Generative AI: Ban it or bring it on? One Professor’s Perspective

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By Michael Quartermain, Professor, School of Business

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Michael Quartermain, Faculty of Business

As I interact with other professors, one topic that is constantly discussed is ChatGPT (a generative AI language model developed by OpenAI). Is AI here to stay? What will we do about it? The discussions are of two minds: banning it in school institutions or looking at ways to embrace it as innovative technology. This is the BIG question

First, we should distinguish between predictive and generative AI (Coursera, 2024). Predictive AI focuses on forecasting future outcomes by analyzing historical data. It helps make informed decisions, mitigate risks, and identify opportunities. This seems easy to embrace as a positive tool, particularly from a business perspective. Generative AI creates new and unique content, such as text, images, videos, or audio, in response to user prompts. ChatGPT, Copilot, DALL-E, and Gemini are examples of generative AI tools. Generative AI is where our focus of discussion lies these days in education. 

“Ban it”

The argument for banning AI from our institutions could signal that the technology is feared, misunderstood, or questioned as a tool to support student learning. There are valid concerns that must be considered before implementing AI in the classroom: 

  • Increased plagiarism and cheating where generative AI tools can facilitate academic dishonesty. Students might misuse the technology to produce essays, reports, or assignments without effort. The ease of generating content could lead (or already have) to a surge in plagiarism cases, undermining the integrity of education (Ta & West, 2023). 
  • Weakening of critical thinking skills through reliance on generative AI might diminish a student’s ability to think critically, analyze information, and synthesize knowledge (Yeralan & Lee, 2023) 
  • Lack of accuracy, validity, and reliability of the AI content outputs; human oversight remains crucial to evaluate the quality of assignments and materials (Chan & Hu, 2023). 
  • Finally, the ethical implications of using generative AI in education are still largely unexplored and include questions about privacy, consent, and transparency (Chan & Hu, 2023). 

Despite these concerns, AI tools are becoming mainstream sooner rather than later. The implication is that the faster we learn to leverage AI as an educational tool, the better our courses will be. While this is yet to be proven true, I know I want to spend my time on something other than being a full-time investigator into which students used an AI generative tool and which did not in my course assessments.  

“Bring it on”

Another perspective suggests that, as educators, we must rethink our teaching practices to embrace this modern technology. We should turn our energy to ways to incorporate this modern technology into teaching practices. This might include turning to more inductive (versus the traditional deductive) learning (Huang, 2023). We could start looking at a flipped classroom to address concerns related to the new technology. The flipped classroom is an educational approach that reverses the traditional classroom setup. Instead of having lectures in class and homework at home, the lecture portion is done outside class, typically through pre-recorded videos or online resources.  

Class time is then used for interactive activities, discussions, and problem-solving, allowing students to apply what they have learned. The goal of the flipped classroom is to create a more engaging and practical learning experience. (Ozdamli & Asiksoy, 2016). Here is an example of how one teacher incorporated ChatGPT into a class assignment: 

Cherie Shields, a high school English teacher in Oregon, told me that she had recently assigned students in one of her classes to use ChatGPT to create outlines for their essays comparing and contrasting two 19th-century short stories that touch on themes of gender and mental health: “The Story of an Hour,” by Kate Chopin, and “The Yellow Wallpaper,” by Charlotte Perkins Gilman. Once the outlines were generated, her students put their laptops away and wrote their essays longhand.”  

Roose, 2023, n.p. 

By having students use AI for only part of the assignment, the teacher “flipped” the learning so that students got started quickly with their assignment, yet had to fill in the blanks with their own ideas.

We need both sides

There may be no black-and-white answer but a world of gray to sort through. There are several concerns that educational institutions may have when considering the use of generative AI: 

  • Using generative AI may create a dependency on technology for the student, potentially reducing a student’s critical thinking and problem-solving skills. 
  • Implementing and integrating generative AI into the curriculum may require significant technological, training, and time investments by institutions and educators. 
  • Concerns about the effectiveness of generative AI as a “teaching” tool, particularly in comparison to traditional methods and the student-teacher interaction that is crucial to the learning experience. 
  • Concerns regarding students’ overreliance on a single tool to develop a deep understanding of concepts and navigate the global world’s complexities. 

There are opportunities for positive outcomes as well:  

  • AI may aid in assessing student performance and providing immediate, personalized feedback to students. 
  • AI may be able to use numerous data points to help identify students who may be at risk. 
  • Virtual chatbots and assistants can support students and instructors with routine work, offloading cognitive effort. 
  • AI-driven tutoring systems, such as Intelligent Tutoring Systems (ITS), can adapt to individual student needs (Compton, Burke, 2023) 

These concerns and opportunities highlight the importance of carefully evaluating the use of generative AI in educational institutions and considering its potential impact on students, teachers, and the broader educational system. 

The decision to embrace or ban generative AI in the classroom must be based on a thoughtful review and consideration of its ethical, legal, and societal implications, which goes well beyond this brief discussion piece. As technological advancements steam ahead, doubling every 1.5 to 2 years (Moore’s Law), we must find a way to keep up as an institution!  Ultimately, educators and institutions must adapt–leveraging AI effectively and cautiously as these tools continue to evolve rapidly. 

References

Chan, C, K, Y & Hu, W. (2023). Technology in Higher Education Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational 20(43). https://doi.org/10.1186/s41239-023-00411-8 

Coursera (2024). Generative vs predictive AI: What’s the difference? Coursera Data.

Crompton, H., Burke, D. (2023). Artificial intelligence in higher education: the state of the field. Int J Educ Technol High Educ 20(22).

Ozdamli, F. & Asiksoy, G. (2016). Flipped classroom approach. World Journal on Educational Technology: Current Issues. 8(2), 98-105.  

Huang, L. (2023). Comparing the Deductive Method and Inductive Method of Grammar Teaching for Chinese Senior High School students. Journal of Education, Humanities and Social Sciences, 8. 229-237. 10.54097/ehss.v8i.4254.

Roose, K. (2023). Don’t Ban ChatGPT in Schools. Teach With It.New York Times.

Ta, R., & West, D. M. (2023). Should schools ban or integrate generative AI in the classroom?

Yeralan, S., & Lee, L. (2023). Generative AI: Challenges to higher education. Sustainable Engineering and Innovation 5. 107-116. 10.37868/sei.v5i2.id196.

Elan Paulson

Elan Paulson, PhD, has been an educator in Ontario's higher education system since 2004. Before joining Conestoga as a Teaching and Learning Consultant, Elan was on the executive team at eCampusOntario. She previously served as Program Director and as an instructor in professional education programs at Western University's Faculty of Education. With a Master's in Educational Technology, Elan specializes in technology-enabled and collaborative learning to support diverse learners. She has also conducted research on faculty participation in communities of practice for professional learning and self-care.

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