- Development of Comprehensive AI Teaching Competencies
Key Point
Build your own AI teaching skills and help students develop AI literacy — teach about, with, and for AI in ways that fit higher education.
✅ Examples
|
What to Do |
Why It’s Important |
Recommended Approach |
|---|---|---|
| ✅ Foster general AI literacy in your course. | Prepares students for real-world AI applications. | Integrate discussions on AI’s impact in your field. |
| ✅ Integrate AI tools when they enhance learning. | Supports active, engaging pedagogy. | Use AI to support collaboration, creativity, or personalization (e.g., idea generation, tailored feedback, co-writing). |
| ✅ Teach about AI ethics and responsible use. | Builds critical awareness of AI’s risks and limits. | Include modules or activities on bias, data privacy, and responsible AI design. |
❌ Examples
|
What Not to Do |
Why It’s a Problem |
Recommended Fix |
|---|---|---|
| ❌ Don’t assume students naturally understand AI’s impact. | Gaps in AI literacy can harm future practice. | Include AI basics even in non-technical courses. |
| ❌ Don’t use AI tools just because they are widely adopted. | Poor fit can distract from learning goals. | Assess if the tool truly enhances your pedagogy first. |
| ❌ Don’t neglect ethical dimensions when teaching AI. | Students may misuse AI or ignore its risks. | Make ethics a core part of any AI-related teaching. |
Excerpt from the Official Guidelines
Instructors are urged to develop digital competencies on the use of AI in teaching, by: a) fostering general AI literacy among students (Teaching for AI), b) integrating AI tools when they assess that this can enhance pedagogy (Teaching with AI), and c) delivering specialized instructions on the use of AI technologies and the ethical considerations involved (Teaching about AI). In any case, the use of AI in teaching should be adapted to align with the unique pedagogical models, professional autonomy, and structural requirements of higher education3.
Last Updated on 5 August, 2025
