Our approach is not to ban AI or large language models completely, because in fields such as MIS and software development these tools are already part of professional practice.
However, their use must be transparent, ethical, and academically responsible.
Students may use AI tools for purposes such as brainstorming, coding support, language improvement, debugging, literature search support, or structuring ideas. But they are not allowed to submit AI-generated work as if it were entirely their own.
In projects, we expect students to understand, explain, defend, and further develop whatever they submit. Therefore, assessment is not based only on the final written output or code. We also use presentations, oral questioning, project demonstrations, progress reports, and instructor feedback during the process.
This makes it much easier to see whether the student actually understands the work or has simply copied an AI-generated answer.
We also encourage students to declare when and how they used AI tools, especially in project-based assignments. So the focus is shifting from simply detecting AI use to ensuring responsible use, academic integrity, and genuine learning.
In short, our policy is: AI can be used as a learning and productivity tool, but not as a substitute for student competence, authorship, or accountability.