
Artificial Intelligence in Learning & Teaching

In late 2022, generative artificial intelligence (AI) tools such as OpenAI’s ChatGPT (OpenAI, 2022) became a part of the mainstream with many exploring its capabilities and inspiring curiosity regarding similar tools and their capabilities (OpenAI, 2022). In higher education, this has sparked fresh conversations, led to many questions, and created the need to pivot to consider these new tools in our learning and teaching (Luckin et al., 2018). Two of the biggest questions have been:
- How do these tools fit into the classroom?
- What do educators need to know to navigate this new era?
This page is dedicated to providing information about AI in learning and teaching to help you make the best decisions about the use of AI in your courses and to learn more about these new tools and technologies.
What is Artificial Intelligence?
Generative AI is a type of artificial intelligence that can create new content, like text, images, video, or music, that looks and sounds similar to what humans would produce. It learns patterns from existing data and uses that knowledge to generate new output.
Artificial Intelligence (AI) is technology that enables computers to perform tasks that usually require human
intelligence (Russell & Norvig, 2021). Users engage with these tools through prompts,
allowing them to direct the tool’s responses. Generative AI refers to AI tools that create new content, like text, images, video, or music, that
looks and sounds similar to what humans would produce. It learns patterns from existing
data and uses that knowledge to generate new output. This includes tools like ChatGPT and Microsoft CoPilot. Try out the following to explore the capabilities of these AI tools: To learn more about how to use AI tools to improve your workflow and enhance your
instruction, consider attending our Generative AI Crash Course workshop session! Efficiency: AI has the potential to enhance what its users are capable of. Some of the ways that
generative AI tools can help instructors is by assisting in the development and modification
of lesson plans, rubrics, assessments, case studies, summaries, reports, outlines,
tables, revisions, graphics, audio, and more. With a well-developed prompt, various
tools can develop the resources above often in a matter of seconds to minutes (Luckin
et al., 2016). Concept Exploration: Users across disciplines can use generative AI to assist in brainstorming, investigating
a topic, exploring alternative perspectives, and/or jump-starting an email (Luckin
et al., 2016). Learning Support: As a learning tool, students can interact in real-time with generative AI tools to
get immediate feedback and support. With that said, AI is not a substitute for instructor-student
or student-student interaction but can be an effective tool when those types of interactions
are not possible. Career Skills: Currently, there has been an increasing demand for individuals equipped with the
knowledge and skills to create AI programs, critically assess AI technologies, collaborate
effectively with AI, and leverage it as a tool in various capacities in the workforce.
This will likely only expand as AI tools are utilized more in the workplace (Luckin
et al., 2016). Inaccuracies / Bias: AI tools such as large language models and image generators are trained from data
that exists on the internet including digitized materials, online discussion boards,
and other human-generated sources. As a result, the outputs that AI tools generate
can contain misinformation as well as reflect views of racism, sexism, ableism, violence,
stereotypes, and more that were “learned” from what is published on the internet (Bender
et al., 2021). Academic Dishonesty: The rise of AI tools has made generating written content and other forms of content
more efficient and easier. It is not always easy to determine if work is generated
by AI or not and AI generators have been found to not only be unreliable but in some
cases biased (Jobin et al., 2019). Privacy: Not all AI tools offer protected versions that safeguard data. In most cases, it
is safe to assume that information shared with AI tools may not be private and there
is a risk that data can be exposed. It is important to consider this as well as speak
to your students about this privacy issue when using AI tools (Jobin et al., 2019). Intellectual Property: Since AI tools learn from what is available on the internet, there have been challenges
with copyright and intellectual property. Users in creative fields such as artists,
writers, and publishers have challenged AI developers in court since their copywritten
material is often used to train AI programs often without permission (Metz, 2023). Unethical Labor Practices: In many cases, research suggests that there are reports of unsafe and unfit labor
conditions that human workers who provide feedback to train AI models face on a daily
basis. (Crawford & Joler, 2018) Carbon Footprint:As AI tools continue to evolve, they will require the use of more energy compared
to traditional Google searches and other online tasks that we are used to. This can
impact emissions in a negative way and make the task of lowering emissions for companies
that are planning to use AI often a significant challenge (Strubell et al., 2019).
If you suspect that a student might have used generative AI for their assignment,
having a conversation with them is a great initial approach. Additionally, due to
privacy concerns, it’s advised not to upload student work to other AI detectors without
their consent.
Using AI in Learning and Teaching
AI tools are transforming education, presenting both exciting possibilities as well as unique challenges. For educators, this means finding ways to reflect on AI use and redesign course content to address unauthorized AI usage while also exploring how these tools can enhance learning and teaching. This section offers practical strategies to minimize unauthorized AI usage as well as provide suggestions on how to incorporate AI into your courses in meaningful, ethical, and engaging ways.
While there are many different approaches to address unauthorized AI usage in the
classroom, we often recommend embracing AI as well as rethinking and redesigning assessments
to reduce the chances of AI misuse. The following are some approaches to minimize unauthorized AI usage: To learn more about how to redesign your assessments to minimize unauthorized AI usage,
consider attending our Generative AI in Higher Education: A Deep Dive Into Assessment Redesign workshop session! AI tools can be helpful to instructors in many ways. The following are some of the
way that AI tools can be used to inform and improve instruction: Develop Learning Objectives: AI tools can help in the development of new learning objectives or to rework existing
learning objectives. AI tools can also provide feedback on how to align learning objectives
to course learning goals (Luckin et al., 2016). Develop Multiple Choice Questions: AI tools can help in the development of multiple choice questions or to provide feedback
on existing multiple choice questions. They can also generate answer choices and distractor
choices for these questions. Brainstorm Lesson Plan Ideas: AI tools can help instructors develop lesson plans as well as brainstorm ideas for
lesson plan enhancement such as developing engaging lesson hooks, discussion topics,
providing real world examples, and more. They can also provide feedback on how to
improve existing lesson plans (Luckin et al., 2016). Creating Rubrics: AI tools can draft rubrics for a course assignment based on details provided such
as assignment directions and learning objectives. They can also provide feedback on
existing rubrics and suggest how they can improve. Some tools such as Microsoft CoPilot
will even export rubrics to Excel / Sheets formats for further editing. Class Activities: AI tools can help to suggest ways to enhance class activities such as provide options
for gamification, suggest scenarios, serve as a role play partner, act as peer-reviewer,
develop multimedia aligned to the lesson, and more. To learn more about how to use AI tools to improve your workflow and enhance your
instruction, consider attending our Generative AI Boot Camp workshop session!
Understanding Student Usage of AI
Students may turn to AI tools for many reasons. Understanding these motivations is an important step in having open and meaningful conversations about AI in the classroom. In this section, you’ll find tips for talking with students about AI, advice on creating AI-related syllabus statements, and guidance on how students can properly cite and acknowledge AI in their work.
It is important to discuss your policies on AI usage in a clear and unambiguous manner.
Including an AI statement in your course syllabus and reviewing this with students
at the start of the course helps to begin the AI discussion. It can also be helpful
to outline which assignments allow for the use of AI tools and which assignments do
not permit the usage of AI tools (Selwyn, 2019). The following document, created by Lance Eaton, Senior Associate Director of AI in Teaching and Learning at Northeastern University,
offers examples of AI syllabus statements tailored to different levels of allowance
across a variety of academic disciplines. This resource can serve as a valuable guide
when crafting your own AI syllabus statements for your courses. When establishing
your policy, it’s crucial to communicate this decision with your students and, as
mentioned earlier, include reminders about AI usage in your assignment instructions
as well. In addition, our Graduate School has developed a policy regarding the usage of Generative
AI which can be found on the Graduate School Bulletin. For more information on developing syllabus statements and communication expectations,
please visit our Course Syllabus: Language and Policies page. Much like us, students have varying experience, knowledge, and opinions of AI tools.
Some students are exploring these tools for the first time and others are using AI
tools for various purposes including editing and revision of writing, coding, math,
citations, and even everyday uses such as cooking, shopping, and more. This is an
important consideration to make when developing AI guidelines for your courses. The following are some recommendations for discussing AI with your students: Properly citing AI tools has become more of a common practice as AI tools continue
to develop further and evolve. Since many students are at different levels of familiarity
with using AI tools, providing instructions on how to do this in your syllabus as
well as on assignments where it would be necessary can be helpful for students. Citing AI Content: Any AI-generated content that is quoted, paraphrased, or otherwise incorporated into
a student’s work should be cited including AI-generated images, media, and other visual
content. Some AI tools also make their interactions shareable, which can be included
as a link or URL. Currently both MLA Style Center: How do I Cite Generative AI in MLA Style? and APA Style: How to Cite ChatGPT provide further guidance on how to cite generative AI in MLA and APA formats (MLA
Style Center, 2023; APA Style, 2023). Acknowledgment of AI Assistance: If students are using AI tools to assist them with different learning activities
such as research and composition, it is important that they know where and how to
document this usage. This could be in the form of an acknowledgment section, methods
section, notes section, or another format that has been previously discussed with
the students. Review AI-Generated Content: In many cases, AI tools can develop biased, illogical, or false information and even
can generate sources that do not exist. This can be due to where the AI tool is pulling
information from, the wording of the prompt that was submitted, and/or other reasons.
It is important that anyone who makes use of AI tools to generate content reviews
its output for accuracy. As the use of artificial intelligence tools in academic writing continues to grow,
faculty should take a proactive and fair approach when evaluating AI-flagged student
work. One important precaution instructors can take is to explicitly require students
(as prat of the course syllabus) to keep a time-stamped copy of all their drafts,
in either Google Docs or Word or whatever format the student is using to construct
the document. This is for the student's protection and could serve as "proof" that
their document was not entirely AI-generated. To further ensure fairness and accuracy in evaluating AI-flagged papers, faculty
can follow the Next Steps for AI-Flagged Paper Flowchart. This guide was created in collaboration with the Stony Brook University Academic Integrity
Judiciary Committee. Best practices include carefully reviewing AI detection reports,
cross-referencing flagged content with course guidelines, engaging students in discussion
about their writing process, and documenting findings thoroughly. It can help faculty
make informed decisions that uphold academic integrity while supporting student learning. As part of an AI^3 Seed Grant for a faculty development and student support program
focused on maintaining the integrity of writing-to-learn assignments while fostering
innovation in the age of AI, Dr. Shyam Sharma, Principal Investigator from the Program
in Writing and Rhetoric, Dr. Rose Tirotta-Esposito, Co-Principal Investigator and
Director of the Center for Excellence in Learning and Teaching, and Co-Principal Investigator
Dr. Christine Fena from the University Libraries, collaborated with faculty, students,
and CELT staff to create these modules to help students build writing-to-learn skills
alongside critical AI literacy. This course empowers college students to develop critical AI literacy while enhancing
their writing skills. Students will learn how to ethically and responsibly integrate
AI tools into their academic writing, fostering a deeper understanding of AI's role
in education. Through interactive lessons and practical exercises, participants will
explore strategies to use AI as a supportive tool rather than a replacement for critical
thinking. By the end of the course, students will be equipped to navigate the challenges
and opportunities of AI in academic contexts, ensuring their writing remains authentic
and impactful. If you would like to request the set of student modules to integrate into Brightspace
and link to your gradebook, please fill out the Student Module Request form. After completing this form you will receive a ZIP file with the Articulate Rise
student modules and instructions for Brightspace integration. CELT is also available
for consultations. You can also share the set of student modules directly by sharing: Fostering Writing-to-Learn Skills with Critical AI Literacy for Students
References:
Since AI is rapidly changing and evolving, it is important to continue to learn about these tools and developments within AI that can impact our personal and professional lives. If you would like to learn more about AI, the sources below can be a great start!
Definition of Artificial Intelligence and Generative AI AI Capabilities in Learning and Teaching Liang, W., Yuksekgonul, M., Mao, Y., Wu, E., Zou, J.. GPT detectors are biased against
non-native English writers. Patterns, 2023; 100779 DOI: 10.1016/j.patter.2023.100779 Ethical Concerns and Risks of AI Gebru, T., et al. (2020). Algorithmic Justice League: Addressing bias in AI. Retrieved fromhttps://www.ajl.org AI in Education and Career Skills Equity, Accessibility, and Carbon Footprint Concerns Syllabus Policies and Pedagogical Guidance Addressing AI in Student Conversations Research on AI-Generated Content Verification
OpenAI. (2022, November 30). Introducing ChatGPT. OpenAI. Retrieved fromhttps://openai.com/blog/chatgpt
Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson Education.
Luckin, R. (2018). Machine Learning and Human Intelligence: The Future of Education for the 21st Century. UCL Press.
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
(pp. 610–623). ACM. https://doi.org/10.1145/3442188.3445922
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An Argument for AI in Education. Pearson Education.
Crawford, K., & Joler, V. (2018). Anatomy of an AI System. AI Now Institute.
Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and policy considerations
for deep learning in NLP. arXiv preprint arXiv:1906.02243.
Association for the Advancement of Artificial Intelligence (AAAI). (2023). Guidelines for the use of AI in educational settings. Retrieved fromhttps://aaai.org
Citing Generative AI Tools (MLA and APA Guidance)
MLA Style Center. (2023). How do I cite generative AI in MLA Style? Retrieved fromhttps://style.mla.org
American Psychological Association (APA). (2023). How to cite ChatGPT. Retrieved fromhttps://apastyle.apa.org
Selwyn, N. (2019). Should Robots Replace Teachers? AI and the Future of Education. Polity Press.
Metz, C. (2023). AI detects its own mistakes – or does it? The New York Times.
Additional AI Resources
Past Panel Discussions
Trends and Tips: Assessment in the Classroom (2/2/23): Assessment PowerPoint | Assessment Recording | Assessment LibGuide | Assessment Blog Post | Assessment Chat Resources
Trendends and Tips: AI Bots in Your Classroom-A New Era of Teaching and Learning (4/11/23): AI Bots PowerPoint | AI Bots Recording | AI Bots LibGuide | AI Bots Chat/Breakout Room Resources
Embracing AI, Preserving Integrity: Navigating the Generative AI Challenge (9/8/23): Preserving Integrity PowerPoint | Preserving Integrity Recording
Exploring Generative AI in Teaching and Learning: A Student's Perspective (11/20/23): Student Perspective PowerPoint | Student Perspective Recording
Chat Conversations with Chat GPT (thanks to Kristen Slovak!):
Past Workshops
Generative AI in Higher Education: A Crash Course for Faculty and Staff (2/15/24): Crash Course PowerPoint | Crash Course Recording
Generative AI in Higher Education: A Deep Dive Into Assessment Redesign (2/29/24): Deep Dive PowerPoint | Deep Dive Recording
Generative AI Boot Camp: How Can AI Make Your Life as a Professor Easier? (3/28/24): PowerPoint | Recording

