AI Text Generators: Resource Page

Stearns Center Recommendations:
Strategies for Teaching Well When Students Have Access to Artificial Intelligence (AI) Generation Tools 


Recent advances in Generative-AI tools have resulted in broad worldwide access to “chatbots” and other online sites that can produce extended pieces of writing, artwork, and/or code, some at the level of mid-range college student competencies, in response to a very wide range of topics or questions.  This technology is not perfect, but it is also not going away, and it will continue to directly impact how we teach and how students learn. Moreover, the tools, their uses, and their effects on teaching and learning (and professional responsibilities) will continue to evolve. Your students currently have access to these tools, and the few who don’t know about them yet will know soon. 

It's important to view Generative-AI programs as tools that can be used for a range of purposes, including activities that support learning as well as interfere with learning. You might think, and ask students to think, about how similar tools have changed the work of your field and thus the skills and abilities that educated professionals need, over the past decades:

  • Multifunction calculators
  • Spelling and grammar checkers
  • Website generators
  • Statistical analysis software
  • 2D and 3D design software
  • High-powered imaging tools

The arguments in your field for "doing something by hand" vs. using a tool that enhances some individual abilities -- both in a learning situation and in a professional context -- are likely to be relevant to conversations about AI text generators.

Want to talk more? Register for one of our Fall 2023 AI in the Classroom seminars or learning communities via our Event Calendar. 

Communicate Your Course Policies About Gen-AI

Basic Academic Integrity Policy Statements

All faculty should identify one or more recommended statements to use regarding academic integrity and Generative-AI programs. These should be designed to complement or amplify a broad statement about general academic integrity. Your statement may, and likely should, vary depending on the course.  Departments, academic units, or programs are encouraged to help faculty create consistent and relevant statements.

Basic Academic Integrity Statement sample: 

 Mason is an Honor Code university; please see the Office for Academic Integrity for a full description of the code and the honor committee process. Three fundamental principles to follow at all times are that: (1) all work submitted be your own, as defined by the assignment; (2) when you use the work, the words, or the ideas of others, including fellow students or online sites, you give full credit through accurate citations; and (3) if you are uncertain about the ground rules on a particular assignment or exam, ask for clarification. No grade is important enough to justify academic misconduct. 

Generative-AI addendum, baseline: Use of Generative-AI tools should follow the fundamental principles of the Honor Code. 

Generative-AI addendum, expanded: Use of Generative-AI tools should be used following the fundamental principles of the Honor Code. This includes being honest about the use of these tools for submitted work and including citations when using the work of others, whether individual people or Generative-AI tools. 


Generating a more complete and accurate explanation of your goals and policies will take more time.

Since use of Generative-AI tools is likely to vary across disciplines, programs, courses, and even assignments, Stearns Center strongly recommends that faculty provide an addendum that fully articulates for students their policy about using tools like ChatGPT in their course. Academic units can also provide important leadership in this area. However, a one-size-fits-all statement is inappropriate.  

Faculty and leaders in academic units may use the chart below to identify language that should be used. Individual faculty should consult their academic unit or program leadership as they compose statements for their courses. 

  • REQUIRED: Core policy language that explains the instructor's or program's particular stance on the use of Generative AI.  
  • RECOMMENDED: Transparency statement that identifies faculty’s use of related tools to evaluate student work
  • OPTIONAL: Expanded language on reasoning 
  • OPTIONAL: Expanded language on discipline or course 
  • OPTIONAL: Expanded language on ethics & access  

Please adapt these statements to the particular needs of a field, program, or course. See the next section for more information on communicating about the overall ethics and accessibility of Generative-AI tools.

For more suggestions about course policies, we recommend Dr. Lance Eaton’s evolving crowd-sourced collection of sample policies here.

Course Policy
on Generative AI
Sample core policy
Transparency about
policy enforcement
Potential expansionDiscipline- or course-
specific addendum
No useAll work submitted in this course must be your own original work; use of AI writing tools, such as ChatGPT, are prohibited in this course and will be considered a violation of academic integrity. All academic integrity violations will be reported to the office of Academic Integrity.Student work may be analyzed using an originality detection tool focused on Generative AI tools. Original work is required in this course to meet its learning objectives. Work produced by Generative AI is not original work and will not aid in the learning process for this course.
The learning objectives for this course require students to demonstrate skills and practices that they can reliably perform without supplemental tools.
In order to do the higher-level work in X field, you need to understand/apply fundamental concepts and skills without the use of AI tools. Practicing without the use of these tools will aid in learning.
Some useWhen explicitly stated by the instructor, Generative AI tools are allowed on the named assignment. Students will be directed if and when citation or statement-of-usage direction is required. Use of these tools on any assignment not specified will be considered a violation of the academic integrity policy. All academic integrity violations will be reported to the office of Academic Integrity. Some student work may be analyzed using an originality detection tool focused on AI tools. Generative AI detection tool use will be revealed when the assignment directions are provided to students. Use of Generative AI tools will sometimes be in alignment with the learning outcomes for this course; when meeting the outcome requires original human action, creativity or knowledge, AI tool use would not align with the stated course goals. There will be times in X field that use of AI tools will be needed for you to do well at the job and there will be times where you will need to be able to do the work without support from these tools. This course aims to provide you with experience in the real-world scenarios that you may encounter once you leave the university.
Unlimited useStudents may use Generative AI tools whenever they believe it would be useful to their learning of course material. Students will be directed if and when citation or a statement-of-usage is required. All academic integrity violations will be reported to the office of Academic Integrity. Student work will not be submitted through originality detection software focused on AI tools because the utilization of these types of tools is expected.Although you are unrestricted with your use of Generative AI tools, you will be responsible for any incorrect, biased, or unethical information that is submitted, and your assignment grade will reflect the inclusion of any material that is incorrect or offensive.
Additionally, you must be transparent with your use and identify when the tool was used.
Use of these tools will likely be very commonplace in X field and gaining experience in the ethical and efficient use of these tools will help you in your professional life once you have left the university.
Required useThis course will require the use of Generative AI tools for some (or all) assignments and assessments. Therefore, the use of these tools when instructed will not be considered a violation of academic integrity. Students will be directed if and when citation or a statement-of-usage is needed. Non-directed or unethical use may be a violation of Academic Integrity and so be reported to the office of Academic Integrity.Student work will not be submitted through detection software because the utilization of these types of tools is expected.
Detection software may be used for assignments where using Generative AI tools does not align with the course learning objectives.
Work produced with the aid of Generative AI is not without risk. You will be responsible for any incorrect, biased, or unethical information that is submitted and you must be transparent with your use even on assignments where you are required to use Generative AI. The use of Generative AI will be a crucial set of skills that you will need to have a successful career in this field.
Entry level jobs in X field will require sufficient knowledge and experience with prompt engineering [or other AI skills that are relevant to your field I.e., coding].

Generative-AI Detection Tools and Other Ethical Issues

"Detection" Tools

Stearns Center recommends skepticism about tools or programs that indicate a reliable way of detecting whether text, artwork, or code is fully or partially generated by an AI tool.

  • Problems with detection technology: Note that there are some technologies existing and more on the way that will claim to be able to "detect" writing from an AI text generator, but using them remains problematic in many ways:
    • These may provide some feedback to instructors, but they are unlikely to be anywhere near a foolproof tool. (See this video of a faculty member experimenting with a flawed detector as just one example among many.)
    • For a thorough explanation of the principled reasons and technical limitations that make relying on any kind of "AI detection" tool problematic, see University of Rochester professor Whitney Gegg-Harrison's overview here.
  • Problems with detection as a core teaching approach: Chasing after "cheating" students, particularly as technologies continue to develop additional capabilities, is a losing game. Stearns Center continues to recommend that faculty invest their time now in alterations to their courses, messaging, assignments, and support structures to encourage and enable students to engage in meaningful assessments of their learning.

In addition, we recommend that faculty generally avoid actions that over-prioritize "catching/preventing cheating" while placing undue stresses on equity, accessibility, and innovative thinking:

    • Requiring handwritten submissions places additional burdens on students, especially those with some physical disabilities
    • Adopting intensive surveillance tools or processes -- such as requiring all steps of writing to be done under human and technological supervision -- is likely to produce few gains while limiting students' thinking and introducing additional biases and inequities into the learning process
    • Planning out systems to personally "recognize" "original" writing, either through eyeballing and comparing in-class samples to take-home samples by the same student, or by using an external text-evaluation tool, are likely to cause more problems than solutions, since all of these approaches are subject to bias and error that may reduce equity without significant gains in integrity


Concerns & Limitations Regarding Ethics and Access 

Departments, academic units, or programs can help clarify how faculty should or may communicate about the challenges inherent in course-use of Generative-AI tools.  For instance, instructors should consider both access and privacy issues:

  • While there are some free Generative AI programs, some do require paid subscription for access. Assignments should be designed to ensure equal access for all students.  
  • Use of some Generative AI programs requires accounts, and these programs may track or retain student input. Some students may not wish to create an account using their personal information, or to submit their original work to a Generative-AI program. Faculty should provide alternatives for students who may not wish to create personal accounts. 

Sample statements to students (and/or faculty) about limitations, concerns, ethical quandaries posed by Generative-AI tools. 

Generative AI tools have limitations: they currently have the tendency to hallucinate (create incorrect statements and provide fake citations), create inaccurate code, and provide offensive images or examples. They have been trained on limited sources that may contain biases and create biased output. The use of these tools creates other ethical quandaries: the algorithms rely on work done by other humans and do not give credit to their sources, and the algorithm adjustments are often completed by workers who may not be fully compensated for their labor and emotional stress. Lastly, reliance on these tools may stifle your own creativity and impede the learning process. Your decisions to use Generative-AI tools should always take these limitations into account. 

Currently there are some unknowns about who owns the right to the materials used with Generative AI tools -- including original student work that is submitted to a Generative-AI program. If you do not wish to risk (or give up) the rights to your intellectual property, you should consult with your instructor.  


General Teaching Suggestions

For your current courses, you should take some basic steps. Additional resources and examples follow this list. 

  • Learn: Familiarize yourself with the kinds of text that AI tools can generate.
    [Note: We recommend not using language that suggests that AI tools “compose” or “write” texts; they are algorithms assembling words and producing text in using a prescribed data set.] 
    • See a brief explanation of how AI text-generation works here or here. 
    • See examples of AI-produced text in response to a prompt here and here (content disclaimer:  the second link is a public social media thread with examples). 
    • Try an AI text-generation tool out for yourself here or here. 
    • Read about the limitations of “AI Text Detection” tools here and here.
    • Consider some of the implications for teaching: There’s a great short IHE article here.
  • Provide clarity: 
    • Prepare and make time to communicate directly with your students about the ethics and risks of using AI text generators for assignments in your class. In addition to concerns about “cheating,” you should address the learning value that you intend for students to gain from completing your assignments without AI assistance. (See some sample syllabus statements below.) In addition, you may want to provide models for students that show the kinds of inaccuracies, falsehoods, or incomplete responses that AI text generators will produce for questions relevant to your field.
    • Articulate your policies for addressing issues of academic integrity with regard to students who turn in work that has been produced by a machine.
  • Consider adapting some of your assignments to increase the value of tasks where students do the work without AI assistance and to limit the opportunity for AI assistance to meaningfully contribute to student success. 
    • Increase the specificity of your question or task: For example, rather than an open-ended writing prompt (“compare X and Y”), ask for specific information or examples (ask students to expand on one point discussed in class, create a scenario and ask for specific resources/sources, or provide an extended reading and have students critique/analyze it) 
    • Require the application of key concepts to specific local cases, problems, or contexts: For example, provide students with a reading and ask them to analyze and expand on the topics or issues in order to focus the students’ thoughts and responses on that paper, example, or case study. 
    • Require inclusion, citation, and direct response to specific course texts: For example, prompt students to cite the textbook or another reading in class, in addition to X number of additional sources that they find in Y database in your field. 
    • Require proposals, drafts, and revisions.  Multiple, sequential stages of a larger assignment can be useful to help students scaffold their understanding as well as help them produce their own content. For example, credit/noncredit activities can be integrated for topic development (and you can provide time in class on this or with paired peer activities). Low-stakes activities can be useful for writing out outlines of papers (for grading, these can be completion/noncompletion or similar). Peer reviews and iterative development, particularly when combined with a short  (one-paragraph) reflection on what changes were made as a result of a first submission or peer review help students continue to frame and develop their learning. 
    • Shift grading criteria, especially for formative writing such as discussion boards or drafts, to place additional value on how students respond to and/or integrate ideas or feedback from their peers or from you. For example, integrating more specifics in discussion prompts (see above), then having students make peer comments and respond to each other, will help continue the conversation and allow students to develop their thoughts on the topic more fully. 
  • Consider adopting activities that include AI text generation as a sample, starting point, and/or opportunity for critique-and-revision
  • Continue learning about AI text generation in higher education settings
    • Begin to explore what "competency" will mean in your field/profession: In 2025 or 2030, as AI tools continue to expand, what do you imagine will separate "average" professionals in your field from leaders in the field? What will experts be expected to have memorized, to do "by hand" without tools, to do quickly in one try? What kinds of complex problems will they need to address using all the tools available? Mason students should be learning (and being assessed on) high-value skills.


Consider upcoming issues for educators and students

Individually, within your academic unit, and/or with colleagues participating in Stearns Center events, keep exploring the larger questions raised by these new tools, such as:

  • What is "original" student work, and when do we most want it, and for what (educational/growth/ethical) purposes?
  • What will students need to do to be “good writers” as educated professionals, as AI text generators continues to gain facility in generating accurate and relevant text?
  • How are current AI text generators in a "free" mode likely to progress toward a for-profit approach, and how will that affect students and young professionals?
  • How can AI text generators be used to support inclusion and equity in higher education?
  • How can responsible writers incorporate the use of AI text generators going forward? For instance, would giving citations and building further or editing the content be sufficient?  Are there any “baseline” uses for composing early drafts? 
  • How can faculty shift their use and assessment of student writing to continue to encourage students to use writing for learning, communication, and documentation of their thinking?  
  • What kinds of privacy and accessibility concerns might be raised concerning AI text generators? 
  • What are the ways that bias and various “-isms” (for example, racism, sexism) appear in AI generated texts?  How do educators consider the potentials of hate speech? 


Additional resource pages for faculty

Additional resources will be added to this page as they become available. 


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