GenAI in Teaching and Learning

In the spring of 2023, VCC published an institutional response to ChatGPT based on the GenAI landscape at the time. Since then, GenAI tools and the thinking and adoption around them have evolved very rapidly. We acknowledge that even as we adapt to these evolving tools, we are still in the process of constant flux, navigation, and examination around the values, uses and impacts of GenAI.

Note that due to privacy and accessibility concerns with third-party GenAI tools, students cannot be required to use these tools and alternatives must always be provided even if you do decide to engage your class with GenAI use.

What are some examples of GenAI tools and how do I access them?

As the pace of generative AI has developed rapidly, the number of tools has increased vastly since the public introduction of ChatGPT in November 2022. Tools are also being integrated into browsers such as Bing Chat with Microsoft Edge. Many new apps and tools have been built on the ChatGPT platform providing user-friendly interfaces to ask for input without the user having to be skilled at prompting. Examples of such tools include Roshi and Teachermatic, which assist educators in creating learning materials and lesson plans. More tools are starting to require paid access, though there are many that are still monetarily free to use.

As you explore the available tools, keep in mind the following:

• Do you need to create an account? If so, it may be worth using an account and email address that is not connected to your work/profession nor personal life. This is to maintain your privacy, as GenAI tools may collect data for its training. It is important to consider whether you want to submit text/data that contains personal information, whether your own or students’. It is worth avoiding the submission of personal data or original work.
• Do you need to keep a history of your chat/generated-content, so that you can refer back? If so, it is likely that you need to create an account.
• Is the tool available for where you currently reside? Note that not all tools are available worldwide.

Below is a list of commonly used tools in education as of November 2023.

According to VCC’s institutional response to ChatGPT, VCC’s academic integrity policy still applies to student work that uses AI tools. This means that VCC expects honesty, integrity, truthfulness and proper use of citation and references in the submission of course work. The institutional response also leans on the guiding principles from Dr. Sarah Eaton and Lorelei Anselmo’s work that among other things, emphasize that the “use of artificial intelligence for schoolwork does not automatically equate to misconduct” and that “artificial intelligence can be use ethically for teaching, learning and assessment”.

As faculty, we can provide clear direction to students so that their use of GenAI for academic work, does not violate the academic integrity policy.  Cornell University has created a series of good practices to engage with your students regarding the use of GenAI tools in relation to academic integrity, as well as strategies to promote academic integrity in the classroom. There are various ways tools can be used – for example students can use the tools for brainstorming, writing improvement, research or to act as a virtual tutor. So, clarity in your direction to students around appropriate tools and appropriate use of tools is important to support their learning success.

As we teach diverse subject matters and applied practice areas, we may not all be in the same mindset regarding the use of GenAI tools in education or have the same industry needs to respond to. Generative AI tools open up new possibilities for teaching and learning and ask questions at the same time, as to how the tools can be used justly, ethically, and critically. It is important to examine both perspectives in order to make decisions about whether and how we can use the tools in our classrooms.

According to Cornell University, generative AI can potentially be used by both faculty and students to: 

• Provide instant access to vast amounts of information quickly
• Aid diverse learners with different learning abilities, linguistic backgrounds or accessibility needs
• Accelerate exploration and creativity, spark curiosity, suggest new ideas and ways of thinking

Students might explore using generative AI to:

• Be more efficient with course work and tasks
• Help with studying
• Generate ideas for brainstorming
• Get further explanation of a topic a teacher is covering for class
• Improve their writing
• Get instant feedback
• Practice language skills in a safe environment

Faculty might explore using generative AI to:

• Act like a virtual teaching assistant that helps with answering student questions, provides clarification, or offers guidance when not in class
• Generate content and course materials including lesson plans, quiz questions, sample problems, or writing scenarios
• Assist in research tasks including analyzing large datasets, identifying patterns, and generating insights and research directions
• Write learning objectives, course descriptions, syllabi statements, or course policies

KPU has also listed some benefits of using GenAI tools here.

As we examine the benefits and possibilities opened up by GenAI in teaching and learning, we also need to consider some current challenges and questions.

Privacy and Data Collection

Generative AI relies on learning from large amounts of data in order to generate new content. This data can include work that has bypassed proper copyright processes and not been permitted by creators, such as novels, artwork, and music, as well as personal information which can be used to identify individuals. As instructors, we need to be mindful that we do not submit original work without permission (e.g., student essay) nor personal information. Another primary consideration is that due to the “black-box” nature of generative AI tools created by third-party companies, educational institutions are not yet able to conduct proper Privacy Impact Assessments on the tools. VCC cannot at this point, assess the impact of the data collected by the companies, for what purposes the data will be used nor who will have access to the data. As such, VCC states that students cannot be required to use the tools and that alternatives must always be provided. 

Equitable Access and Accessibility

There are free and differently priced models for generative AI tools. For example, ChatGPT have a subscription-based version that is more current and powerful than the free one. If you are encouraging students to use it, consider how your learning activities can be designed so that students are not disadvantaged if they are not using the paid versions of the tools. Students may also not have easy access to high-speed internet or tech devices, and that could impact their use of the tools. Consider options and alternatives that will allow students to meet learning outcomes without the use of the tools.

Keep in mind that accessibility principles and practices are still applied if and when using generative AI in your courses.  The generative AI tools themselves ought to be navigable to all students and be aligned with assistive technology for those who need it. However, with the exception of Bing Chat, most generative AI interfaces are not yet well designed for accessibility with assistive technology. If you are teaching a course to students using assistive technology such as screen readers and keyboard navigation, implementing these tools may be an accessibility risk. Offer options so that students are not required to use the tools. 

Perpetuation of Bias and Discrimination

Generative AI, being trained on large amounts of data, can reflect the bias, bigotry and discrimination found on the internet as a whole, which is then re-produced in the content it generates. Most generative AI's have been developed in the western world; therefore, they can also be culturally biased.

It is important to consider the prompts that we are inputting into the GenAI tool to attempt to reduce biased perspectives and perpetuate existing biases. It is also vital to vet the output before sharing with students to assess for accuracy and presence of bias. Likewise, if we choose to allow for GenAI use in our classes, it would be beneficial to encourage our students to use the tools with critical reflection and analysis. (KPU, 2023)

Chapman University provides an introduction to the places where bias can show up in AI as well as identify the types of bias that we can watch out for and apply critical analysis to whenever we are engaging with content  generated by AI.

Unreliable Generated Content

Generative AI will provide a response whether it has the information or not. If it does not have any information, it will generate believable inaccurate information to satisfy the prompt or attempt to give you the “best” though not necessarily the most accurate, answer (“AI hallucination”). Generative AI also tends to frame its responses to questions as absolutes, as though every question has a single correct answer. It does not have the discernment built-in to determine whether the content generated is based on fact or not.

For example, when both ChatGPT 3.5 and Perplexity were prompted to “Write me a bio about Jennifer Benson, a nurse in the 1950s in New York City. She was known for her pioneering work with the ethics of care. Make it only 100 words or less.”, the content generated was:

ChatGPT 3.5 Output

Jennifer Benson, a trailblazing nurse in 1950s New York City, left an indelible mark with her pioneering work in the ethics of care. Dedicated to compassionate patient advocacy, she challenged traditional medical norms, emphasizing the importance of empathy and human connection in healthcare. Jennifer's commitment to holistic care redefined nursing practices, earning her widespread respect. Her legacy endures as a beacon for future generations of healthcare professionals, reminding them of the profound impact that genuine compassion can have on both patients and the healthcare system as a whole.

Perplexity Output

Jennifer Benson: Pioneering Nurse in 1950s New York City

Jennifer Benson was a pioneering nurse in 1950s New York City, known for her groundbreaking work with the ethics of care. She challenged traditional gender roles and advocated for a more compassionate approach to patient care. Benson's work contributed to the development of care ethics, a feminist ethic that emphasized the importance of empathy and emotional connection in caregiving. Her legacy continues to inspire nurses and ethicists to prioritize the human aspect of healthcare. Benson's contributions have left a lasting impact on the nursing profession and the ethical framework of healthcare.

The sources used for the bio about Jennifer Benson, pioneering nurse in 1950s New York City, are as follows:

• • Jennifer Benson – Executive Director – Center of the American Experiment - LinkedIn
  • Jennifer Benson – American Experiment
  • Feminism and Feminist Ethics – Introduction to Philosophy – Rebus Press
  • Ethics in Human Biology: A Historical Perspective on Present Challenges – Annual Reviews
  • [PDF] Case Studies in Nursing Ethics

The issue above is that Jennifer Benson as a nurse during the 1950s in New York City did not exist, at least not in the way the output was generated. It is a made-up name, and the tools simply combine information and words from different and adjacent sources to create the bio. It is time-consuming for faculty, students, and librarians to check the sources to verify the accuracy of the content. This is especially true for references that is adjacent to or similar in some words to the content but is not directly connected. Note that while Perplexity (and Bing Chat) automatically includes sources, other tools may not.

It is important that we recognize that AI generated content represent a starting point that requires research, reflection, and thoughtful input. For example, the response given may help focus the direction of research but must not be taken as accurate or as research itself. In this, we need to be a subject matter expert and ensure AI-generated content is credible and reliable before distributing to students (unless inaccuracy is part of the assignment) or asking students to follow AI-generated procedures. It would be beneficial to Incorporate information and digital literacy training into the course and inform students that the content generated by AI may be biased and inaccurate. (KPU, 2023)

Digital and AI Literacy

While digital literacy is already part of an integrated framework in BC K-12 education, we are increasingly being faced with extending it to AI literacy in post-secondary education. As AI is finding its way more and more in everyday life, AI tools are also finding their way into workplaces, resulting in an expectation that graduates should have at least a basic understanding of AI to be able to interact effectively with the technology. As with moving towards a responsible and ethical use of GenAI, here are 7 ways to use GenAI in the classroom that helps with building AI literacy. Here is a sample lesson plan that you can adapt to facilitate discussions with your students about AI literacy.

Teaching Practice

When trying to determine whether to use generative AI tools in your teaching practice, it is helpful to consider the types of tasks you commonly do and your strengths and preference for each type. For example, you may really enjoy creating lesson plans that build upon your subject matter expertise and experience with interactive classroom activities. You may, however, find the task of generating discussion points/questions from textbooks/literature to be time-consuming. In this case, you may want to use a GenAI tool to summarize the literature and produce some discussion points. 

Due to privacy and data collection considerations, we encourage faculty to never upload student work for grading purposes.

Here is a chart that can help you decide:

Classroom

As with any technology or tool, it is important to weigh the pedagogical benefits versus the considerations and challenges in the context of course design and the alignment with learning outcomes. Ultimately, “learning outcomes should guide the knowledge and skills students will grain from the course and help determine the types and approaches to assessments and learning activities.” (Recommendations and Guidelines - Teaching Resources, 2023)

This sliding scale can help you inquire and decide whether and how to incorporate AI use in the classroom.

Here are some questions to consider:

• What is my own comfort level with using GenAI tools?
• How does my own teaching practice align with the use of the tools?
• How do I see my role in engaging with GenAI in the classroom? If you have never engaged with GenAI in the classroom or with students, consider starting small with one or two assignments to build confidence and literacy. Continue to foster ethical and critical thinking throughout the process.
• Are there any areas where the use of GenAI tools will be beneficial for students and their learning? Note that alternatives must be provided for students who do not want to use GenAI tools. Here are 101 Creative ideas on using AI in Education. 

If you decide to encourage or to allow the use of GenAI tools in the classroom, it is important to discuss with students the expectations, ethical considerations, role of the tools and their usage, and in which ways students can engage with them. The course syllabus is a good place to start this communication. You may also want to co-create a classroom agreement on the use of generative AI in the classroom. Here are two sample templates:

• Co-Created Class Use of GenAI Template 1
• Co-Created Class Use of GenAI Template 2

Regardless of whether you decide to use generative AI in your teaching practice and/or encourage its use in your class, it is likely that the tools themselves have found their way in, whether by students using them already or that the tools were used inadvertently through their integration on browsers and other apps. Therefore, it is important to address and discuss with your students all the considerations and reasonings for your decision, to ensure that learning outcomes are met and that students do not inadvertently violate academic integrity. You may also choose to co-create a decision with your students.

Here are some steps to addressing GenAI use in your class:

• Be clear in your course syllabus/student handbook about the use of GenAI. Here’s a course syllabus with sample language. If you are not changing your decision in the course syllabus, discuss with your students why the decision was made and provide clear reasoning within the context of the course, learning outcomes, assessments and learning activities.
• If you want to co-create a decision with your students, here is an example of a decision-making process.
• You may choose to co-create a classroom agreement on the use of GenAI. Here are two samples:
  • Co-Created Class Use of GenAI Template 1
  • Co-Created Class Use of GenAI Template 2

• Communicate clearly the VCC academic integrity policy and how you want students to cite and reference. You can facilitate discussions around how students see the use of generative AI with respect to academic integrity and how group/collaborative work will be handled. If you are already using generative AI in your own teaching practice to create learning materials, for example, model proper attribution/citation in the learning materials.
• Include the ethical and other considerations in your discussions. University of Technology Sydney has a checklist that you can adapt/use to help students use generative AI tools ethically and responsibly.
• Here is a sample lesson plan that you can adapt to discuss generative AI use in your class.

If you have decided not to allow GenAI use in your class, or want to mitigate AI use, here are some ways you can address AI generated content and adapt your assignments/assessments (Using AI to Co-develop Teaching materials):

• Choose non-text-based outputs – diagrams, podcasts, videos, screencasts, mind maps, presentations, etc.
• Do work in class – writing, discussion, panels, debates, problem solving.
• Break large assignments into smaller stages with peer review in class.
• Create authentic assessments.
• Have assignments incorporate reflection on in class discussion/activities.
• Have students generate in-class summaries of topics/concepts and then compare with AI and identify gaps.
• Plan for students to use AI – then critique work for biases, gaps, hallucinated resources, etc.
• Ask for personal connections with the content.

If you have decided to encourage GenAI use in your class, here are some ways you can incorporate it:

• UBC has suggestions for addressing AI that cover situations where you want to mitigate AI use, integrate it into your assignments or support students to use it in their own learning.
• Ethan Mollick’s 7 ways to use GenAI
• 101 Creative ideas on using AI in Education

If you have decided to include GenAI into your teaching practice (Using AI to Co-develop Teaching materials), here are some ways:

• Co-develop teaching materials with GenAI, including assessments and assignments.
• Co-develop rubrics, lesson plans, glossaries of terms, images, presentation slides, FAQ documents, etc.

As with the use of any new tool, technology, or pedagogical approach, and especially with the rapidly evolving landscape of generative AI, consider how you would consistently reflect and adapt both in the teaching practice and classroom-student experience sides. Consider factors such as how student learning has been impacted in relation to educational standards and learning outcomes, how your own teaching practice have evolved, any challenges that arose that require addressing and any curricular changes that may need to be made due to evolving workplace/employer/industry needs in your specific field.

This is an area that requires much consideration. VCC has specifically chosen not to purchase an institutional license for TurnItIn (or other text similarity detectors) in past discussions, for the following reasons:

• Fuels mistrust between student and instructor/institution
• Students may resent the assumption of guilt
• Private companies making profit (from student work and intellectual property)
• Privacy concerns
• Student consent (is it obtained?)
• Reliability of software (various studies shown here, here and here)
• Does not resolve the underlying cause of academic dishonesty
• Does not promote academic integrity or teach students about plagiarism

Laura Dumin, a Professor of English and Tech Writing, has written a thoughtful piece about the use of AI detection tools that includes some pertinent questions as to why we should or should not use these tools. Institutions such as UBC are generally discouraging the use of AI detectors such as TurnItIn. Likewise, the University of Toronto discourages the use of AI detectors due to privacy and ethical concerns (e.g. uploading student work) and the reliability of the tools themselves.

We encourage you to provide clear guidelines to students regarding academic integrity, use alternative and authentic assessment strategies and continue using traditional methods to address potential academic misconduct, such as meeting with students to discuss their assignment(s).

• The VCC CTLR Events Calendar often has links to courses from CTLR, BCCampus, and others.
• UBC’s Centre for Teaching, Learning and Technology often has events and workshops pertaining to generative AI.
• Microsoft and LinkedIn has a pathway for Career Essentials in Generative AI.
• Prompt libraries and resources:
  • Wharton School of the University of Pennsylvania (Dr. Ethan Mollick and Dr. Lilach Mollick), Assigning AI: Seven Approaches for Students with Prompts
  • AI for Education's well organized Prompt Library for Educators
  • Ethan Mollick's prompt library for instructor aides and student exercises
  • Coadaptive Labs Prompt & GPT Library (well laid out examples with creative ways to use generative AI)
  • Github Prompts for Students