI use checklist for students for your use.

Brainstorming ideas

For instance, using AI to brainstorm ideas or find a way to structure an essay can be useful and further learning, particularly when teachers give permission to use AI for this purpose. One particularly effective use for AI is to ask it to generate counter-arguments to identify points you may have overlooked in your argument. Using those brainstormed ideas to write something in your own words with your own research can qualify as proper use, especially when the final work states that you used AI in the initial stages.

AI is also useful to figure out how to structure your argument; but your argument, too, must be your own and in your own words. If you use AI for this function, be sure to state that you’ve used AI in the initial stages of your work.

The gray area of AI use, also known as The Fine Print

All of the ways students can use generative AI is subject to the code of conduct at your school. That is, if your school bans any use of AI in completing assignments, including brainstorming, then you should not use AI; in the case that AI is explicitly banned, any use would then be misuse.

Conclusion: What you need to know about proper AI writing tool use as students

Here’s the thing: the process of writing is how you learn to think and express your ideas. While AI tools can help you study, and can help you get started with framing your thoughts, your thoughts must be your own, and reflected in the work you submit for evaluation.

Think of it this way: it’s okay to ask someone to proofread your work and make sure you don’t have spelling or grammar errors. But it’s not okay to ask someone to rewrite your work.

It’s also okay to ask someone to help you brainstorm, but it’s not okay to ask someone to write your essay for you.

AI is here to stay, and students need to understand what constitutes proper and improper use of AI writing tools. This is important because not only do you want to avoid misconduct and discipline, you want to make sure that you come out of school prepared for the future. This preparation includes a deep understanding of academic integrity as well as a firm footing in the subject matter you’ve studied.

AI-Resistant Assignments

Last Updated: Winter/Spring 2023

• Assignments that emphasize the writing process, rather than just the final product, will discourage students from using AI tools to do their work for them.
• Process-oriented assignments also tend to be more engaging and impactful for students.
• Framing your writing assignments as extensions of the class discourse challenges students to respond to the course content with new ideas of their own (something AI generally can’t accomplish).
• Making revision integral to the assignment helps students critically examine and improve their writing process, while making it harder to take AI-assisted shortcuts.
• Reflective and metacognitive writing assignments make students’ learning visible to them and to you; it also holds students accountable for the intellectual work of your course.

See assignment prompts that incorporate one or more of these principles.

At the time of this writing (winter 2023), the AI writing tool ChatGPT has recently launched, with several competitors soon to follow, and it’s clear that artificial intelligence will have a massive impact on the way we write, both inside and outside academia, for the foreseeable future.  As AI continues to evolve, so will our teaching practices, but one immediate concern for many instructors is the possibility that students may use ChatGPT and similar text-generation tools to avoid the intellectual work prescribed by many of our writing assignments.  

While the current generation of AI tools can’t produce particularly insightful or effective academic writing, that doesn’t mean students won’t try to substitute AI-written work for their own.  Furthermore, savvy users have already found more subtle ways to use ChatGPT to make their work as writers easier, such as using it to produce revisable first drafts or to shortcut the research process by identifying and summarizing a variety of sources on a given topic.  Whether these practices constitute academic misconduct or not is largely up to individual instructors to decide, but if you would personally consider them inappropriate for your courses, it’s worth considering how you might design new writing assignments or reconfigure old ones to make them less susceptible to digital assistance.

Fortunately, many of the existing best practices for designing writing assignments can also make them more difficult to complete with AI tools.  More importantly, though, they can also discourage students from turning to AI in the first place by placing greater value on the writing process, rather than just its product.  This helps to make the learning process more transparent and makes assignments more engaging, accessible, and impactful for students who complete them faithfully.

Making Writing an Extension of the Class Discourse

The best writing assignments will often ask students to engage not just the subject matter or source material of the course, but the discourse around that material that develops within the class itself.  A prompt, for example, might explicitly require students to respond to ideas that have come up in class discussion, or to apply concepts or themes that you’ve examined in class to a new text or subject.  However you frame it, the key to this approach is asking students to contribute something new to the discussion that explicitly builds on ideas they’ve encountered in your course.  In other words, ask students to make their writing an extension of the class itself, rather than an exercise that just happens to address the same basic material. This distinction can be subtle, but here are a few sample prompts that use this approach effectively .

This might not seem like a revelatory practice–after all, don’t all essay assignments require students to engage core ideas from the course?  But there’s an essential difference between simply engaging ideas from a course and responding to them effectively in conversation.  Engagement simply requires a student to understand the material and react to it.  Responding requires them to have a working understanding of the discourse around the material — who has said what, where previous speakers have agreed, disagreed, complemented and contradicted each other, and, most crucially, what remains to be said.  

As scholars, we all understand this implicitly; we review and cite other scholars because we want readers to see exactly where and how we’ve built upon the ideas that have come before, and we craft our arguments in ways that actively invite future scholars to respond to them.  Students, however, especially students who are new to college-level writing, tend not to think of their writing this way until they’re explicitly taught to do so.  High school classes and high-stakes standardized exams generally train students to see writing as a series of hurdles which they must complete for the sole purpose of demonstrating that they know the course material and can explain it in their own words.  Consequently, students often approach their writing exactly the way an AI would: by seeking to remix other people’s ideas in a way that fulfills the prompt, whether or not they say anything particularly new or interesting along the way.

Framing assignments as a way to build on the class discourse requires students to take a more active role through their writing, and in the course itself.  Once they come to understand that their writing will be an extension of the conversation taking place in the classroom, they start to realize that the more they participate in (or at least actively pay attention to) that conversation, the easier it becomes to engage it in writing.  They also become more invested in their writing, as they start to see the essay as a distillation of ideas that grew out of real interactions with real people, not a detached set of musings composed in isolation and shouted into the void (or the cloud).  

The writing produced this way is often messy, over-energetic, unfocused, underdeveloped, or otherwise heavily in need of revision. But it also tends to have a life and a voice that’s distinctive to the course, the term, the class, and the student all at once, and AI tools cannot match this distinctiveness. An AI can learn in the sense that it can gradually produce more refined output, but it can’t understand the ideas it synthesizes well enough to add anything distinctive and relevant to them. It can’t think , and that’s exactly what a good writing assignment will require students to do, above all else. Thus, any assignment that requires students to think — and to articulate their thinking clearly — in response to the ideas they encounter will resist AI’s intervention.

Creating Space for Revision

Most instructors encourage their students to make at least some effort to revise their writing.  We may implore them to start early, to consult the writing center, to read their essays out loud or to a friend, to form peer review groups, and so on. But it’s another thing entirely to make revision an integral and visible part of an assignment. Doing this not only places direct value on revision, but it also allows students to see and understand how revision works and why it’s so crucial to good writing and good thinking.

It’s important at this point to articulate a distinction that might seem obvious to any experienced writer, but is often revelatory to students: revision is not the same as editing. Editing (in this context, anyway) means examining and improving the presentation of one’s ideas–the grammar, the phrasing, the formatting, etc. Revision, on the other hand, means examining and improving the ideas themselves–fundamentally re-envisioning one’s conclusions and the tapestry of sources, responses, counter-responses, and epiphanies that lead to them. Most students don’t fully understand this distinction or, if they do, are not sure how to apply it to their own writing. They need to be taught how to revise, and this makes it hugely beneficial to them when revision becomes an integral part of an essay assignment.  When an instructor and a well-crafted assignment guide them through the revision process, many students discover for the first time what they’re really capable of as writers.

Granted, extended revision can be difficult to integrate into classes that are not explicitly designed to teach writing. Many instructors simply don’t have the luxury of time necessary to collect full drafts, comment on them in any significant way, and repeat again with the final drafts.  Fortunately, this is not the only way to create space for revision. Consider these alternatives, none of which are mutually exclusive:

• Simply spend some time in class discussing revision, giving students examples of what you would consider a solid first draft and solid final draft and offering various techniques for getting from the former to the latter (there are many, many resources for revision advice to be found online–find one that feels like the best fit for your assignment and point students there, or ask the WAC Director for suggestions).  Have students submit their rough drafts along with the final versions, and be sure to comment on how well the final draft improves on the earlier version in your feedback to the students.
• Conduct a peer review session, either in class or asynchronously through the cloud, in which students comment on each other’s drafts.  When they submit their final drafts, ask students to address if and how they responded to their peers’ comments.
• Set aside all or part of a class session on the day drafts are due, and have students evaluate their own drafts: what turned out well, what aspects are still in process, and how will they proceed with that knowledge? Have them turn this into a written revision plan, to guide the process to the final draft.
• In a class with multiple essay assignments, require students to choose one essay to revise and resubmit at the end of the term.  You can allow the revised essay to replace the grade of the earlier version, or make it a separate assignment grade (both approaches have their own pedagogical merits).

Each of these techniques helps to make revision an integral part of the assignment, not a side practice that we might encourage, but not explicitly require. They also create opportunities for you as an instructor to step in and guide students’ revision processes, helping them to see methods and opportunities to improve their writing that they don’t.  While this kind of feedback does require some time and attention on the instructor’s part, it can often allow for less feedback (and easier grading) on the final version of the assignment, as you’ll already have created a dialogue with the students around the assignment that you can simply bring to a close with a few explanatory notes and (ideally) a completed rubric.

The concrete ways that revision complicates the use of AI writing tools are fairly obvious. Essays produced by ChatGPT tend to be remarkably free from grammatical errors, but fairly vacuous; thus, they require little editing but a great deal of revision. And, since it’s generally harder to revise someone else’s work effectively than your own, students who produce their drafts with ChatGPT will often find that the revision process requires more work for less return.

Again, though, the real value of guided revision is that it encourages students to see their writing as a work in progress and to get a better sense of what they can accomplish with a fully developed writing process. The more pride and value they associate with their own writing, the less likely they’ll be to let AI do it for them.

Encouraging Reflection and Metacognition

The WAC Program has (to understate it mildly) promoted reflective and metacognitive writing as a teaching practice for some time, so it’s probably no surprise to see a section on them here. In the context of creating AI-resistant writing assignments, though, reflective and metacognitive writing take on additional layers of value, both because they help students to see the benefits of their own intellectual work and because they make it more difficult to conceal if they’ve allowed AI to do that work for them. 

Quickly stated, the distinction between the two modes is that reflective writing looks backwards (what have I learned and experienced?), while metacognitive writing looks forwards (how can these experiences inform my future actions and methods?).  These modes of thinking go together more often than not, and both are obviously essential for learning.  By challenging students to enact these processes–to actively consider, in writing, what they’ve learned and what they plan to do with that learning–we help them to connect the disparate pieces of their education, understand their own strengths and weaknesses more effectively, and simply develop a better understanding of themselves.

In practice, this is often a much simpler and smaller-scale operation than those principles would suggest.  Any formal writing assignment can be scaffolded fairly easily with one or more informal reflective and/or metacognitive tasks.  These tasks can (and generally should) be short and fairly simple both to write and to read.  They can happen at any point in the writing process–before, after, or even while the student is writing the assignment itself.  Consider a few common scaffolding assignments in this vein:

• A week or more before a formal writing assignment is due, ask students to write a paragraph or two summarizing their topic and articulating why they chose it (ideally, in the context of the ideas above, explaining how their assignment will respond to ideas that they have encountered in class).  Then, ask them to assess the work they’ll need to do to complete the assignment–what sources will they engage and how, what questions will they have to address, what conclusions do they still need to form, etc.?
• The weekend before the assignment is due, ask students to write a concrete plan for their entire writing process. How long do they think it will take to create an outline, write a draft, revise it, and proofread it? When and where will they do this work? What additional help, if any, will they seek out, from whom, and when?
• As they turn in the assignment, have students compose a short note to you about their writing process and how it worked out for them. How did their ideas change between conception and completion? What steps were easy or difficult? Did any of that surprise them? Overall, how happy are they with the final product as they submit it to you? Comment on this note as part of your feedback to the student — based on the final product, what aspects of the student’s writing process served them well, and what practices might they want to change or adopt for the next assignment?
• As they begin work on the next assignment, ask students to consider what they learned writing the last one. What ideas from that project will inform this one? What lessons about their own writing process did they learn, and how will that inform the way they write this assignment?

None of these techniques are particularly novel, but they are powerful, because they require students to consider not just the final product of the assignment, but the actual learning process that the assignment is designed to enact.  It seems obvious to us that we create writing assignments because we want students to learn from the process of writing them, but students tend to fixate on the product rather than the process.  This makes the actual work of writing seem obscure and magical, even when they do it themselves. They sit down at the computer, mull over the topic at hand, and gradually, sometimes painfully, the final product grinds itself into being.  When they’re asked to articulate these steps in writing, though, their process becomes visible to them, and the opportunity emerges for them to critically examine what they do and how they can do it better.

Their writing process also becomes more visible to you, which is useful both instructionally and in the context of making assignments AI-resistant.  In instructional terms, metacognitive writing allows you to respond to the way students work, not just the work itself.  You can see how their ideas evolve and, ideally, help to guide them.  You can see how students approach writing (from methodologies of research to basic time management) and offer encouragement or guidance.  In other words, you can make their learning an active part of the class.

This pushes against the encroachment of AI in a number of ways.  Most concretely, any of the metacognitive steps suggested above could be completed effectively in class, making it much harder (though perhaps not impossible) for students to covertly hand the work over to the robot.  Furthermore, if students know that they’ll have to explain their writing process in some detail, they might think twice about letting AI do the writing.  None of the tasks suggested above should be particularly challenging for students who actually completed the assignment as designed, but they’re considerably more challenging as exercises in creative fiction.  Pointing this out to students when you introduce the assignment can reduce the perceived benefits of letting AI do the heavy lifting.

On a less concrete but more profound level, though, this kind of scaffolding discourages AI-based cheating by placing value on the writing process rather than just the product.  By helping students see how the real intellectual labor called for by your assignment is meant to benefit them, you discourage the transactional mentality that sees assignments essentially as invoices for students to fill.  My experience is that the overwhelming majority of students are more willing to work than we tend to assume, as long as they believe that their efforts will be rewarded in some way, and metacognitive writing can help them see the benefits of their work in a useful and tangible form.

The same can really be said for any of the practices described above. At the end of the day, we cannot force students to feel invested in their educations, nor can we stop them from seeking out ways to make their academic work easier, legitimately or otherwise. However, if we start from the assumption that most students are invested in their education and truly want to learn, and we create assignments that allow them to see and experience that learning as it happens, then the perceived value of letting AI do their writing for them will diminish significantly. It will also allow us, as instructors, to approach AI writing tools from a position of strength by making it a teaching issue rather than a detection and enforcement issue.

Center for Educational Effectiveness

Ai & student writing.

AI & Teaching

What is it.

Generative AI (GenAI) like ChatGPT and Google Bard are based on Large Language Models (LLMs). These chatbots were trained by applying machine learning techniques, modeled on neural networks, to find patterns in billions of documents. They generate original text by predicting the likeliest sequence of words in response to a prompt, based on their training data. They do not understand content and can make mistakes. Many professions are incorporating AI into their workflows, so educators may need to cultivate AI literacy and train students to use these tools strategically and thoughtfully.

Research on AI and student writing is rapidly evolving with the technology. Current research suggests that when used appropriately, AI may enhance student drafting, revision, and research practices (Dobrin, 2023). Additionally, AI may help students who have had less access to academic English to receive feedback on word choice and grammar (Warschauer et al., 2023). Despite this benefit, these tools reinforce dominant language practices which often erase marginalized voices and encode existing social, racial and linguistic bias (Bender et al, 2020). “Chatbots can democratize access to expertise,” but in recent history, over reliance on AI has hindered critical judgment and even “erode[d] expertise” (MacArthur, 2023). If students over rely on chatbots, they may “limit their intellectual growth and confidence” (Buriak et al., 2023). Since policies that prohibit AI are ineffective, instructors should strive to create learning environments that encourage critical and transparent AI use (MLA-CCCC, 2023).

• "43%  of college students have used ChatGPT or a similar AI application. Of those who have used AI tools, 50% say they have used them to help complete assignments or exams.” (Welding, 2023)
• " Over half of college students (54%) say their instructors have not openly discussed the use of AI tools like ChatGPT.” (Welding, 2023)

Teaching Strategies

T o mitigate plagiarism, set clear policies for AI use in your syllabi. Here are three samples from the University Writing Program . Provide students with resources on how to ethically cite AI ( APA ; MLA ; Chicago ).

Identify the content, skills, and writing tasks your students struggle with. Consider whether AI would help student learning in these areas.

Brainstorming:   AI can be especially useful before students start drafting. For example, AI can provide background information or generate a list of research questions.

Editing: AI can increase equity for students who have had less access to academic English. On the other hand, these same students may be accused of plagiarism more often (Warschauer et al., 2023). Example prompt: “Copy edit this text. Then, tell me what you changed and why.” 

Tutoring: Students can use AI to help learn new or difficult concepts and skills with prompts like “Act like a tutor…” . AI can also generate examples to help students grasp new ideas or to provide instructors with examples for classroom use.

Discuss the benefits and risks of AI in science communication.  While AI can assist with the writing process in many ways, from improving organization to refining abstracts, it can also omit minority perspectives, replicate human bias, and impede the critical thinking necessary for creative science and the development of expertise.

Test out your assignments on AI to determine their level of exposure and adjust accordingly. Critique AI drafts with students to identify lack of complexity or nuance.

Provide students with clear criteria, assignment goals or rubrics so they can ask AI for targeted feedback (Mollick & Mollick, 2023). AI is not always correct; remind students they should view feedback critically and ask them to explain feedback they used. Share Chatbot prompting resources and see Mollick & Mollick (2023) for detailed prompts.

Students say …

"AI writing tools can be helpful in aiding the research and writing process. They assist me  in sorting through information, brainstorming ideas, and even providing inspiration. However, it is important for me to remain vigilant and maintain a thorough understanding and control of the content throughout the writing process."

“ ChatGPT … helped me reorganize sentences that were confusing for native speakers"

• "I will never be comfortable using AI to come up with statements and concepts for projects I am responsible for."
• How do you encourage students to work with AI Writing Tools in ethical, critical, and constructive ways that reflect writing processes and workflows they will engage in not only in their academic work but also during their professional careers?
• What aspects of your classroom policies (e.g., Syllabus Language around AI Writing Tools Usage, Grading, Participation) can you revise to better reflect your commitment to integrating thoughtful and critical AI usage into your writing assignments?
• Consider the content and skills you intend to teach with an assignment. What do students struggle with? Does the struggle help or hinder their learning? For example, academic reading is difficult for many students and AI can help them understand technical concepts; however, If your goal is for students to to analyze research methods, then an AI summary may hinder learning.
• Have you shared tips with students to protect peers’ and their own privacy and intellectual property while using AI? Consider discussing how chatbots may use their work to further train itself and create and sell new products.
• Have you reviewed the Instructor Resources created by the University Writing Program and the Writing Center (see Further Resources below)?

Further Resources

Writing and AI: Resources for Instructors Resources for Students to Develop Critical AI Literacy ChatGPT Resources  -  This list of articles and other resources is curated by Dr. Margaret Merrill, Senior Instructional Design Consultant at the University of California, Davis. 

Contributors

Joanna Johnson , Marit MacArthur , Sophia Minnillo , Kem Saichaie , Lisa Sperber , Nick Stillman , and Carl Whithaus

Share your feedback

After exploring our AI & Student Writing JITT, we invite you to respond to a few brief questions. We value your time and feedback as we strive to continuously improve Just-In-Time Teaching resources on Generative AI.

Feedback Form

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency , 610–623. https://doi.org/10.1145/3442188.3445922

Buriak, J. M., Akinwande, D., Artzi, N., Brinker, C. J., Burrows, C., Chan, W. C. W., Chen, C., Chen, X., Chhowalla, M., Chi, L., Chueh, W., Crudden, C. M., Di Carlo, D., Glotzer, S. C., Hersam, M. C., Ho, D., Hu, T. Y., Huang, J., Javey, A., … Ye, J. (2023). Best Practices for Using AI When Writing Scientific Manuscripts. ACS Nano , 17 (5), 4091–4093. https://doi.org/10.1021/acsnano.3c01544

ChatGPT . (2023, July 13). ChatGPT. Retrieved August 31, 2023, from https://chat.openai.com

Dobrin, Sidney. (2023). Talking About Generative AI: A Guide for Instructors . Broadview Press. https://drive.google.com/file/u/1/d/1svsCFEs0t42Psd6t-VCSRd333ZcZynfK/view?usp=sharing&usp=embed_facebook

Gladd, J. (2020). How to Prompt AI Chatbots. In Write What Matters . Press Books. https://idaho.pressbooks.pub/write/chapter/how-to-begin-prompting-ai-chatbots/

MacArthur, Marit. (2023). Expertise, Generative AI, and the Convergent Futures of (Teaching) Writing and Coding. Inside Higher Ed. (forthcoming).

MLA-CCCC Joint Task Force on Writing and AI. (2023, July). MLA-CCCC Joint Task Force on Writing and AI Working Paper: Overview of the Issues, Statement of Principles, and Recommendations . https://aiandwriting.hcommons.org/working-paper-1/

Mollick, E. R., & Mollick, L. (2023). Assigning AI: Seven Approaches for Students, with Prompts (SSRN Scholarly Paper 4475995). https://doi.org/10.2139/ssrn.4475995

University of Pittsburgh Writing Institute Workshop on AI and the & Teaching of Writing. (2023, June 1). Stress Testing Writing Assignments: Evaluating Exposure of an Assignment’s Tasks to AI . https://www.writinginstitute.pitt.edu/sites/default/files/PDFs/stress_testing_writing_assignments_6.1.23.pdf

Warschauer, M., Tseng, W., Yim, S., Webster, T., Jacob, S., Du, Q., & Tate, T. (2023). The Affordances and Contradictions of AI-Generated Text for Second Language Writers (SSRN Scholarly Paper 4404380). https://doi.org/10.2139/ssrn.4404380

Welding, L. (2023, March 27). Half of College Students Say Using AI Is Cheating . Best Colleges. https://www.bestcolleges.com/research/college-students-ai-tools-survey/

Center for Teaching Innovation

Ai in assignment design.

Using generative artificial intelligence (AI) can be both productive and limiting—it can help students to create and revise content, yet it also has the potential to undermine the process by which students create. When incorporated effectively into assignments, generative AI can be leveraged to stimulate students' ability to apply essential knowledge and develop critical thinking skills. 

As you explore the possible uses of generative AI in your course, note that establishing a general familiarity with generative AI and being mindful of accessibility and ethical concerns will be helpful. 

The following process may help you determine how to best incorporate generative AI into your course assignments.

Affirm What You Actually Want to Assess

As you decide how you might incorporate AI into your course, it’s important to revisit your current course assessment plan, most importantly your course learning outcomes —that is, the skills and knowledge you want students to learn and demonstrate by the end of your course. Once you have a clear idea of the specific skills/knowledge you want to assess, the following questions can help determine whether or not your current assignments are effective and assessing what you want them to assess:

• Does my assignment call for the same type of thinking skills that are articulated in my class outcomes? For example, if my course learning outcome calls for students to analyze major themes in a work, is there risk of my final assignment prompting students to do more (e.g., synthesize multiple themes across multiple works) or to do less (e.g., merely identify a theme) than this outcome? If so, there may be a misalignment that can easily be addressed.
• Does my assignment call for the same type of thinking skills that students have actually practiced in class? For example, if I am asking students to generate a research prospectus, have I given them adequate opportunity to develop—and receive feedback on—this skill in class?
• Depending on your discipline, is there a need for an additional course outcome that honors what students now need to know about the use of generative AI in your course/field?

Explore When & How Generative AI Can Facilitate Student Learning

Once you have affirmed your learning outcomes and ensured that your assignments are properly aligned with those outcomes, think about if, when, and how it might make sense to incorporate generative AI. Is there a way to leverage generative AI to engage students in deeper learning, provide meaningful practice, or help scaffold your assignments?

Consider the usefulness of generative AI to serve as:

• Have students analyze AI-generated texts to articulate what constitutes “good” (and not so good) responses to prompts.
• Have students analyze AI-generated texts and engage in error analysis to develop more nuanced and discipline-specific writing skills.
• Leverage the use of generative AI platforms to help students become more discerning. This can help students develop the critical thinking and information literacy skills required to effectively and responsibly use such platforms.
• Have students revise AI-generated texts to develop critical thinking skills.
• Have students engage with a generative AI platform as a tutor. 
• Facilitate students’ responsible, self-guided use of generative AI to develop select discipline specific skills (e.g., coding in computer science courses)
• Have students use generative AI to off-load repetitive tasks.
• Have students use generative AI to conduct preliminary analysis of data sets to confirm broad takeaways and affirm that their more nuanced analysis is heading in the right direction.

Identify When Generative AI Cannot Facilitate Student Learning

It is often the case that students cannot—or should not—leverage generative AI to promote or demonstrate their own learning. To help ensure that your assignment design highlights students’ unique perspectives and underscores the importance of a (non-generative AI informed) discipline-specific process, consider how to emphasize metacognition, authentic application, thematic connection, or personal reflection.  

Even if another part of an assignment calls for the use of generative AI, the following strategies may supplement the uses of AI highlighted above and foster deep and meaningful learning:

• Have students identify the successes and challenges they experienced throughout the completion of a project.
• Have students set incremental goals throughout a project, highlighting next steps of a discipline-specific process, resources they used, and the steps about which they are enthusiastic/nervous.
• Have students self-assess their work, identifying strengths and weaknesses of their product/effort.
• Have students engage in problem-based learning projects, ideally in authentic settings (e.g., problems that focus on our local community, real-world challenges, real-world industries, etc.).
• Have students present projects (and engage with) authentic audiences (e.g., real stakeholders, discipline-specific research partners, native-speaking language partners, etc.)
• Have students connect select reading(s) to course experiences (e.g., labs, field experiences, class discussions). 
• Leverage Canvas-based tools that promote student-to-student interactions (e.g., Hypothesis for social annotation or FeedbackFruits for peer review and feedback).
• Have students provide a reflective rationale for choices made throughout the completion of a class project (e.g., an artist statement, response to a reflection prompt about personal relevance of source selections)
• Have students connect course experiences/motivations to their own lived experiences.

Create Transparent Assignment Materials

Once you have thought about whether or not generative AI can be effectively incorporated into your assignments, it is important to create assignment materials that are transparent (Winkelmes, et al., 2019). Specifically, this means creating ways to communicate to students the task you are are requiring, along with its purpose and evaluative criteria:

• Task. Students will benefit from having a clear and accessible set of directions for the project or assignment you are asking them to complete. 
• Purpose. Students are often more motivated when they understand why a particular task is worth doing and what specific knowledge or skills they will develop by completing the assigned task.
• Evaluative Criteria. Students benefit from having a clear sense of how their work will be evaluated and a full understanding of what good work looks like.

Communicate Your Expectations for Generative AI Use 

Regardless of the extent to which you incorporate the use of generative AI into your assignment design, it is essential to communicate your expectations to students. Sharing clear directions for assignments, communicating how students can be successful in your class, and promoting academic integrity serves both you and your students well. 

Example Assignment Policy Language for Generative AI Use

The following language on the use of generative AI may be helpful as you create directions for specific assignments. Please note that the following sample language does not reflect general, course-level perspectives on the use of generative AI tools. For sample course-level statements, see AI & Academic Integrity .

Prohibiting AI Use for a Specific Assignment

Allowing the use of generative ai for a specific assignment with attribution.

For full details on how to properly cite AI-generated work, please see the APA Style article, How to Cite ChatGPT . "

Encouraging the Use of Generative AI for a Specific Assignment with Attribution

For full details on how to properly cite AI- generated work, please see the APA Style article, How to Cite ChatGPT ."

Confer with Colleagues

There is almost always a benefit to discussing an assessment plan with colleagues, either within or beyond your department. Remember, too, that CTI offers consultations on any topic related to teaching and learning, and we are delighted to collaboratively review your course assessment plan. Visit our Consultations page to learn more, or contact us to set up a consultation.

2023 EducaUse Horizon Report | Teaching and Learning Edition. (2023, May 8). EDUCAUSE Library. https://library.educause.edu/resources/2023/5/2023-educause-horizon-report-teaching-and-learning-edition

Antoniak, M. (2023, June 22). Using large language models with care - AI2 blog. Medium. https://blog.allenai.org/using-large-language-models-with-care-eeb17b0aed27

Dinnar, S. M., Dede, C., Johnson, E., Straub, C. and Korjus, K. (2021), Artificial Intelligence and Technology in Teaching Negotiation. Negotiation Journal, 37: 65-82. https://doi.org/10.1111/nejo.12351

Jensen, T., Dede, C., Tsiwah, F., & Thompson, K. (2023, July 27). Who Does the Thinking: The Role of Generative AI in Higher Education. YouTube. International Association of Universities. Retrieved July 27, 2023.

OpenAI. (2023, February 16.). How should AI systems behave, and who should decide? https://openai.com/blog/how-should-ai-systems-behave

Winkelmes, M. A., Boye, A., & Tapp, S. (2019). Transparent design in higher education 

teaching and leadership: A guide to implementing the transparency framework institution-wide to improve learning and retention. Sterling, VA: Stylus Publishing .

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Using AI tools

AI Writing Tools | Definition, Uses & Implications

AI writing tools are artificial intelligence (AI) software applications like ChatGPT that help to automate or assist the writing process. These tools use machine learning algorithms to generate human-sounding text in response to users’ text-based prompts.

Other AI tools, such as grammar checkers , paraphrasers and summarizers serve more specific functions, like identifying grammar and spelling mistakes or rephrasing text.

Table of contents

How do ai writing tools work, what can ai writing tools be used for, implications of ai writing tools, other interesting articles, frequently asked questions about ai writing tools.

AI writing tools (chatbots, grammar checkers, etc.) use natural language processing (NLP) algorithms, machine learning , and large language models (LLMs) to generate or improve written text. These tools are trained to identify patterns in vast amounts of data. The tools then use these patterns to analyze human inputs (or prompts) and generate natural-sounding outputs (similar to how predictive text works).

Different AI tools may be programmed in different ways. For example, ChatGPT, the popular chatbot developed by OpenAI and released in November 2022, uses generative pre-trained transformers (GPTs) and was trained using reinforcement learning from human feedback (RLHF) , meaning that the tool was given feedback from humans to help guide it towards the most helpful responses.

AI writing tools have a number of helpful applications. Some of these applications are discussed below.

Interactive learning and feedback

Generative AI tools can be helpful resources for conversational learning. By inputting questions, users can engage in interactive learning at any time.

You can also prompt these tools to provide feedback on your work to improve the clarity or consistency of your writing. However, it’s important not to upload sensitive information, as user inputs are generally saved by the tool for the purposes of training future models.

Below is an example of how ChatGPT can be used for interactive learning.

Example: Using ChatGPT for interactive learning

• Tell me three facts about Carthaginian culture
• Carthaginians were known for their maritime trade and commerce, and their navy was one of the strongest in the ancient Mediterranean world. They established colonies and trading posts throughout the Mediterranean, including in Sicily, Sardinia, and North Africa.
• Carthaginians had a polytheistic religion, and their chief deity was Baal Hammon, the god of fertility, agriculture, and the sky. They also worshiped a number of other gods and goddesses, including Tanit, the goddess of love, fertility, and war.
• Carthaginians were skilled metalworkers and produced a variety of metal goods, including weapons, armor, jewelry, and household objects. They were particularly famous for their bronze work, which was highly prized in the ancient world. Carthaginian bronze was so valued that it was used by the Romans to make their famous statues and other works of art.
• Tell me three more facts about the Carthaginian navy
• The Carthaginian navy was one of the most advanced and powerful navies of the ancient world. It was instrumental in establishing Carthage as a dominant power in the Mediterranean region.
• The Carthaginians were known for their skill in shipbuilding and developed a variety of ship types for different purposes, including warships, transport ships, and cargo ships. One of their most famous ship types was the quinquereme, a large warship with five rows of oars.
• The Carthaginian navy was led by a commander called the “admiral.” The admiral was responsible for overseeing the fleet and making strategic decisions about naval warfare. One of the most famous Carthaginian admirals was Hannibal Barca, who led the Carthaginian fleet during the First Punic War against Rome.

Generating research questions and outlines

AI writing tools can be used to generate potential research questions or research paper outlines . You can then refine the tool’s responses by further prompting it or directly editing the output yourself to ensure the result makes sense and fits your requirements.

Below is an example of how ChatGPT can be used to generate potential reseach questions and research method ideas.

Example: Using ChatGPT to generate research questions and methods

• Develop three possible research questions on the following topic: “The influence of technology on second language acquisition.”
• What is the impact of technology-assisted language learning (TALL) on the acquisition of a second language?
• How do different types of technology, such as mobile applications, virtual reality, and online platforms, affect second language acquisition outcomes?
• How do individual learner characteristics, such as age, proficiency level, and motivation, interact with the use of technology in second language acquisition?
• Suggest three quantitative research methods appropriate to the second question.
• Experimental research: This research method involves manipulating an independent variable (in this case, the type of technology used) to observe its effect on a dependent variable (second language acquisition outcomes). Participants would be randomly assigned to different groups using different types of technology to learn a second language, and then their language acquisition outcomes would be measured and compared.
• Survey research: This research method involves using questionnaires to gather data from a large group of participants. In this case, a survey could be designed to gather information on participants’ use of different types of technology to learn a second language, as well as their language acquisition outcomes. This would allow for a large-scale investigation of how different types of technology are being used, and what their impact might be.
• Correlational research: This research method involves examining the relationship between two or more variables. In this case, a correlational study could be conducted to investigate whether there is a relationship between the type of technology used and language acquisition outcomes. Data could be collected from participants using different types of technology to learn a second language, and then the correlation between the type of technology and language acquisition outcomes could be calculated.

Paraphrasing text

AI tools like ChatGPT and Scribbr’s free paraphrasing tool can help you paraphrase text to express your ideas more clearly, avoid repetition, and maintain a consistent tone throughout your writing.

They can also help you incorporate scholarly sources in your writing in a more concise and fluent way, without the need for direct quotations. However, it’s important to correctly cite all sources to avoid accidental plagiarism.

Summarizing text

AI writing tools can help condense a text to its most important and relevant ideas. This can help you understand complex information more easily. You can also use summarizer tools on your own work to summarize your central argument, clarify your research question, and form conclusions.

You can do this using generative AI tools or more specialized tools like Scribbr’s free text-summarizer .

Proofreading text

AI writing tools can be used to identify spelling, grammar, and punctuation mistakes and suggest corrections. These tools can help to improve the clarity of your writing and avoid common mistakes .

While AI tools like ChatGPT offer useful suggestions, they can also potentially miss some mistakes or even introduce new grammatical errors into your writing.

We advise using Scribbr’s proofreading and editing service  or a tool like Scribbr’s free grammar checker , which is designed specifically for this purpose.

Translating text

AI translation tools like Google Translate can be used to translate text from a source language into various target languages. While the quality of these tools tend to vary depending on the languages used, they’re constantly developing and are increasingly accurate.

While there are many benefits to using AI writing tools, some commentators have emphasized the limitations of AI tools and the potential disadvantages of using them. These drawbacks are discussed below.

Impact on learning

One of the potential pitfalls of using AI writing tools is the effect they might have on a student’s learning and skill set. Using AI tools to generate a paper, thesis , or dissertation , for example, may impact a student’s research, critical thinking, and writing skills.

However, other commentators argue that AI tools can be used to promote critical thinking (e.g., by having a student evaluate a tool’s output and refine it).

Consistency and accuracy

Generative AI tools (such as ChatGPT) are not always trustworthy and sometimes produce results that are inaccurate or factually incorrect. Although these tools are programmed to answer questions, they can’t judge the accuracy of the information they provide and may generate incorrect answers or contradict themselves.

It’s important to verify AI-generated information against a credible source .

Grammatical mistakes

While generative AI tools can produce written text, they don’t actually understand what they’re saying and sometimes produce grammar, spelling, and punctuation mistakes.

You can combine the use of generative AI tools with Scribbr’s grammar checker , which is designed to catch these mistakes.

Ethics and plagiarism

As AI writing tools are trained on large sets of data, they may produce content that is similar to existing content (which they usually cannot cite correctly), which can be considered plagiarism.

Furthermore, passing off AI-generated text as your own work is usually considered a form of plagiarism and is likely to be prohibited by your university. This offense may be recognized by your university’s plagiarism checker or AI detector .

If you want more tips on using AI tools , understanding plagiarism , and citing sources , make sure to check out some of our other articles with explanations, examples, and formats.

• Citing ChatGPT
• Best grammar checker
• Best paraphrasing tool
• ChatGPT in your studies
• Is ChatGPT trustworthy?
• Types of plagiarism
• Self-plagiarism
• Avoiding plagiarism
• Academic integrity
• Best plagiarism checker

Citing sources

• Citation styles
• In-text citation
• Citation examples
• Annotated bibliography

AI writing tools can be used to perform a variety of tasks.

Generative AI writing tools (like ChatGPT ) generate text based on human inputs and can be used for interactive learning, to provide feedback, or to generate research questions or outlines.

These tools can also be used to paraphrase or summarize text or to identify grammar and punctuation mistakes. Y ou can also use Scribbr’s free paraphrasing tool , summarizing tool , and grammar checker , which are designed specifically for these purposes.

Using AI writing tools (like ChatGPT ) to write your essay is usually considered plagiarism and may result in penalization, unless it is allowed by your university . Text generated by AI tools is based on existing texts and therefore cannot provide unique insights. Furthermore, these outputs sometimes contain factual inaccuracies or grammar mistakes.

However, AI writing tools can be used effectively as a source of feedback and inspiration for your writing (e.g., to generate research questions ). Other AI tools, like grammar checkers, can help identify and eliminate grammar and punctuation mistakes to enhance your writing.

You can access ChatGPT by signing up for a free account:

• Follow this link to the ChatGPT website.
• Click on “Sign up” and fill in the necessary details (or use your Google account). It’s free to sign up and use the tool.
• Type a prompt into the chat box to get started!

A ChatGPT app is also available for iOS, and an Android app is planned for the future. The app works similarly to the website, and you log in with the same account for both.

Yes, ChatGPT is currently available for free. You have to sign up for a free account to use the tool, and you should be aware that your data may be collected to train future versions of the model.

To sign up and use the tool for free, go to this page and click “Sign up.” You can do so with your email or with a Google account.

A premium version of the tool called ChatGPT Plus is available as a monthly subscription. It currently costs $20 and gets you access to features like GPT-4 (a more advanced version of the language model). But it’s optional: you can use the tool completely free if you’re not interested in the extra features.

ChatGPT was publicly released on November 30, 2022. At the time of its release, it was described as a “research preview,” but it is still available now, and no plans have been announced so far to take it offline or charge for access.

ChatGPT continues to receive updates adding more features and fixing bugs. The most recent update at the time of writing was on May 24, 2023.

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Generative AI in your assignments

Can i use generative ai tools in my assignments.

Some subject coordinators may explicitly include information in your assessment guidance as to whether these kinds of tools may be used and how.  You must comply with the requirements of the assessment task – if you are unsure, check with your lecturer.

Tools such as AI chatbots can be helpful to explain concepts in different ways – this may help you to understand difficult concepts in your course.  Tools like ChatGPT can also potentially help you to think about an initial structure for an assignment: for example you might ask for section headings for a document based on your own notes, as a way to get started. 

In some cases, your lecturer may ask you to use ChatGPT or other generative AI tools as part of the assessment.  If this is the case, make sure that you understand how you are expected to use the tool and which parts of the work are expected to be your own original work.  If you are unsure, ask you tutor or lecturer for clarification. 

It is important to remember that when you submit an assignment or other assessment, you are taking responsibility for the content, and claiming it as your own work.  Whilst generative AI tools can be useful for helping you to understand a topic or structure your thinking, using them to write substantial parts of your work for you (where this is not explicitly required as part of the assessment) is academic misconduct and may have serious consequences for you.

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Microsoft 365 Life Hacks > Everyday AI > 5 tips to write better AI prompts

5 tips to write better AI prompts

Generative AI has the ongoing ability to provide the answers and results that you need, but since it depends on what is being looked for, it’s only as good as the prompts that you give it. Discover some tips on how to write strong AI prompts and frame your questions so you can get the most out of these advanced tools.

What are AI prompts?

An AI prompt functions as a conversation starter. The instructions and requests that you input into the text window of an AI tool will determine the result that you get. These results depend on the word usage and phrasing of your prompts, the length and specificity, and any context you can provide it.

Because AI is so open-ended, writing and honing the most accurate prompt can seem nearly limitless. The more that you familiarize yourself with AI tools, the more that this open-endedness will seem beneficial.

Tips for crafting an effective AI prompt

There are no limits to an AI prompt; it can be as simple as a phrase or include multiple detailed paragraphs. However, if you want results tailored to your needs, these tips can inform your inputs:

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Determine your goals

What kind of answer are you looking for: a to-do list and a schedule, a few bulleted points of advice, or a fully formed passage that fits a certain style of writing? The way you frame a prompt shapes the AI tool’s output.

Write simply and directly

Be clear and concise when you frame your question or request, without adding extraneous details that might steer AI into an unwanted direction. Be sure to ask AI for one task at a time, otherwise you might get jumbled results.

Be specific

Relatively few AI-generated answers are one-size-fits-all, so it’s important to add any details that relate to your life or your needs. For example, if you’re asking AI to create a fitness plan , tell the tool your goals and timeframe, your current mobility and strength levels, and other details that work specifically for you. Ask open-ended questions. Instead of relying on true/false answers, ask for pros and cons.

Add necessary context

Context is key for tailoring AI results to your exact needs. If you’re asking AI for recipe advice , add some helpful context. For example, are you throwing an Italian dinner party for your closest friends, one of whom is gluten-free? Be sure to mention this so that your response can be better personalized to what you’re looking for. This strategy is especially helpful for generating specific writing projects such as party invitations, postcards , or other ways for assisting with creative endeavors.

Expand on details

If you want more information on an aspect of your AI-generated results, ask away! Perhaps a question about vacation activities mentions outdoor hiking, which might pique your interest. Or the fitness plan involves kettlebells, a fitness routine you’re unfamiliar but interested in. You can ask a follow-up question while preserving your initial results.

AI isn’t perfect, nor can it read your mind; therefore, you might not get the result that you need or that you want to use the first time you try. Refine your AI prompts or start over from scratch, if necessary.

No matter what your everyday task is, you can get the most out of AI by using strong prompts—especially when you expand and add context. Check out more everyday AI tips to enhance your daily routine.

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Understanding Threshold Concepts to Design Assignments and Courses

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Resources for Teaching Writing

Course & assignment design.

• Examples of Effective Writing Assignments
• Scaffolding Writing to Support Student Learning
• Creating Assignments for Miami Plan Capstone Courses
• Teaching Literature Reviews
• Using Threshold Concepts to Design Assignments and Courses
• Teaching Grammar Rhetorically 
• Structuring Purposeful Group & Team Work
• Mentoring Graduate Writers

Feedback & Assessment

• Using ePortfolio Assignments 
• Giving Feedback to Writers
• Facilitating Meaningful Online Discussions
• Engaging Students in Effective Peer Response

Teaching Online and with AI

• Providing Online Writing Support
• Integrating AI to Guide Learning

Threshold concepts are the core knowledge and disciplinary capabilities that students must successfully transition through to make progress in their majors. The threshold concepts (TC) framework is the guiding framework of our signature Faculty Writing Fellows Program , which supports faculty members in teaching students to write more effectively in their disciplines and professions and to use writing in ways that encourage deep learning of disciplinary material. The TC framework is useful in helping make visible disciplinary conventions that have become tacit over time, and in helping identify where students might get “stuck” in the learning process and where best to intervene.

In this resource, we unpack the TC framework in an effort to help you think through how it might help in classroom planning and assignment design. Check out our Composing Meaningful Writing Assignments resource for more on how to bring ideas related to threshold concepts into pedagogical practice. 

Summary of the Threshold Concepts Framework

Threshold concepts are foundational concepts a learner internalizes as they come to fully participate in a discipline. They are akin to a “portal” that unlocks "a new and previously inaccessible way of thinking about something" (Land et al., 2005, p. 53).  These disciplinary concepts are defined collaboratively when experts from fields come together to name what they know, and—like disciplinary knowledge—these concepts are ever-changing.

Some examples of threshold concepts include:

• “Opportunity cost” from the field of Economics (Davies & Mangan, 2007)
• “Change through space and time” from the fields of Earth and Environmental Science (Ryan, 2014)
• “All writers have more to learn” from the field of Writing Studies ( Adler-Kassner & Wardle, 2015 )

Research on threshold concepts began as part of a 15-department professional development project led by Dr. Erik Meyer and Dr. Ray Land at the University of Durham, UK from 2001-2005. Meyer and Land found that individual disciplines have unique ways of thinking and knowing and, therefore, unique challenges for teaching their students. From this original study, researchers across the globe have studied the TCs of their own disciplines and implications for student learning.

From research on threshold concepts, we know that they are:

• Transformative. TCs significantly shift how students perceive the required work process and product of their discipline/s and how they must perform as a member within that field. Access to these ways of knowing and doing occurs over time and thorough engaged participation.
• Integrative. TCs reveal the interconnectedness of the discipline when students connect together ideas from between and among what they had previously believed to be unrelated aspects of their studies.
• Troublesome. TCs provoke “rupture[s] in knowing” in which students untangle intellectual uncertainties (Schwartzman, 2010, p. 38).
• Bounded. TCS reflect ways of knowing within specific disciplines; however, these are the threshold concepts that meaningfully inform how we teach across the disciplines, such as those from writing studies.
• Irreversible. TCs change how students think and approach problems, to the extent that it is difficult to revert back to a previous way of understanding.

Additionally, when students wrestle with threshold concepts, they pass through differing stages of liminality based upon their experiences and learning.

Source: (Land, Meyer, & Baillie, 2010, p. xii)

How to Use Threshold Concepts as the Basis for Course and Program Design

While threshold concepts are not to be confused with learning outcomes, they can serve as the basis for course and program design. 

One helpful approach is for an instructor to identify threshold concepts for a specific course and then work backwards from that threshold concept to design major course assignments, smaller course activities, requited scaffolding, etc. (refer to our backwards design worksheet for more guidance). Sometimes, it helps to start with the big picture and work backwards down to the smaller, more specific components. 

For an entire program, it could help for faculty to work together to identify the various threshold concepts they wish for students to learn throughout their program and identify which courses can address which threshold concepts. This mapping could be broken down to whether the threshold concept is a major focus, a moderate focus, or a minor focus. The act of mapping a curriculum in this manner can help a program see where some threshold concepts and other course concepts might overlap, and also identify where a program might need more information (for example, if students take courses in another department).

Please see this curricular mapping spreadsheet for more guidance on how you might map your curriculum in this way. This framework is adapted from Chris Anson at North Carolina State, and it’s been used with other curricula at Miami. 

Threshold Concepts at Miami

Over 190 faculty members have completed our Faculty Writing Fellows Program , and have innovated their writing instruction to in part help teaching the various TCs in their disciplines and programs.

The Disciplinary Writing Guides on our HWAC website directly build from the work of former Fellows. See how a few of them have identified threshold concepts and integrated them in to assignment and course design:

• Art History 
• Gerontology
• Philosophy  

Additionally, Miami faculty members have published about threshold concepts and curricular work, including 22 alumni who published chapters in HWAC staff members’ edited collection Changing Conceptions, Changing Practices: Innovating Teaching Across Disciplines . The faculty authors in the collection share their experiences teaching threshold concepts in their courses and across their programs, describing their approaches and also the very real challenges they have faced and the types of larger-scale change they aim to create.

We provide further reading in the next section, but wanted to note here the important role threshold concepts play in so many programs and courses across Miami. There’s so much generative potential with this framework, and we invite you to apply for Fellows to learn more yourself by participating in the full program.

Further Reading

• Adler-Kassner, L., & Wardle, E. (Eds.). (2015). Naming what we know: Threshold concepts of writing studies. University Press of Colorado.
• Anderson, C., & Day, K. (2005, November). Subject overview report : History. Report from the Enhancing Teaching-Learning Environments in Undergraduate Courses Project. University of Edinburgh.
• Davies, P., & Mangan, J. (2007). Threshold concepts and the integration of understanding in economics. Studies In Higher Education, 32(6), 711-726.
• de Medeiros, K., & Kinney, J.M. (20200. Writing like a gerontologist for The Gerontologist. The Gerontologist, 60(5), 793-796. 
• Donald, J. (2001). Learning to think: Disciplinary perspectives. Jossey-Bass.
• Elon University's Center for Engaged Learning. Threshold concepts: Student and faculty perspectives .
• Entwistle, N., McCune, V., & Hounsell, J. (2002). Approaches to studying and perceptions of university teaching: Learning environments: concepts, measures and preliminary findings . ETL Project Occasional Report.
• Flanagan, M. (2017). Threshold concepts: Undergraduate teaching, postgraduate training, professional development and school education: A short introduction and bibliography . University College of London.
• Glotfelter, A., Martin, C., Olejnik, M., Updike, A., & Wardle, E. (Eds.). 2022. Changing conceptions, changing practices: Innovating teaching across disciplines . Utah State University Press.
• Land, R., Meyer, J. H., & Flanagan, M. T. (Eds.). (2016). Threshold concepts in practice. Springer.
• Land, R., Meyer, J. H. F., & Smith, J. (Eds.). (2008). Threshold concepts within the disciplines . Sense Publishers.
• Meyer, J., & Land, R. (2003). Threshold concepts and troublesome knowledge: Linkages to ways of thinking and practicing within the disciplines . Occasional Report 4: Enhancing Teaching-Learning Environments in Undergraduate Courses Project.
• Meyer, J. H. F., & Land, R. (2006). Threshold concepts and troublesome knowledge: Issues of liminality. In J. H. F. Meyer & R. Land (Eds.), Overcoming barriers to student understanding (pp. 19-32). Routledge.
• Meyer, J. H. F., Land R., & Baillie, C. (2010). Threshold concepts and transformational learning. Sense Publishers.
• O'Mahony, C., Buchanan, A., O'Rourke, M., & Higgs, B. (Eds.). (2014). Threshold concepts: From personal practice to communities of practice: Proceedings of the National Academy's Sixth Annual Conference and the Fourth Biennial Threshold Concepts Conference .
• Ryan, A. M. (2014). Seeing deeply in space and through time: Interdisciplinarity meets threshold concepts in Earth and Environmental Science.
• Schwartzman, L. (2010). Transcending disciplinary boundaries: A proposed theoretical foundation for threshold concepts. In R. Land, J. Meyer, & C. Baillie (Eds.), Threshold concepts and transformational learning (pp. 21-44). Sense Publishers

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