2.1 Our Changing Teaching Work
Every learning technology has affordances (or advantages) and constraints (or limitations). On the one hand, you may hesitate to incorporate AI into your teaching due to concerns about its ability to support learning, uncertainty about its effectiveness, or impact on students. On the other hand, the newness of AI technology, its potential risks, and the learning curve students face are frequently underestimated.
Mindset about AI and Education
The concept of a growth mindset, introduced by Carol Dweck, emphasizes the belief that dedication and hard work can develop abilities and intelligence. Dweck (2016) has highlighted potential misunderstandings and misapplications of this concept. For instance, encouraging effort without effective strategies or feedback can lead to frustration rather than growth.
In the context of AI in education, adopting a growth mindset involves being open to experimenting with AI tools and critically evaluating their effectiveness, learning from our experiences, and viewing challenges as opportunities for informed growth. Educators who adopt a growth mindset are more likely to explore innovative teaching methods, including AI, in ways that genuinely enhance their teaching and student engagement (Seaton, 2018).
Integrating AI into teaching practices in a mindful and measured way aligns with the principles of a growth mindset. By approaching AI with curiosity and a willingness to learn but also with some skepticism, faculty can experiment with different tools and applications to see what works best in their context. AI can save time on administrative tasks, inspire new teaching strategies, provide fresh perspectives on content delivery, and even assist with research. Viewing AI as a partner in the teaching process rather than a replacement allows educators to focus on the creative and relational aspects, where human judgment and empathy are irreplaceable.
Select the accordion items below to learn more about a growth mindset about AI in education.
Reflecting on Our Changing Work
When AI first became widely available, and it was clear that teaching work was changing, some authors sought to make sense of how faculty were feeling in response to these changes. Benjamin Bratton, in “The Five Stages of AI Grief ” (2024), uses a well-known grief cycle model to explain negative feelings about changes to education in the face of AI. Edward Maloney, in “The 4 Stages of AI” (2023) explains how responses to AI use can shift from “regulate” to “reimagine.”
Perhaps helpful for reflecting on our changing work is one quote from Bratton who, after describing the final stage of grief (Acceptance, or inevitability), provides an alternative approach, what he describes as non-grief:
“There are ‘non-grief’ ways of thinking through a philosophy of artificialized intelligence that are neither optimistic nor pessimistic, utopian nor dystopian.[…]. [I]t does not mean that humans are irrelevant, are replaceable or are at war with their own creations. Advanced machine intelligence does not suggest our extinction, neither as noble abdication nor as bugs screaming into the void. It does mean, however, that human intelligence is not what human intelligence thought it was all this time. It is both something we possess but which possesses us even more. It exists not just in individual brains, but even more so in the durable structures of communication between them, for example, in the form of language.”
Consider this fictional scenario and the reflection questions following:
Reflection Questions: AI and My Changing Teaching Work
Dr. Emilia Cartier, a faculty member at Conestoga College, has been teaching technical writing for over seven years. After the pandemic, Emily noticed that she felt tired and less energized. Rapid changes in educational technology and the pressure to adapt quickly have added stress.
With AI tools becoming more integrated into education, Emilia feels uncertain and hesitant about incorporating them into her teaching. Concerns about AI’s ability to support learning and its impact on students weigh heavily on her mind.
Emilia recognizes her challenges and acknowledges that every learning technology has benefits and limitations. Reflecting on these concerns, she also understands the importance of considering the potential of AI. She wants to reflect on her feelings, concerns, and the opportunities AI might bring to enhance her teaching methods and improve student learning outcomes without further stress and burnout. She also wants students to be ready for the 21st century workplace, which will increasingly use AI, but also wants students to have the foundational knowledge and skills required for success in the industry.
Emilia reflects:
- How do I currently perceive the role of AI in education? Do I see it as a tool, a partner, or a potential threat?
- What are my main concerns about integrating AI into my teaching practices?
- How can AI enhance my teaching methods and improve student learning outcomes?
- How can I ensure students are learning new AI skills but also recognizing the limitations of AI?
- What steps can I take to ensure that my use of AI aligns with ethical standards and promotes fairness and inclusivity?
- How can I stay informed about the latest developments in AI and its applications in education?
Getting Started with AI as an Aid to Your Teaching Work
As articulated by Jean Piaget (1972), constructivist learning theory posits that learners construct knowledge through experiences and reflection. This theory is applicable when you engage with AI in your teaching. By becoming more exposed to and interacting with AI tools, you are actively constructing new knowledge about how AI can grow your teaching practices, potentially leading to a deeper understanding and more effective teaching strategies.
EDUCAUSE’s 4Ds framework outlines key use cases for AI in education, focusing on four main areas to provide faculty support: Figure X. Four Generative AI Use Cases. From EDUCAUSE.
Caveats: Using AI at Conestoga
While the 4D framework provides some general ideas, it is important to use generative AI wisely and in keeping with Ontario and Ministry legislation. At Conestoga, this includes the following:
- Avoid using AI to grade student work
- Actively address ethical bias in AI tools
- Use transparency and consent to collect student data
- Review carefully automatic content creation
- Avoid following AI recommendations without human judgement
Please refer to the guidelines in the Sharepoint Site’s AI Do’s and Don’ts document and to Section 1.2 College AI Guidelines and Resources for more information.
Select the accordion items below to learn more about ways AI can help faculty enhance teaching and learning.
Learn More
Learn more about Uses of AI Chatbots in Education (Faculty Learning Hub).