Tag: academic integrity

Chatbots in Higher Education: Benefits, Challenges, and Strategies to Prevent Misuse – Faculty Focus

Artificial intelligence (AI) platforms, especially chatbots like ChatGPT and Gemini, are influencing many areas of higher education. Students and instructors can interact with these tools to get real-time, personalized help with nearly any academic task at hand, including helping students study or revamping course content for instructors. There is no question that the educational potential is significant, but so too are the concerns about academic integrity and the consequences of students relying too heavily on these tools. While it’s important to weigh the pros and cons of chatbots, using the right strategies and technologies can help avoid those issues and still allow faculty and students to benefit from this burgeoning technology.

Use Cases for Chatbots in Higher Education Teaching

First, let’s consider uses among faculty. They can use chatbots to help improve most areas of teaching and learning while still saving time.

Chatbots can assist with different phases of course design, including writing learning objectives and developing and repurposing content. Chatbots can also be used in evaluating student performance data if your institution offers a secure chatbot (just be sure to anonymize the data). Instructors can also use chatbots to review the rules and instructions for their assignments and tests to identify vague or subjective text and suggest clearer, more objective wording. 

But one of the most impactful uses is adapting course content into formats that support students with different learning needs. Chatbots can adapt, simplify and organize text for students with learning or cognitive disabilities, generate alternative text for multimedia content, and they can even adjust their responses based on student emotions (for example, offering words of encouragement when a student is frustrated or discouraged).

Instructors may be tempted to use chatbots to grade written coursework as well, but for now, it is important to note that the technology still struggles with the nuances of grading and feedback. However, chatbots can still help by pulling out the main ideas and revealing whether a student’s essay meets basic criteria, which gives instructors a clearer starting point before reading.

You’ll see a lot of jargon and articles that make prompt writing seem complicated, but you don’t need to be an expert to write effective prompts. It’s a skill you can pick up quickly after a few tries, especially once you find what works for you and start creating your own templates to use in your courses.

Students and Chatbots: Finding a Balance

There are many ways that students can use chatbots to support learning while steering clear of misusing them for tests and assignments. Ensuring ethical and beneficial adoption of AI requires clear strategies and guidelines along with the right technology.

Improving Academic Performance

Recent research indicates that chatbots can improve learning and academic outcomes, but balance is key. When students rely on them too heavily, any benefits, like increased engagement, motivation and reflection are reduced or eliminated. When used appropriately, AI chatbots can tutor students to help them better understand and comprehend the information, which also increases engagement. Chatbots give students instant, personalized help with tasks such as summarizing content and checking grammar, and they also create a nonjudgmental space where students feel more comfortable asking questions.

Cognitive Load Reduction and Stress Management

Chatbots are ideal for offloading tasks such as summarizing a lecture transcript or highlighting key points in an assignment. With students under pressure to complete assignments, leaning on AI can also reduce stress and anxiety by giving them more time to focus on the important elements of an assignment. 

Similarly, chatbots can help students visualize information by generating charts, graphs or images to support their ideas. They can also provide adaptive support for students with disabilities or language barriers by reading, translating, simplifying or reformatting content to meet their needs. This reduces cognitive load, allows students to focus on the assignment itself and builds confidence in their ability to complete the work.

Strategies for Reducing Chatbot Misuse

Because of the speed and ease of use for chatbots, students may begin to use them as a shortcut to get work done instead of a supplemental learning tool. That’s a big issue. It bypasses critical thinking, contextual understanding and collaboration. This not only cheats the student out of learning but creates academic integrity issues for higher education institutions to address and stay ahead of.

Cheating is common in higher education, and with recent surveys indicating that more than 85% of students use AI daily to help with schoolwork, there’s a good chance of overlap. Students have mixed opinions when it comes to using AI for homework, with around 40% of students acknowledging that using AI for research and writing assistance should be acceptable, but there should also be limitations and ethical use.

Communicating with students about academic integrity codes of conduct, AI use, and cheating policies and ramifications are the first steps in setting expectations. But delivering assignments in ways that reduce opportunities for the use of chatbots or that lay out specific guardrails for chatbot use can also be helpful.

Reducing Chatbot Cheating

Cheating in higher education will never completely go away, and efforts to maintain and manage tools and channels used for cheating must be ongoing. As more students leverage chatbots for both approved and unapproved use, educational institutions can work to help students understand the appropriate way to leverage technology within the learning environment.

While educators struggle to detect AI use reliably, AI detection tools can identify unedited chatbot-generated content with reasonable accuracy. But their effectiveness drops when students edit or modify responses or use AI paraphrasing tools to rewrite the content. They’re more useful as a gut check, not definitive proof that the text was AI-generated.

Remote proctoring during assessments and written assignments adds another barrier to cheating. Ideally, the proctoring solution should leverage AI test monitoring together with live human proctors, which gives faculty the control to prevent AI use and the flexibility to allow approved resources. For example, instructors can proctor exams or essays by restricting access to all unauthorized websites and software, including chatbots, while still providing access to specific materials like case studies or tools like Word, Excel and Google Docs.

Another option is to use scaffolded, realistic assignments and assessments that focus on real-world application and requiring students to connect course content to their personal experiences or context. This makes it more difficult for chatbots to generate accurate or meaningful responses. For example, assessments could ask students to develop a scenario based on a local community issue, work on collaborative projects that include peer reviews or create video responses that reference specific class lectures or materials. This approach helps evaluate students’ true understanding of materials and that they are developing practical skills.

Set the Stage Now for an AI-Inclusive Future

AI chatbots are powerful tools that can make education more personalized, accessible and engaging. However, their misuse can undermine academic integrity and dilute learning. The solution, in most cases, isn’t to ban them outright, but to integrate them responsibly throughout teaching and learning processes. Striking this balance isn’t always easy, but it’s necessary to preserve the value of learning while preparing students for a future where AI will almost certainly be a part of their work.

Tyler Stike is the Director of Content at Honorlock and a doctoral student in educational technology at the University of Florida. In his role at Honorlock, he develops a wide range of content on online education, assessment, and accessibility. He is interested in how affective states influence learning and performance, and plans to research how AI can support adaptive learning experiences that help students manage those states.

References

W. Dai et al., “Can Large Language Models Provide Feedback to Students? A Case Study on ChatGPT,” 2023 IEEE International Conference on Advanced Learning Technologies (ICALT), Orem, UT, USA, 2023, pp. 323-325, doi: 10.1109/ICALT58122.2023.00100.

Strike, Tyler. “AI Prompting Examples, Templates, and Tips For Educators.” Resources for Education & Assessment, March 27, 2025, https://honorlock.com/blog/education-ai-prompt-writing/

Sánchez-Vera, Fulgencio. 2025. “Subject-Specialized Chatbot in Higher Education as a Tutor for Autonomous Exam Preparation: Analysis of the Impact on Academic Performance and Students’ Perception of Its Usefulness” Education Sciences 15, no. 1: 26. https://doi.org/10.3390/educsci15010026

Kelly, Rhea. “Survey: 86% of Students Already Use AI in Their Studies” Campus Technology, August 24, 2024 https://campustechnology.com/articles/2024/08/28/survey-86-of-students-already-use-ai-in-their-studies.aspx

McKearin, Cheryl. “Report on Student Attitudes Towards AI in Academia,” Learning Technology Solutions, April 5, 2024, https://learning.uic.edu/news-stories/report-on-student-attitudes-towards-ai-in-academia/

Kofinas, A. K., Tsay, C.-H., & Pike, D. (2025). The impact of generative AI on academic integrity of authentic assessments within a higher education context. British Journal of Educational Technology, 00, 1–28. https://doi.org/10.1111/bjet

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October 6, 2025
Bringing C.H.A.O.S to Chaos: Syllabi with an AI Usage Policy – Faculty Focus

It is no secret that Artificial Intelligence (AI) technology is transforming college classrooms. AI tools can easily and quickly assist students in various tasks such as essay writing, literature reviews, analyzing data, formulating code, solving equations, image generation, music composition, and so much more. With minimal or no effort, within minutes, students have most assignments, test questions, or discussion problems figured out and done…enter the chaos!

As educators, this means everything that we experienced in our own education and have worked years to develop is changing. We need to rethink our role, assignments, as well as formative and summative assessments of student learning all while AI capabilities change daily.

Through all this, we feel educators can take one concrete step to control the chaos by Communicating How AI Operates in the Syllabus (C.H.A.O.S). This article highlights the significance of AI usage policies and what elements should be considered in the policy. It also provides a few useful tips to implement AI policies.

Is there a need to specify the AI usage policy in the class syllabus?

Including an AI usage policy offers clarity to students regarding acceptable usage of AI tools. Although educators are making attempts to develop campus-wide consensus about AI tools, different sections of the same course may have different AI usage policies and practices depending on the instructor and their comfort level. When an explicit AI usage policy is stated in the syllabus, students (and faculty members) can be held accountable for upholding that policy. Any incidents of inappropriate AI usage or cheating can be dealt with within the framework of the policy mentioned.

What are the elements of an AI policy?

A clear AI usage policy needs to have at least three elements – acceptable use, citations necessary, and consequences of non-adherence to the policy. The first element, a well-formulated AI usage policy, specifies acceptable AI usage in learning processes, e.g. brainstorming and creating outlines. In the policy, it is beneficial to provide examples of unacceptable usage, e.g. using whole paragraphs of AI text or writing the whole essay. To develop the acceptable use portion, faculty need to take time and honestly reflect on how they see AI tools being integrated into classroom learning, career fields, and life in general. This can range from absolutely no AI usage to intentional integration of the tools in the classroom space. Your level of familiarity, acceptance of, and perceived value in AI will help shape what is allowed.

The second element is to determine how AI usage needs to be acknowledged and cited appropriately. Again, it is helpful to provide a sample citation as students may be unfamiliar with the norms of citations while taking initial undergraduate courses.

Furthermore, AI tools often include biases, inaccuracies, or sometimes hallucinations. Humans using AI tools, in this case students, need to be aware of these shortcomings and understand that even with proper citations they will be held accountable for not reviewing and verifying the accuracy of their work before submitting. So, the citation element in the syllabus must explain that the ultimate responsibility of academic rigor for the assignment submitted lies with the student.

The last element should outline information about how the instructor will deal with non-adherence to the policy. As an instructor, will you provide a chance for students to resubmit the work? Will the usage result in a loss of points, a zero for the assignment, or a failing grade in the course? How will AI usage be checked? How will you communicate it to students? What is the process and who is involved? These are a few questions that can help an educator shape their usage policy.

Implementing AI usage policy

A few additional steps can be taken when implementing an AI usage policy to make the process smoother. Given the varied nature of AI use policy in various courses, it would be helpful to have a classroom discussion early on (day 1) and throughout the semester with each assignment and exam. Researchers have suggested using a stoplight framework e.g., Red – No AI is allowed in this course; Green – AI tools are allowed and encouraged; and Yellow- AI is permitted for following activities only (Urbaczewski, 2025).

Regularly talking about AI usage may remove some of the pressure from students who want to express themselves through their essays or art and feel seen/heard but may be afraid that their grades will be poorer if they don’t use AI tools. Sharing stories of how past students have effectively, or ineffectively, utilized AI in their work can be helpful in mitigating inappropriate usage.

Another possible step is to introduce scaffolding in high stakes summative assignments such as end of the semester projects. Instead of a one-time submission worth 100 points, students could submit intermediate steps and include the prompts they may have used to get a response from AI tools such as ChatGPT or Perplexity. Some instructors may offer extra credit for such intermediate steps.

Unlike grading or attendance policies in the syllabus, AI usage policies will be dynamic. As AI technology advances, the definition of academic integrity may need to be revisited. Faculty members may need to revise this policy each semester and update it to ensure that students are meeting learning outcomes. As the educational landscape continues to evolve, remember you can get a handle on the chaos by introducing C.H.A.O.S to keep your syllabi in alignment with the current times.

AI Disclosure: AI tools such as Editor in MS Word were used for checking grammar and spelling. No AI tools were used for brainstorming or writing this article.

Simantini Karve, PhD, is a professor of biology and professional development co-coordinator at Skyline College, San Bruno, CA.

Jessica Hurless was a professor of Communication Studies and currently serves as the Dean STEM division at Skyline College, San Bruno, CA.

Reference

Urbaczewski, Andrew, “Developing a syllabus for is course usage in the ai era” (2025). Proceedings of 2024 AIS SIGED International Conference on Information Systems Education and Research. 16. https://aisel.aisnet.org/siged2024/16

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August 25, 2025
Bringing C.H.A.O.S to Chaos: Syllabi with an AI Usage Policy – Faculty Focus

It is no secret that Artificial Intelligence (AI) technology is transforming college classrooms. AI tools can easily and quickly assist students in various tasks such as essay writing, literature reviews, analyzing data, formulating code, solving equations, image generation, music composition, and so much more. With minimal or no effort, within minutes, students have most assignments, test questions, or discussion problems figured out and done…enter the chaos!

As educators, this means everything that we experienced in our own education and have worked years to develop is changing. We need to rethink our role, assignments, as well as formative and summative assessments of student learning all while AI capabilities change daily.

Through all this, we feel educators can take one concrete step to control the chaos by Communicating How AI Operates in the Syllabus (C.H.A.O.S). This article highlights the significance of AI usage policies and what elements should be considered in the policy. It also provides a few useful tips to implement AI policies.

Is there a need to specify the AI usage policy in the class syllabus?

Including an AI usage policy offers clarity to students regarding acceptable usage of AI tools. Although educators are making attempts to develop campus-wide consensus about AI tools, different sections of the same course may have different AI usage policies and practices depending on the instructor and their comfort level. When an explicit AI usage policy is stated in the syllabus, students (and faculty members) can be held accountable for upholding that policy. Any incidents of inappropriate AI usage or cheating can be dealt with within the framework of the policy mentioned.

What are the elements of an AI policy?

A clear AI usage policy needs to have at least three elements – acceptable use, citations necessary, and consequences of non-adherence to the policy. The first element, a well-formulated AI usage policy, specifies acceptable AI usage in learning processes, e.g. brainstorming and creating outlines. In the policy, it is beneficial to provide examples of unacceptable usage, e.g. using whole paragraphs of AI text or writing the whole essay. To develop the acceptable use portion, faculty need to take time and honestly reflect on how they see AI tools being integrated into classroom learning, career fields, and life in general. This can range from absolutely no AI usage to intentional integration of the tools in the classroom space. Your level of familiarity, acceptance of, and perceived value in AI will help shape what is allowed.

The second element is to determine how AI usage needs to be acknowledged and cited appropriately. Again, it is helpful to provide a sample citation as students may be unfamiliar with the norms of citations while taking initial undergraduate courses.

Furthermore, AI tools often include biases, inaccuracies, or sometimes hallucinations. Humans using AI tools, in this case students, need to be aware of these shortcomings and understand that even with proper citations they will be held accountable for not reviewing and verifying the accuracy of their work before submitting. So, the citation element in the syllabus must explain that the ultimate responsibility of academic rigor for the assignment submitted lies with the student.

The last element should outline information about how the instructor will deal with non-adherence to the policy. As an instructor, will you provide a chance for students to resubmit the work? Will the usage result in a loss of points, a zero for the assignment, or a failing grade in the course? How will AI usage be checked? How will you communicate it to students? What is the process and who is involved? These are a few questions that can help an educator shape their usage policy.

Implementing AI usage policy

A few additional steps can be taken when implementing an AI usage policy to make the process smoother. Given the varied nature of AI use policy in various courses, it would be helpful to have a classroom discussion early on (day 1) and throughout the semester with each assignment and exam. Researchers have suggested using a stoplight framework e.g., Red – No AI is allowed in this course; Green – AI tools are allowed and encouraged; and Yellow- AI is permitted for following activities only (Urbaczewski, 2025).

Regularly talking about AI usage may remove some of the pressure from students who want to express themselves through their essays or art and feel seen/heard but may be afraid that their grades will be poorer if they don’t use AI tools. Sharing stories of how past students have effectively, or ineffectively, utilized AI in their work can be helpful in mitigating inappropriate usage.

Another possible step is to introduce scaffolding in high stakes summative assignments such as end of the semester projects. Instead of a one-time submission worth 100 points, students could submit intermediate steps and include the prompts they may have used to get a response from AI tools such as ChatGPT or Perplexity. Some instructors may offer extra credit for such intermediate steps.

Unlike grading or attendance policies in the syllabus, AI usage policies will be dynamic. As AI technology advances, the definition of academic integrity may need to be revisited. Faculty members may need to revise this policy each semester and update it to ensure that students are meeting learning outcomes. As the educational landscape continues to evolve, remember you can get a handle on the chaos by introducing C.H.A.O.S to keep your syllabi in alignment with the current times.

AI Disclosure: AI tools such as Editor in MS Word were used for checking grammar and spelling. No AI tools were used for brainstorming or writing this article.

Simantini Karve, PhD, is a professor of biology and professional development co-coordinator at Skyline College, San Bruno, CA.

Jessica Hurless was a professor of Communication Studies and currently serves as the Dean STEM division at Skyline College, San Bruno, CA.

Reference

Urbaczewski, Andrew, “Developing a syllabus for is course usage in the ai era” (2025). Proceedings of 2024 AIS SIGED International Conference on Information Systems Education and Research. 16. https://aisel.aisnet.org/siged2024/16

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August 25, 2025
5 Steps to Update Assignments to Foster Critical Thinking and Authentic Learning in an AI Age – Faculty Focus

I recently attended a student panel on use of AI in college classes. The three panelists shared their perspectives, borne out in an April 2025 Gallup survey: they want to learn to use AI tools in appropriate ways, they’re anxious about the potential negative impact on their critical thinking skills, and they want explicit guidance from their faculty members—which they’re not consistently getting.

Even, or especially, in an AI age, we know our students need to think critically and learn authentically to be productive and engaged citizens and future employees. We recognize we need to update assignments to promote academic integrity in an AI age, yet many of us feel unprepared to do so. The crux of the problem is this: how do we foster critical thinking and authentic learning when it’s so easy for students to outsource their cognitive work?

One promising solution to the triple challenge of fostering critical thinking, meaningful learning, and academic integrity is to double down on transparency. We can provide the guidance students want, embed analysis and evaluation into our assignments to get at that all-important critical thinking, and nudge students toward integrity. How? By embracing transparency.

Let’s detail our expectations for responsible AI use. Let’s emphasize the why: why we want students to use their own cognitive abilities for some tasks, why using AI could be helpful at times, and why we’ve crafted our AI-integrated assignments in the ways we have. Finally, let’s ask students to disclose their use in full transparency (and reflect on their learning, as Marc Watkins argues here).

In short, we can promote integrity when assessments are meaningful, purposeful, and include transparent instruction on appropriate AI use. We can teach students to critically analyze AI-assisted work and promote authentic learning as we do. To help us achieve these aims, here are five steps to update assignments in ways that help students learn the skills they need while fostering a culture of academic honesty.

Step 1: Take a critical look at your current syllabus.

If you’re like me, you have tried-and-true activities and assignments that you’ve relied on for many years. Some of these may be updateable, but others may just need to go. If AI can easily complete a task (try running your instructions through a tool like ChatGPT to find out), maybe it’s no longer a relevant measure of authentic learning. Also, following the remaining steps below will likely mean that you add new instructional practices (like modelling AI use) and new components of the assignments you update (like a reflection on how AI helped or hindered learning). Make time for these important new course elements by getting rid of outdated tasks.

Step 2: Consider whether and how students should use AI on the assignments you keep.

Remember, students want to know exactly what is appropriate for AI use in your class. A helpful tool for this process is the 5-level AI Assessment Scale (AIAS). The levels range from No AI, AI Planning, AI Collaboration, Full AI, and AI Exploration. Each one identifies and sanctions different ways students can use AI in appropriate and meaningful ways to support their learning.

Leon Furze, one of the creators of the AIAS, presents it a tool that helps update our assignments and start conversations with our students. He recommends using this framework to guide your thinking: break down each assignment, project, or discussion board activity into disparate steps, then decide for which parts of the process AI use is appropriate. Providing transparent guidance, guidance that may vary for different parts of the project, is what students need right now.

Step 3: Carve out time to discuss and model your expectations.

Many students are not sure what is acceptable in this current moment. What better way to help them feel confident while developing the AI skills they need than modelling what you’re looking for? Take class time or record a video for your online class to teach your students what you expect them to do with AI for each assignment, what not to do, and what you’ll be looking for in their finished product.

As you approach this aspect of instruction, take heart. I don’t think every instructor needs to be an AI expert, but I do think we’re doing our students a disservice if we’re not teaching them how to be AI Whisperers, a concept I gleaned from Ethan Mollick’s 2024 book, Co-Intelligence. A new kind of expertise is emerging, he argues: the skilled and effective use of AI in every field. As disciplinary experts, you know what kind of AI use will help students learn your material and what will disempower them as learners. Let’s allocate time to help students develop AI literacy while maintaining their agency.

Step 4: Ask students to disclose their AI use, as noted above.

The student panelists showed palpable relief when they described instructors who simply had them cite their use of AI. “Encourage your students to be transparent about their AI use,” one student, a finance major, said. As she talked about how simple it was to add a line at the end of the assignment such as, “ChatGPT generated the outline for this essay,” the anxiety that had previously clouded her expression disappeared.

One approach is to use the AI Disclosure (AID) framework to document how students used AI, or add an appendix to each assignment, or add comments or footnotes to make transparent what they wrote and what AI wrote. Get students to declare their AI use and even better, ask them to reflect on whether their use helped or hindered their learning.

Step 5: If you suspect inappropriate use of AI, don’t accuse students of cheating.

Instead, have a conversation with them. Recall that a primary goal of the AIAS is to facilitate discussions about AI use. Imagine that as a class, you agreed that Level 2 (AI Planning) was appropriate for a particular project. If a student submits work that seems to have been completed at Level 4 (Full AI), refer back to the framework to facilitate a conversation about your perception of their work and their process. As AIAS co-creator Leon Furze points out, now you can get away from wondering whether a student cheated with AI and instead ask, “can I make a valid judgement of this student’s capabilities [whether they have used AI or not]?”

And as argued by the authors of a new book titled The Opposite of Cheating: Teaching for Integrity in an Age of AI, this takes moral accusation out of the conversation, reduces the adversarial tone, and enables students to reflect on and hopefully learn from the experience. You can also decide together what actions should take place next, whether the student resubmits the assignment in accordance with your AI-usage guidance, whether they lose the opportunity to earn a grade for that assignment, or whatever else you and your student decide is appropriate in that situation.

Students want to know how to use AI well. “If we don’t teach students how to use AI responsibly, they’re going to be poorly equipped for the workforce,” said the third student panelist, a computer science major. Let’s update our assignments to facilitate meaningful learning of our content, the skills students need in an AI age, and ethical, integrous use of AI to equip them for the workplace they’ll enter. In doing so, we’re helping to develop engaged citizens who think critically about information they encounter. I can’t think of more important work to be engaged in at this moment in time.

Flower Darby is an associate director of the Teaching for Learning Center at the University of Missouri, a co-author of The Norton Guide to Equity-Minded Teaching (2023), and the lead author, with James M. Lang, of Small Teaching Online: Applying Learning Science in Online Classes (2019).

References

Bertram Gallant, Tricia, and David A. Rettinger. 2025. The Opposite of Cheating: Teaching for Integrity in the Age of AI. University of Oklahoma Press.

Furze, Leon. 2024. “Updating the AI Assessment Scale.” August 28. https://leonfurze.com/2024/08/28/updating-the-ai-assessment-scale/

Furze, Leon. 2025. LinkedIn post. https://www.linkedin.com/posts/leonfurze_artificialintelligence-aieducation-assessment-activity-7295247135480889346-UWFC/

Kassorla, M. 2024. “Our New Course: Some Highlights.” January 4. https://michellekassorla.substack.com/p/our-new-course-some-highlights

McMurtrie, Beth. 2025. “AI Unready.” January 30. https://www.chronicle.com/newsletter/teaching/2025-01-30?utm_source=Iterable&utm_medium=email&utm_campaign=campaign_12441556_nl_Teaching_date_20250130&sra=true

Mollick, E. 2024. Co-Intelligence: Living and Working with AI. Portfolio.

Walton Family Foundation and Gallup. 2025. How American Youth View and Use Artificial Intelligence. https://www.gallup.com/analytics/658901/walton-family-foundation-gallup-voices-gen-american-youth.aspx

Watkins, Marc. 2024. “Make AI Part of the Assignment.” October 2. https://www.chronicle.com/article/make-ai-part-of-the-assignment?sra=true

Weaver, Kari D. 2024. “The Artificial Intelligence Disclosure (AID) Framework: An Introduction.” College & Research Libraries News 85 (10). https://crln.acrl.org/index.php/crlnews/article/view/26548/34482

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July 9, 2025
A Values-Based Approach to Using Gen AI – Faculty Focus

As a learning designer in a centralized teaching and learning unit, it’s my job to explore new technologies, particularly AI. But I’ll admit, I didn’t jump right in. As Generative AI (GenAI, a subset of AI that can produce content, ideas, and data by learning from existing data and patterns) has become prevalent, so have a wide range of concerns about its usage: authenticity, critical thinking, bias, representation, plagiarism, and sustainability, to name a few.

For a while, I felt paralyzed. How am I supposed to make decisions about this emerging technology that I don’t fully understand? But scholars like Maha Bali reminded me that we need to engage with AI in order to discuss its implications and influence its outcomes. As leaders, educators, users, and creators, we have choices. So, here’s how I have been thinking through when and how I’m going to use GenAI in a way that aligns with my values.

I value originality.

I create original work as a learning designer, as well as personally as a writer and artist, and I don’t want GenAI to train on my work. If I use GenAI, I will use a proprietary tool from my university (e.g., CoPilot), a tool with a paid subscription (like ChatGPT Plus), or another tool that won’t use my work.

I value transparency.

Working in digital learning, I am a partner on academic content. I respect my instructors’ hard-earned expertise and original work, and I won’t use their work with GenAI tools without their permission. In addition, if instructors’ content appears on platforms that use GenAI, I will inform them where and how it is used. As GenAI use increases in our course development processes, I will discuss the advantages and disadvantages of using specific tools, and we will work together to decide whether and how GenAI will be applied.

I value collaboration.

I work with amazing instructors to create online courses and other digital learning experiences. With a team of experts, I guide instructors through the process of brainstorming, outlining, and developing academic materials that we organize into a guided, accessible experience. My teammates and I bring a broad range of skills to this complex work, and we collaborate to create unique and valuable learning experiences. GenAI can help us with parts of this process, but I won’t use GenAI to replace our work with material that lacks the rich human experience and expertise that informs effective teaching and learning.

I value scholarship.

Higher education centers on the exchange, synthesis, and development of ideas. We build on others’ work while crediting them for their contributions. We do this to support our arguments, demonstrate our scholarship, and contribute to an ongoing conversation. While I can use GenAI for research, I can’t depend on it to accurately quote or cite others. Therefore, I won’t assume what GenAI writes or cites is accurate, and I will do my own research. In addition, if I use AI in my work (or in collaborative work), I will cite it.

I value sustainability.

Estimates vary on how much energy GenAI uses, and it depends on what you’re using it for. We do know that simple text queries don’t use as much energy as generating images or video requires. Is it worth using GenAI to create an image of your dog as an astronaut, or a dress composed of hundreds of kittens? As much as I love cute animals, I will minimize using GenAI to create images or videos, particularly for nonessential tasks. Additionally, I will weigh the impact of saving significant time and energy on essential tasks against the potential sustainability costs.

I value critical thinking.

I don’t want the easy answer. I want the complexities, the nuance, the human experience that makes an article or study or creative work unique. I won’t rely on GenAI to create something simplistic, biased, or inaccurate. If I use GenAI, I will use it to generate ideas, answer simple questions, or create an initial outline or template. From there, I will edit and rewrite what it provides, checking for bias, representation, and accuracy. Further, I will advise instructors on how to guide their learners in taking a similar approach.

I’m far from an expert in GenAI, and it’s a moving target. But deciding how I will engage with it has given me some peace of mind in a chaotic, ever-changing world. My best wishes on your own AI journey.

Heather Hans, MLIS is a senior learning designer at Duke University. She is energized by learner-centered design, good UX, and expanding access. She enjoys travel, wildlife gardening, and pie.

References

Bali, M. (2024, June 16). What Can We Refuse in AI? Reflecting Allowed. https://blog.mahabali.me/pedagogy/critical-pedagogy/what-can-we-refuse-in-ai/

Hillier, M. (2023, February 20). Why does ChatGPT generate fake references? TECHE. https://teche.mq.edu.au/2023/02/why-does-chatgpt-generate-fake-references/

Brown University Library. (2025, February 5). Generative Artificial Intelligence: Citation and Attribution with AI Tools. LibGuides at Brown University. https://libguides.brown.edu/c.php?g=1338928&p=9868287

Nicoletti, L., & Bass, D. (2023, June 9). Humans are biased. Generative AI is even worse. Bloomberg.com. https://www.bloomberg.com/graphics/2023-generative-ai-bias/

Duke Learning Innovation & Lifetime Education. (2024, August 12). Generative AI and Teaching at Duke. Duke Learning Innovation & Lifetime Education. https://lile.duke.edu/ai-and-teaching-at-duke-2/

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June 11, 2025
Engaging Students in Meaningful Learning Experiences – Faculty Focus
Two years ago, I was invited to deliver a course at a prestigious management school abroad. Though hesitant at first, I accepted the opportunity to do what turned out to be one of my most rewarding teaching experiences. I taught a group of students unlike any I had taught over the span of my long teaching experience in diverse settings and institutions.

The students portrayed an exceptional level of behavioral engagement. This surprised me since I had never seen them before, and I was new to them. I had not had the chance to establish any social or emotional bonds with them. I could see them taking their own notes during the lessons, never asking me for my slides, a common practice among other students I have taught. They would work on the assigned tasks in class and use their time efficiently. Assigned homework was always completed without me having to send them reminders. When I gave a break during a session, many would open books and read until the class resumed.

It happened that my class was interrupted by the New Year’s one-day holiday. I asked the class after the holiday to think of a new year’s resolution, and to my surprise, a handful of students said that they intended to increase the number of books they would read in the coming year.

At the end of my visit, I left those students and went back home to my regular educational setting. I found myself reflecting on my own recent experience. In my setting, most teachers I work with grapple with the challenge of engaging their students in their learning; thus, they work hard on providing students with incentives and support to stay on tasks, contribute to their groups, and complete their assigned work. I know that many of those teachers designed very good learning experiences and tried to accommodate their students’ needs, yet they did not observe the engagement they hoped for.

This contrast raised several questions:
- What are we missing as educators when it comes to student engagement?
- Are the challenges related to the curriculum, the school, or the larger context extending beyond the school to the home and society?
- Is it the collective perception toward education a factor in fostering student engagement? Have educators and parents been able to help students understand the bigger meaning behind their school experiences and tasks?
- Have we been able to help them make the connection between these tasks and their reality?
- Has the system taken these into considerations when designing the educational curricula?
Talking about relating learning experiences to real life brings to my attention how this group of young management students integrated their academic knowledge with their online profiles. Many connected with me on LinkedIn, where I have been seeing them share deep reflections and insights from their studies. Although they are still in their early years of their university studies, they express their opinions and stand as though they are experts in their field. They report on activities they engage in related to what they study and reflect on what they encounter and experience. They provide bulleted lists of advice and practice. Reading their posts, I see these students already can foretell their placement in life after they graduate and are acting accordingly. This could be a reason why they embrace schoolwork and engage with it willingly.

I end with two incidents from my visit that resonate with me. For one of the assessments, I conducted an online, objective-type quiz, consisting mainly of multiple-choice questions. The class speed in which the students submitted their responses led me to think they had worked collectively on a WhatsApp group. When I raised this concern, one student who seemed offended assured me that they would not do such a thing. This claim was validated when I graded the final exam, a rigorous three-hour subjective type of exam. The class average was an impressive A.

The second incident was when I asked the class for feedback on my teaching, as I usually do towards the end of a semester. One student advised me: “Next time you teach here, be tougher on students. We are used to working hard, and we can handle it.” I had never heard of anything similar from a student; on the contrary I have students who often request reduced workload and extended deadlines.

Reflecting on this experience, I believe the following can be considered as main takeaways for educators:
- Design meaningful learning experiences: The type of learning experiences we design for our students should relate to their realities and be meaningful and to where the students see themselves later in life
- Recognize the multifaceted nature of engagement: Student engagement is not necessarily the product of the teacher’s efforts but a myriad of aspects including the curriculum, perceptions, school and culture.
- Allow students’ voices: Listening to the students’ voices provides us with a lot of tips on how we can improve the learning experiences for them and attend to what they think they need help with.
- Foster student accountability: There are ways to help students be accountable to their own actions and to behave responsibly towards their learning
- Cultivate academic integrity: academic integrity can be achieved effortlessly when students are interested in what they do and understand the positive impact of their learning on their lives.
Amal Farhat has experience in teaching and instructional coaching at K-12 schools and higher education. She has worked in the private and public sectors. Her interests mainly pertain to the development of professional learning communities through positive, constructive interactions among stakeholders of an institution. In higher education, she taught in the Faculty of Letters and Humanities and Faculty of Education. Additionally, she works as a teaching and learning specialist supporting faculty members with their teaching practices. Amal holds a PhD in education from the Doctoral Institute at Lebanese University, a counseling in pedagogy diploma from St. Joseph University, and is CAEL (Certificate in Advanced Education Leadership) certified from Harvard Graduate School of Education.
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May 2, 2025