Geotech University AI Adopted Model

 

P-Factor	Definition	Geotech University Application	Focus & Goal
1. Pedagogy	AI as a Teaching/Learning Aid	AI tools are integrated into modular assignments to enhance critical thinking, data analysis, and technical writing practice, acting as a "Co-Pilot".	Enhance Learning Outcomes: Students use AI to accelerate research, synthesize dense material, and debug code, but must cite and verify all output.
2. Policy	Governance and Ethical Use	The creation of clear guidelines governing submission integrity, data privacy, and intellectual property (IP) rights related to AI-generated content.	Ensure Academic Integrity: Define the permissible limits of AI use in academic submissions and establish clear consequences for misuse (see Safety Policy below).
3. Practical Research	AI as a Research Accelerator	Faculty and doctoral students utilize AI for high-level tasks like hypothesis generation, large-scale data modeling, and literature gap analysis, particularly in technical fields.	Drive Innovation: Leverage AI tools to increase research output and efficiency, with mandatory transparency regarding the specific models used.
4. Privacy & Protection	Data Security and Safety	Strict controls on input data to protect PII (Personally Identifiable Information), proprietary research, and university data when interacting with external LLMs (Large Language Models).	Maintain Data Integrity: Prohibit the input of confidential University or research data into non-vetted public AI platforms.