Yapay Zekâ ve Hukuk: Yapay Zekâ Çağında Yeni Eğitim Paradigmaları ve MootGPT Deneyimi Üzerine Bir İnceleme

Öz

Bu çalışma, yapay zekânın (YZ) özellikle üretken yapay zekâ (ÜYZ) araçlarının, hukuk eğitimindeki yaklaşım, yöntem ve değerlendirme süreçlerini nasıl dönüştürdüğünü; bu dönüşümün İbn Haldun Üniversitesi Hukuk Fakültesi’nde yürütülen “Yapay Zeka ve Hukuk” dersi ile somutlaştığını ve ders çıktısı olan “MootGPT: Yapay Zekâ ile Etkileşimli Farazî Dava Hazırlık Asistanı” aracılığıyla uygulamalı bir örneğe dönüştüğünü incelemektedir. Çalışma, önce YZ’nin eğitimde özelleştirilmiş içerik üretimi, sürekli geri bildirim ve etkileşimli öğrenme gibi işlevleri üzerinden hukuk eğitimine sunduğu fırsatları ve riskleri tartışmakta; ardından hukuk eğitimi için önerilen AILE (Artificial Intelligence + Law + Education) birleşim modelinin hedef, içerik ve ölçme-boyutlarını ana hatlarıyla sunmaktadır. Makalede, 2024–2025 Bahar döneminde açılan dersin kapsamı, yürütülen “Adaletin Kodları” öğrenci çalıştayı ve dört öğrenci projesi özetlenmekte; merkezî örnek olan MootGPT’nin sistem ve kullanıcı promptlarından oluşan iskelet tasarımı; Input–Output, Chain-of-Thought, Expert ve Tree-of-Thought gibi tekniklerin entegrasyonu; rol simülasyonları (hakim, karşı avukat, akademik danışman) ve hava hukuku odaklı bağlamlandırma ayrıntılandırılmaktadır. Süreçte gözlenen güçlü yönler (dil doğruluğu, argüman örgüsü, simülasyonla pratikleşme, zaman verimliliği) ile sınırlılıklar (halüsinasyon, muğlak/şablon çıktılar, eleştirel düşünmede erozyon riski, gizlilik/etik hassasiyet) sistematik biçimde değerlendirilmektedir. Sonuç olarak, ÜYZ’nin hukuk eğitimine entegrasyonunda öğretim tasarımının, kaynak doğrulama ve etik ilkelerin, ayrıca kullanıcıların YZ okuryazarlığının belirleyici olduğunu vurgulamaktadır.

Anahtar Kelimeler

• yapay zekâ
• üretken yapay zekâ
• hukuk eğitimi
• farazi dava
• prompt
• prompt tasarımı.

Artificial Intelligence and Law: An Examination of New Educational Paradigms in the Age of Artificial Intelligence and the MootGPT Experience

Öz

This study examines how artificial intelligence (AI), particularly generative AI (GIA) tools, transforms approaches, methods, and evaluation processes in legal education; how this transformation materializes in the “Artificial Intelligence and Law” course conducted at Ibn Haldun University Faculty of Law; and how it is transformed into a practical example through the course output, "MootGPT: Artificial Intelligence-Based Interactive Moot Court Preparation Assistant." The study first discusses the opportunities and risks AI presents to legal education through its functions in education, such as customized content production, continuous feedback, and interactive learning. It then outlines the objectives, content, and measurement dimensions of the proposed AILE (Artificial Intelligence + Law + Education) integration model for legal education. The article summarizes the scope of the course offered in the Spring 2024–2025 semester, the “Codes of Justice” student workshop conducted, and four student projects; the skeleton design of the central example, MootGPT, consisting of system and user prompts; the integration of techniques such as Input–Output, Chain-of-Thought, Expert, and Tree-of-Thought; role simulations (judge, opposing attorney, academic advisor), and aviation law-focused contextualization are detailed. The strengths observed during the process (language accuracy, argument structure, practice through simulation, time efficiency) and limitations (hallucinations, ambiguous/template outputs, risk of erosion in critical thinking, privacy/ethical sensitivity) are systematically evaluated. In conclusion, it emphasizes that instructional design, source verification and ethical principles, as well as users' AI literacy, are decisive in the integration of AI into legal education.

Anahtar Kelimeler

• artificial intelligence
• generative artificial intelligence
• legal education
• moot court
• prompt
• prompt design.

Kaynakça

1. Arora, Jhanvi, Tanay Patankar, Alay Shah, ve Shubham Joshi. “Artificial Intelligence as Legal Research Assistant”, 2020. https://www.semanticscholar.org/paper/Artificial-Intelligence-as-Legal-Research-Assistant-Arora-Patankar/bdc3690b27decc58bcbdb8b624153778f0854d7a.
2. Ajevski, Marjan, Kim Barker, Andrew Gilbert, Liz Hardie, ve Francine Ryan. “ChatGPT and the Future of Legal Education and Practice.” The Law Teacher 57/3 (2023): 352–399.
3. Bayraktar, Breana, Dayna Henry, ve Jessica Taggart. “Navigating the AI-enabled Education Landscape: A Multifaceted Approach to Providing Effective Professional Learning and Support for Educators.” Theory Into Practice 64/4 (2025): 421–433.
4. Buckley, Josh, Mark Burdon, Anna Huggins, ve Nicholas Godfrey. “Towards a Legal Prompt Engineering Strategy for Identifying Rationes Decidendi”. Monash University Law Review 51/1 (2025): 1-41.
5. Caldarini, Guendalina, Sardar Jaf, ve Kenneth McGarry. “A Literature Survey of Recent Advances in Chatbots”. Information 13/1 (15 Ocak 2022): 41.
6. Charlotin, Damien, ve Niccolò Ridi. “GenAI as an International Lawyer: A Case Study with the Jessup International Law Moot Court”, 05 Haziran 2025.
7. Chen, Lijia, Pingping Chen, ve Zhijian Lin. “Artificial Intelligence in Education: A Review”. IEEE Access 8 (2020): 75264-78.
8. Chen, Xieling, Di Zou, Haoran Xie, Gary Cheng, ve Caixia Liu. “Two Decades of Artificial Intelligence in Education”. Educational Technology & Society 25/1 (2022): 28-47.

9. Farber, Shai. “Harmonizing AI and human instruction in legal education: A case study from Israel on training future legal professionals.” International Journal of the Legal Profession 31/3 (2024): 349–363.
10. Fenwick, Mark, Wulf A. Kaal, ve Erik P. M. Vermeulen. “Legal Education in a Digital Age: Why ‘Coding for Lawyers’ Matters.” TILEC Discussion Paper DP 2018-033 (Ekim 2018). Tilburg Law and Economics Center (TILEC). https://ssrn.com/abstract=3227967.
11. Friedland, Steven I. “Adaptive Strategies for the Future of Legal Education.” Loyola Law Review 61/2 (2015): 211–234.
12. Guan, Chong, Jian Mou, ve Zhiying Jiang. “Artificial Intelligence Innovation in Education: A Twenty-Year Data-Driven Historical Analysis”. International Journal of Innovation Studies 4/4 (Aralık 2020): 134-47.
13. Gutowski, Nachman N., ve Jeremy W. Hurley. “Forging Ahead or Proceeding with Caution: Developing Policy for Generative Artificial Intelligence in Legal Education”. University of Louisville Law Review 63/3 (2025 2024): 581-626.
14. Head, Amanda, ve Sonya Willis. “Assessing law students in a GenAI world to create knowledgeable future lawyers.” International Journal of the Legal Profession 31/3 (2024): 293–310.
15. Hiller, Janine S., ve Destynie J. L. Sewell. “Presumptions of AI Malfunction: A Judicial Response to AI Harms”. American University Law Review 74/6 (2025 2024): 1497-1550.
16. Hwang, Gwo-Jen. “A conceptual map model for developing intelligent tutoring systems”. Computers & Education 40/3 (01 Nisan 2003): 217-35.
17. Israfilzade, Khalil, ve Nuraddin Sadili. “Beyond interaction: Generative AI in conversational marketing - foundations, developments, and future directions”. JOURNAL OF LIFE ECONOMICS 11, sy 1 (09 Şubat 2024): 13-29. doi:10.15637/jlecon.2294.
18. Lee, Daniel ve Edward Palmer. “Prompt Engineering in Higher Education: A Systematic Review to Help Inform Curricula”. International Journal of Educational Technology in Higher Education 22 (2025): 1-22.
19. Lee, Jiwon ve Jeongmin Lee. “Generative AI chatbot for teachers’ data-informed decision-making”. Educational Technology & Society 28/3 (2025): 298-317.
20. Li, Peng Lai. “Natural Language Processing Technology Explainers”. Georgetown Law Technology Review 1/1 (2017 2016): 98-104.
21. Liu, Pengfei, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi ve Graham Neubig. “Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing”. arXiv, 2021.
22. Ma, Bo, ve Yuhuan Hou. “Artificial Intelligence Empowers the Integrated Development of Legal Education: Challenges and Responses”. Future Human Image 16 (2021).
23. Ma, Zhi-Qiang, Xin Cui, Wen-ping Liu, Yun-Fang Tu ve Gwo-Jen Hwang. “ChatGPT-assisted collaborative argumentation”. Educational Technology & Society 28/3 (2025): 133-50.
24. McCarthy, John. “What is Artificial Intelligence”, 2007.
25. Migliorini, Sara ve João Ilhão Moreira. “The Case for Nurturing AI Literacy in Law Schools”. Asian Journal of Legal Education 12/1 (Ocak 2025): 7-24.
26. Pei, Leisi, Morris Siu-Yung Jong, Biyun Huang, Wai-Chung Pang, ve Junjie Shang. “Formally integrating Generative AI into Secondary Education: Application of ChatGPT in EFL Writing Instruction.” Educational Technology & Society 28/3 (2025): 281–297
27. Popenici, Stefan A. D., ve Sharon Kerr. “Exploring the Impact of Artificial Intelligence on Teaching and Learning in Higher Education”. Research and Practice in Technology Enhanced Learning 12/1 (Aralık 2017): 22.
28. Schulhoff, Sander, Michael Ilie, Nishant Balepur, Konstantine Kahadze, Amanda Liu, Chenglei Si, Yinheng Li, vd. “The Prompt Report: A Systematic Survey of Prompt Engineering Techniques”. arXiv (26 Şubat 2025).
29. Scott, David M, ve Ukri Soirila. “The Politics of the Moot Court”. European Journal of International Law (20 Ekim 2021).
30. Serra, Alexandria. “AI Lawyering Skills Trainers: Transforming Legal Education with Generative AI”. Case Western Reserve Journal of Law, Technology and the Internet 16/1 (2025): 74-132.
31. Surden, Harry. “Machine Learning and Law”. Washington Law Review 89/1 (2014): 87-116.
32. Tao, Lei, Hao Deng ve Yanjie Song. “Generative artificial intelligence in education: A topic-based bibliometric analysis.” Educational Technology & Society 28/2 (2025): 327–347.
33. UNESCO. What is generative AI and how does it work? Guidance for generative AI in education and research. UNESCO, 2023. JSTOR.
34. Ünlütabak, Burcu ve Onur Bal. “Theory of mind performance of large language models: A comparative analysis of Turkish and English”. Computer Speech & Language 89 (01 Ocak 2025): 101698.
35. Walter, Yoshija. “Embracing the Future of Artificial Intelligence in the Classroom: The Relevance of AI Literacy, Prompt Engineering, and Critical Thinking in Modern Education”. International Journal of Educational Technology in Higher Education 21 (2024): 1-29.
36. Wang, Jia, Xingyu Yuan, Yuqing Zhang, Pinxiao Guan, Hui Zeng, ve Zeyu Wang. “Development and Application of an Intelligent Moot Court Trial Platform Based on Machine Learning and Natural Language Processing Technology”, 558-64. Atlantis Press, 2023.
37. Wei, Jason, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, ve Denny Zhou. “Chain-of-Thought Prompting Elicits Reasoning in Large Language Models”. arXiv, 2022.
38. Xu, Benfeng, An Yang, Junyang Lin, Quan Wang, Chang Zhou, Yongdong Zhang, ve Zhendong Mao. “ExpertPrompting: Instructing Large Language Models to be Distinguished Experts”. arXiv, 2023.
39. Yao, Shunyu, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao, ve Karthik Narasimhan. “Tree of Thoughts: Deliberate Problem Solving with Large Language Models”. arXiv, 2023.
40. Zhu, Chenjia, Meng Sun, Jiutong Luo, Tianyi Li, ve Minhong Wang. “How to harness the potential of ChatGPT in education?” Knowledge Management & E-Learning: An International Journal (10 Haziran 2023): 133-52.