Assessment and academic integrity

In the age of AI, assessment processes cannot be approached solely through the dilemma of prohibiting or permitting. At BAU, the core aim is to develop assessment approaches that are fair, aligned with learning outcomes, and better able to make visible students' original thinking, analysis, synthesis, problem-solving, and transferable skills.

Our Faculty of Educational Sciences and BAUPRO are actively studying the effects of AI on assessment, learning analytics, feedback, instructional design, and academic integrity, and are contributing to the pedagogical framework for the transformation in this area.

This work supports treating AI at BAU not merely as a technical tool but as a field that transforms teaching quality, student support, pedagogical design, and academic assessment processes.

Questions to clarify for each course

• Is the use of AI permitted in this course?
• If it may be used, for what purposes?
• In which types of assignments, projects, or exams is its use restricted?
• Is disclosure expected when AI assistance is used?
• How should AI output be verified?
• How will citation and academic integrity principles be applied?
• Which data, documents, or materials may students not upload to AI tools?
• Does the assessment structure create an unfair advantage or disadvantage between students who use AI and those who do not?