Table of Contents
Authenticating Student Work in the AI Era: An International Baccalaureate Teacher's Perspective
By Michele Lackovic
7 minute read
Key Takeaways:
Teachers are the first line in authenticating student work
Process-based authentication works better than AI detection
Practical strategies help maintain academic integrity
Small steps lead to meaningful integration
As I watch my 11th grade International Baccalaureate (IB) students work with Khanmigo, Khan Academy's AI tutor, to refine their Extended Essay research questions, the dual nature of AI in education becomes increasingly clear. While AI tools can effectively support student learning, teachers remain the first and most important line in authenticating student work. As both a classroom teacher and someone who has facilitated AI workshops for over 3,000 educators, I see daily that teacher authentication is key in maintaining academic integrity for student assessments and coursework.
The Authentication Challenge
AI detection software isn't the definitive solution it once promised to be. Even companies like Turnitin acknowledge that AI detection tools shouldn't be the sole determinant of authenticity, as these tools work by identifying patterns rather than exact matches. This can lead to false positives, particularly for students writing in their second language who may use more patterned language structures.
The limitations of AI detection have led some educators to shift their focus to document history tracking, but this too has proven to be an exhausting and futile endeavor.
Even as educators scrutinize document histories for signs of AI-generated content being pasted in, new tools are emerging to circumvent these checks. For example, philosophy professor Graham Clay recently demonstrated how OpenAI's Operator can simulate authentic writing processes in Google Docs - creating natural-looking version histories complete with gradual typing, typical errors, and realistic breaks between sections.
While students may not currently use such tools, their existence shows why we need to move beyond technological policing of student work.
The IB's Framework for Authentication
The IB system recognizes that teachers know their students' capabilities, writing voices, and thinking patterns best. For decades, the IB's mandatory scaffolded assessment process has served a dual purpose: guiding students through complex thinking and writing tasks while naturally authenticating their work through close teacher supervision. This built-in verification system remains as relevant in the AI era as it was in the past. That's why teachers must authenticate work before it's submitted for external assessment and moderation.
The IB's Academic Integrity Policy establishes a clear framework for AI use (International Baccalaureate Organization, "Appendix 6: Guidance on the use of artificial intelligence tools" 53-55). Building on this foundation, the IB's "Evaluating 13 Scenarios of Using AI in Student Coursework" provides specific guidance for teachers and students:
Appropriate AI Use:
Summarizing key points and suggesting references (with student understanding)
Exploring alternative viewpoints (with independent investigation)
Generating essay structure templates (with acknowledgment)
Inappropriate AI Use:
Generating complete essays
Having AI rewrite work
Using AI for required reflections
Moving Toward Process-Based Authentication
Leon Furze's AI Assessment Scale offers helpful guidance for teachers navigating this new landscape. Moving away from simple "permitted/not permitted" distinctions, it now provides nuanced guidance for integrating AI tools authentically and transparently into the learning process.
At our school, we've transformed how we approach summative writing assessments. Our Extended Essay student-centered professional development exemplifies this evolution. In a full day workshop, students learn the complete research process - from initial questioning to final citation - with AI tools integrated naturally into each step.
Librarians, subject-area expert teachers, and coordinators work together, providing immediate guidance as students learn to use these tools effectively.
We've similarly redesigned our approach to course-based summative assessments. The HL Essay in Language A Literature is now developed largely in class, where teachers can meet with students individually and peers can engage in discussion. While AI writing tools can provide structured guidance, there's no replacement for having a teacher present during the writing process to understand individual student needs and provide contextual feedback.
Practical Authentication Strategies
These authentication principles can be translated into concrete classroom practices that support both learning and academic integrity. In my classroom, I've found success with:
1. Real-Time Engagement
Partner discussions with immediate presentations
Supervised writing with devices in exam mode
Hand-annotated texts
Individual conferences during project development
2. Evidence of Process
Regular check-ins at key development stages
Student explanations of methodology
Research logs with dated entries
Reflection on AI tool use and learning impact
3. Mixed Assessment Approaches
Combining take-home analysis with in-class synthesis
Oral explanation of written work
Portfolio development showing work progression
Discussion-based peer engagement
The Heart of Teaching
I recently watched a talk show where an AI professional development trainer and a philosophy professor debated the role of AI in education. While one advocated embracing AI tools and the other rejected them entirely, I found myself thinking: we can do both. The key is sequence - having students do the heavy lifting of reading and analysis first, then using AI to extend their thinking. Without teacher guidance in this process, students may never learn the value of doing the foundational work themselves.
We are in a world where the teacher's role is more important than ever. The challenges are real. As AI tools advance, students face temptation to shortcut their learning. But with these challenges come opportunities for sophisticated research, deeper analytical discussions, and the development of critical evaluation skills. It is precisely in navigating these opportunities - knowing when to embrace AI tools and when to rely on traditional methods - that teacher expertise becomes indispensable.
The path forward isn't about dramatic overnight changes. It's about taking small steps, experimenting thoughtfully, and gradually finding what works for our students and our teaching style.
The workplaces our students will enter expect proficiency with AI tools. By focusing on process, engagement, and demonstration of understanding, we can help them develop both the technical and ethical skills they'll need - one step at a time.
After all, isn't this what good teaching has always been about? Meeting students where they are, guiding them through new challenges, and helping them grow into capable, ethical learners - no matter what tools they're using.
Visit www.myibsource.com for more information
About the Author: Michele Lackovic teaches IB Literature and Theory of Knowledge at Suncoast Community High School, where she coordinates both MYP and CAS. An IB workshop leader specializing in Literature and examiner for Extended Essay and Language A, she leads professional development in AI integration and recently facilitated an AI in IBEN Practices webinar with nearly 3,000 global attendees. She is the author of Pearson's English A Literature for the IB Diploma and holds degrees from Penn State and UCLA.
Works Cited
International Baccalaureate Organization. “"Appendix 6: Guidance on the use of artificial intelligence tools."” Academic Integrity Policy, International Baccalaureate, March 2023. Accessed 15 February 2025.
International Baccalaureate Organization. “Evaluating 13 Scenarios of Using Artificial Intelligence (AI) in Student Coursework.” International Baccalaureate, 2024. Accessed 15 February 2025.
