Reflections on the “Standardizing AI in Higher Education” Conference
June 26-27, 2025
By Özlem Zengin, Züleyha Tulay, Ozan Tekin
Özlem Zengin
“Evaluating AI’s Role in Administrative Tasks and Data Protection” by Koray Tunç
This session presented a very timely and relevant exploration of how AI can support educational administration beyond simple chatbots. It recognized the power of generative models to improve efficiency, support strategic planning, and transform workflows. The session also showed a mature understanding of data protection issues, encouraging critical thinking around privacy, security, and responsible use.
I particularly appreciated the balance between opportunities (e.g., automating tedious tasks, improving quality processes, enhancing student support) and caution (e.g., safeguarding sensitive data, controlling model training). The real-world applications like accreditation tasks or custom GPTs for students were practical and inspiring, suggesting that with the right design, AI can become a trustworthy partner in educational administration.
Overall, this presentation was an excellent starting point for managers seeking to adopt AI strategically while maintaining ethical standards and data security. It invited school leaders to become proactive architects of AI-enhanced systems, rather than passive users of off-the-shelf tools.
Züleyha Tulay
From Challenge to Opportunity: Navigating AI Integration in Higher Education
The two-day conference titled Standardizing AI in Higher Education: Towards Ethical, Effective and Consistent Implementation focused on the urgent need for standardized AI policies and guidelines across Turkish universities. This joint event, organized by Fatih Sultan Mehmet Vakıf University, MEF University and Özyeğin University, shed light on themes such as AI integration in higher education, evolving competencies in the AI era, risks around data privacy, lack of adequate orientation for educators, AI competency frameworks such as the one developed by UNESCO, potential downsides and some practices adopted by the universities for embracing AI.
Takeaways from the conference presentations
The plenary session of the first day of the conference was delivered by Koray Tunç, one of the conference co-hosts. the event. His main message was the fact that if we want to achieve higher standards, collaboration is the keyword and experience matters. He also highlighted that the current landscape of AI implementation in education is fundamentally chaotic, characterized by widespread student misuse and fragmented, experimental teacher adoption that lacks consistency across institutions. Schools find themselves lagging behind technological developments. Moving forward requires establishing controlled environments where AI integration can be systematically developed and tested rather than left to the current state of ad hoc experimentation.
The station rotations offered participants practical insights. In his session titled “Z-Axis Education: Elevation through Connecting with Awe”, Joel Compton focused on the potential downsides of AI and recommended to promote expertise through true flow within the real world. Alireza Kabiriaslifar demonstrated cases where academic integrity and student voice matters while using AI in student work and academic writing. Deniz Barutçuoğlu shared a Coursera project which showed how AI tools can be integrated into language learning tasks for six core skills. In her session titled “Fast-Track Your Listening Materials: A Hands-On Introduction to ElevenLabs”, Meryem Büşra Ünsal shared some samples of listening materials prepared with ElevenLabs and how practical and time-saving it could be for educators.
Want to know how to actually train teachers and students to use AI effectively? Doğu Özdemir had some answers. In his session, he broke down the practical steps for creating AI orientation programs that work, drawing on Kotter's proven 8-step change model to guide schools through the transformation process. Rather than just talking theory, Özdemir showcased real platforms making a difference—like the AI Cafe and Innovative Instruction Hub. The key takeaway? Successful AI integration isn't about throwing technology at people and hoping for the best—it's about structured, thoughtful orientation that acknowledges both the potential and the pitfalls.
In her plenary session, Caroline Fell Kurban explained the current AI landscape through Martin Heidegger's lens, "The essence of technology is by no means technological"—meaning AI's real impact isn't in what it can do, but in what it's doing to us as thinkers and learners. For teachers, this means rethinking everything. Teaching with AI isn't about mastering another tool—it's about preserving student agency and nurturing deep thinking in an age when machines can mimic human cognition. The key insight? Stop asking "What can AI do for us?" and start asking "What is AI doing to us?" That shift changes everything about how we approach AI in education.
The second plenary session delivered by Hakan Tarhan focused on viewing AI as a participant in learning rather than just a partner. Tarhan's practical advice is using AI as a dialogic participant, not just an answer generator. Designing tasks where students can contest or redirect AI outputs rather than simply accepting them is essential. The key insight? Academic integrity isn't about preventing plagiarism—it's about helping students develop their identity and voice in a world where human and machine cognition are increasingly intertwined. As Tarhan puts it: "Don't ban AI—contextualize it."
Gurbet Kabadayı's presentation offered practical look at AI integration through her 10-week AI Club for B1 ESL learners. Rather than theoretical frameworks, she shared real classroom experiences, complete with what worked, what didn't, and what surprised her along the way. The club structure was simple: weekly hour-long sessions where students learned to use AI tools like ChatGPT and MagicSchool for language practice. Each week targeted a specific skill—from prompt writing and vocabulary expansion to speaking practice and real-time debates. The goal wasn't to replace traditional teaching but to build learner autonomy through guided AI interaction.
Following the sessions on both days, participants formed five committees that tackled a distinct dimension of AI integration, providing valuable insights and actionable recommendations. The committees focused on academic integrity, student AI use in and beyond the class, teacher support and training for AI literacy, evaluating AI’s role in admin tasks and data protection and AI in curriculum design and materials development.
The comprehensive roadmap emerging from the brainstorming sessions reveals both the urgency and complexity of integrating AI into higher education while maintaining academic integrity. As educators, we stand at a critical juncture where AI requires immediate, thoughtful action.
Key Challenges We Must Address
The discussions across five committees highlighted some issues that resonate with our own experiences. Students increasingly view AI as a shortcut rather than a learning enhancer, leading to overdependence that undermines critical thinking skills. Meanwhile, faculty face a significant literacy gap—many of us lack fundamental training in effective AI integration and struggle to distinguish between appropriate AI assistance and academic misconduct.
Perhaps most concerning is the absence of consistent institutional policies. Without clear guidelines, we operate in a vacuum where some embrace AI tools while others resist entirely, creating inequitable learning environments and confusion among students about acceptable use.
Practical Solutions Forward
The roadmap offers concrete strategies we can implement immediately. First, developing AI literacy programs for both faculty and students that emphasize responsible use is essential. The recommendation for AI orientation programs and the creation of specialized AI support units resonates strongly.
Assessment redesign emerges as crucial. Rather than attempting to detect AI use, we should embrace transparent integration—requiring students to document their AI interactions, shifting to process-focused evaluation, and designing authentic assessments that leverage AI as a learning tool instead of viewing it as a threat.
Moving Forward Together
The roadmap emphasizes that successful AI integration requires institutional commitment, not individual effort. We need dedicated funding for AI tools and training, collaborative professional development opportunities, and clear ethical guidelines that protect both academic integrity and student privacy.
Most importantly, we must recognize that AI integration isn't about replacing human expertise but enhancing it. Our role evolves from information providers to learning facilitators who guide students in critically evaluating AI-generated content and developing essential digital literacy skills.
The path forward demands courage to embrace change while maintaining our core educational values. By working collectively to implement these recommendations, we can transform AI from a challenge into an opportunity for more engaging, personalized, and effective education.
Ozan Tekin
Gen-AI was dropped into our lives in early 2020. Since then educational professionals as in any other field have been trying to meddle with the challenges it has presented us. However, the speed and scale it has reached have affected our institutional capacity to respond meaningfully, hence prompting educational professionals to adapt to this evolution hastily. As educators, we are now in a peculiar tension. While offering a myriad of educational opportunities for writing, research and personalized feedback, it raises issues regarding academic integrity, erosion of critical thinking, voice and originality. In the field of education, this hype has been met with extreme optimism, framing AI as a ‘’cognitive partner or collaborator’ or a force that ‘’democratizes’’ learning for learners with multilingual backgrounds and diverse cognitive abilities. Nevertheless, others have been skeptical about the extent to which AI can be ‘’effectively’’ and ‘’efficiently’’ augment ‘’learning’’ and ‘’teaching’, questioning the ethical boundaries of its use, bias and commodification of education itself.
To address both edges of the sword, a conference on ‘’Standardizing AI In Higher Education’’ at Fatih Sultan Mehmet University took place last week between 26-27 June. The first day kicked off with plenary speeches on the implications of the use and integration of Gen-AI into pedagogy in higher education, and its potential benefits for teaching and learning from a macro window. Following the plenaries, the participants had the chance to join multiple sessions ranging from practical examples of Gen-AI use in writing, listening and speaking presented by speakers from different universities in Istanbul. One particular example of such a session was delivered by Joel Compton on ‘’Z-Axis Education: Elevation through Connecting with Awe’’. Compton, in his 15-minute presentation, highlighted the importance of attention, cognitive capabilities in the age of AI and invited all educators to pay attention to the transformative faces of social-emotional learning with a focus on striking a balance between meaningful human interaction and connection against the backdrop of a ubiquitous tool as Gen-AI. Dr. Caroline Fell Kurban’s keynote titled “The Essence of Tech is by No Means Anything Technological” invited participants to pause and critically examine what AI is doing to us as humans. Opening with Heidegger’s provocation, she emphasized that the influence of generative AI extends beyond outputs, and it reshapes our thinking habits. Two students might use the same chatbot prompt but walk away with very different cognitive outcomes. The issue, she argued, is not just how we use the tool, but how it reconfigures our approaches to learning.
Drawing on UNESCO’s AI Competency Framework, she urged educators to go beyond AI awareness toward a more grounded AI literacy—one that includes ethical reasoning, pedagogical design, and professional development. These competencies were mapped onto the TPACK framework, underscoring that effective tech use requires solid pedagogical and disciplinary knowledge. She further employed the SAMR model to show that Gen-AI can deepen learning, but only when it leads to genuine task redefinition.Later in the afternoon, Kate Stopa’s session on AI bias shifted focus from cognition to equity. Through real examples, she demonstrated how AI tools often misrepresent accents, reinforce stereotypes, or marginalize non-Western perspectives. Participants left with tools to detect bias, redesign prompts, and create inclusive, critical AI engagements in their classrooms.
Across the sessions, one key message emerged: AI in education must be anchored in human values—agency, depth, and equity. Without that, any standardization effort risks becoming a hollow exercise in efficiency.
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Conference Takeways - PDF Click here