^{Themes: Assessment, Engagement, Ethical challenges in using AI, How I’ve been using AI, Individual education plans (IEPs), Lesson planning, Special education, Teaching Strategies
Audience & Subject: General (All Grades)}

Introduction

Below, we explore the challenges and opportunities presented by the rise of AI in education, with a particular focus on the issue of academic integrity and AI-enabled cheating. We delve into the current landscape of AI usage in educational settings, discuss the potential misuse of AI tools by students, and share strategies for limiting AI-enabled cheating while embracing the benefits of this technology.

AI in Education: Exploring the Landscape

AI is increasingly being integrated into educational practices, offering new avenues for enhancing learning experiences and streamlining administrative tasks. From personalized learning platforms to automated grading systems, AI has the potential to revolutionize the way we approach education. However, as with any disruptive technology, it also presents new challenges we must address.

Challenges of Academic Integrity with AI

One of the most pressing concerns surrounding AI in education is the potential for student misuse, leading to academic integrity violations. With the advent of powerful language models like ChatGPT, there is a strong temptation for students to use AI tools to complete assignments or even impersonate themselves during online exams. The temptation then raises questions about the validity of assessments and the integrity of the learning process.

What is AI-Enabled Cheating?

AI-enabled cheating can take various forms, including:

• Using AI to generate essays, code, or other assignments and passing them off as one’s own work.
• Employing AI paraphrasing tools to reword existing content and circumvent plagiarism detection.
• Utilizing AI-powered online exam proxies to impersonate a student during online assessments.

Prothero (2024) took a deep dive into academic dishonesty, looking at several data sources. According to data from Turnitin—a plagiarism detection company—AI use was detected in approximately 10% of assignments reviewed in the past year, with 3% generated mainly through AI. Additionally, survey data from Stanford suggests that the percentage of students admitting to cheating has not increased significantly since the release of ChatGPT. The insight indicates that AI cheating is perhaps not as pervasive as we think.

Time to Rethink Cheating

The emergence of AI tools challenges traditional notions of cheating and raises questions about where to draw the line. Yet, nuances and complexities are involved in defining and addressing AI-enabled cheating. For example, Miller (2023) outlines some questions we should consider when determining if it is cheating when a student:

• Plugs a prompt into an AI and copies the response verbatim?
• Uses an AI to generate a response but then reads, edits, and adjusts it before submission?
• Creates multiple AI responses, selects the best parts, edits them, and submits the final product?
• Writes the main ideas and uses an AI to generate a draft and provide feedback for improvement?
• Consults the internet and AI for ideas but writes the assignment content independently?
• Writes the entire assignment without consulting AI or the internet?

Strategies for Preventing AI-Enabled Cheating

While the concerns surrounding AI-enabled cheating are valid, it is essential to strike a balance between maintaining academic integrity and embracing the benefits of AI in education. Here are some strategies that educators can employ to prevent AI-enabled cheating:

1. Educate on Academic Integrity and AI Ethics. Fostering a culture of academic integrity and ethical AI use is crucial. Educators should:
   • Discuss the importance of academic honesty and the consequences of cheating.
   • Provide guidance on the ethical use of AI tools and the importance of acknowledging AI assistance.
   • Involve students in discussions around AI policies and regulations to promote buy-in and understanding.
2. Set Clear AI Usage Policies. Educational institutions should develop clear policies that specify if and how AI tools are allowed for assignments and exams. These policies should:
   • Communicate expectations and requirements clearly to students and faculty.
   • Define what constitutes acceptable AI use and what is considered cheating.
   • Be regularly reviewed and updated as AI technologies evolve.
3. Design AI-Resistant Assignments. Educators can create assignments that are more resistant to AI-enabled cheating by:
   • Using personalized prompts and unique contexts that AI cannot easily replicate.
   • Requires original analysis, emotional connections, and real-world applications.
   • Incorporating group work, presentations, interviews, and other interactive elements.
   • Randomizing test questions and imposing time limits to discourage AI assistance.
4. Develop AI Literacy. Fostering AI literacy among students and educators is crucial. This can involve:
   • Teaching critical thinking skills to evaluate AI outputs and identify potential biases or inaccuracies.
   • Incorporating AI writing as a learning tool, not just a deterrent, to help students understand its capabilities and limitations.
   • Focusing on mastering concepts and developing higher-order thinking skills rather than solely emphasizing performance on assignments or exams.

Final Thoughts

As we navigate the “messy middle” of AI integration in education, it is essential to approach the issue of AI-enabled cheating with nuance and open-mindedness. We must ask ourselves: At what point does it become more detrimental for students not to use AI tools that will be ubiquitous in their future careers? The key is to strike a balance between maintaining academic integrity and embracing the benefits of AI. By outsourcing the “doing” to AI while retaining the “thinking” and critical analysis, we can leverage AI as a powerful learning tool while upholding the core values of education. Ultimately, AI is not a threat to jobs; those who know how to use AI effectively will have a significant advantage. By working together to develop ethical guidelines, clear policies, and innovative pedagogical approaches, we can move forward in this AI-driven era while preserving the integrity of the educational process.

Activities

Activity 1: AI Ethics Debate

Overview

This activity aims to foster critical thinking and ethical reasoning skills by engaging students in a structured debate on the ethical implications of AI use in academic settings.

Description

Divide the class into two teams, one representing the “pro-AI” side and the other representing the “anti-AI” side. Provide each team with ethical scenarios or case studies related to AI-enabled cheating or using AI in education. Teams will research and prepare arguments to defend their assigned positions. During the debate, teams will present their arguments and refute the opposing team’s points. Encourage students to consider various perspectives, such as academic integrity, fairness, privacy concerns, and AI’s potential benefits or drawbacks in education.

Key Benefits

• Develops critical thinking and ethical reasoning skills;
• Promotes understanding of multiple perspectives on complex issues;
• Encourages research and evidence-based argumentation; and
• Fosters respectful dialogue and debate skills.

Possible Challenges

• Ensuring balanced and well-researched arguments from both sides;
• Maintaining a respectful and constructive tone during the debate; and
• Addressing potential biases or preconceived notions about AI.

Support Materials

Gather the following using ChatGPT:

• Ethical case studies or scenarios related to AI and education;
• Guidelines for debate structure and rules; and
• Rubrics for assessing argumentation, research, and presentation skills.

Activity 2: AI Literacy Scavenger Hunt

Overview

This activity aims to develop students’ AI literacy by challenging them to explore and evaluate various AI tools and resources related to education.

Description

Create a list of AI-powered tools, websites, or resources relevant to educational contexts (e.g., writing assistants, plagiarism detectors, personalized learning platforms). Divide students into small groups and provide them with the scavenger hunt list. Each group must locate and explore the listed resources, answering specific questions or completing tasks related to each item. For example, they might be asked to generate a short essay using a writing assistant and then critically evaluate the output or analyze the privacy policies of an AI-powered learning platform.

Key Benefits

• Promotes hands-on exploration and evaluation of AI tools
• Develops critical thinking skills in assessing AI outputs and implications
• Fosters understanding of the capabilities and limitations of AI in education

Possible Challenges

• Ensuring access to the required AI tools and resources
• Providing clear instructions and guidelines for evaluating the resources
• Addressing potential ethical concerns or biases in the AI tools or data sources

Support Materials

Gather the following using ChatGPT:

• List of AI tools, websites, and resources for the scavenger hunt
• Evaluation rubrics or question prompts for each resource
• Guidelines for responsible and ethical use of AI tools

Activity 3: AI Resistant Assignment Design

Overview

This activity aims to equip educators with strategies for designing assignments that are resistant to AI-enabled cheating while promoting authentic learning.

Description

Divide participants into small groups and provide them with a sample assignment or learning objective. Each group will collaborate to redesign the assignment or create a new one incorporating AI-resistant elements. Encourage participants to consider techniques such as personalized prompts, unique contexts, real-world applications, group work, presentations, and time-limited assessments. Groups will present their redesigned assignments and share strategies for making them more resistant to AI-enabled cheating.

Key Benefits

• Develops skills for designing AI-resistant assignments;
• Promotes creativity and innovation in assessment methods; and
• Encourages collaboration and sharing of best practices among educators.

Possible Challenges

• Ensuring assignments are truly resistant to AI-enabled cheating;
• Balancing the need for AI resistance with authentic learning objectives; and
• Addressing potential accessibility or equity concerns with certain assignment types.

Support Materials

Gather the following using ChatGPT:

• Sample assignments or learning objectives for redesign;
• Guidelines and examples of AI-resistant assignment strategies; and
• Rubrics for evaluating the effectiveness of redesigned assignments.

Resources

AI & Cheating

Benito, A. (2023, November 9). Academic integrity and the use of Artificial Intelligence (AI). International Center for Academic Integrity. https://academicintegrity.org/resources/blog/471-academic-integrity-and-the-use-of-artificial-intelligence-ai

Xie, K., & Anderman, E. M. (2023, August 12). 3 ways to use ChatGPT to help students learn – and not cheat. The74. https://www.the74million.org/article/3-ways-to-use-chatgpt-to-help-students-learn-and-not-cheat/

Clark, H. (2023). The AI-infused classroom. Elevate Books Edu.

Clark, H. (2024, April 29). Helping students use AI creatively without the temptation of cheating. Edutopia. https://www.edutopia.org/article/guiding-students-creative-ai-use/

Miller, M. (2023). AI for educators: Learning strategies, teacher efficiencies, and a vision for an artificial intelligence future. Ditch That Textbook.

Spector, C. (2023, October 31). What do AI chatbots really mean for students and cheating?. Stanford Graduate School of Education. https://ed.stanford.edu/news/what-do-ai-chatbots-really-mean-students-and-cheating

AI Literacy

Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., & Barro, S. (2023). AI literacy in K-12: A systematic literature review. International Journal of STEM Education, 10(1), 29. https://link.springer.com/article/10.1186/s40594-023-00418-7

Common Sense Education. (n.d.). AI Literacy Lessons for Grades 6–12.  Retrieved May 2024, from https://www.commonsense.org/education/collections/ai-literacy-lessons-for-grades-6-12

Paulson, E. (2024, April 30). Building educator AI literacy. (2024, April 1). Conestoga Faculty Learning Hub. https://tlconestoga.ca/building-educator-ai-literacy/

Elgersma, C. (2024, March 6). ChatGPT and beyond: How to Handle AI in schools. Common Sense Education. https://www.commonsense.org/education/articles/chatgpt-and-beyond-how-to-handle-ai-in-schools

Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In, Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16). https://doi.org/10.1145/3313831.3376727

Responsible AI for Social Empowerment and Education. (n.d.). MIT AI literacy units. Retrieved May 2024, from https://raise.mit.edu/resources/

References

Miller, M. (2023). AI for educators: Learning strategies, teacher efficiencies, and a vision for an artificial intelligence future. Ditch That Textbook.

Prothero, A. (2024, April 25). New data reveal how many students are using AI to cheat. EducationWeek. Retrieved May 2024, from https://www.edweek.org/technology/new-data-reveal-how-many-students-are-using-ai-to-cheat/2024/04

About the authors

name: Tricia Dwyer-Kuntz

Tricia Dwyer-Kuntz is an Academic Associate in the Faculty of Education at Ontario Tech University, teaching in both the B.Ed and B.A. (Educational Studies) programs. She came to this position after 30 years as a teacher, administrator and special education consultant in K-12. 

Her passion lies in inclusive education and technology integration for ALL students. Chosen by Apple to be an international Apple Distinguished Educator, she enjoys pushing technology to its limit, particularly in the area of accessibility.

name: Stephanie Kuntz

Dr. Stephanie Kuntz is a student at Ontario Tech University enrolled in the Master of Education program. She has a Doctor of Medicine from McMaster University and is a neurologist and clinician educator. She is completing a postgraduate fellowship in multiple sclerosis and neuroimmunology at St. Michael’s Hospital in Toronto. Her interests lie in using AI and e-learning in medical education, particularly in minimizing burnout in undergraduate and postgraduate medical students.