Title: Existing Guidelines and Examples of Good Practice
Course: Assessment Using Digital Technology > Section: Ethical and safety aspects of assessment in a digital environment

Scholarly and Professional Sources

- European Commission (2018). General Data Protection Regulation (GDPR) – key legal framework for data protection in the EU.
- OECD (2021). AI and the Future of Skills, Education and Learning – includes discussions on the ethical implications of using AI in education.

- JISC (2020). Code of Practice for Learning Analytics – clear guidelines for the ethical use of data in education.

Institutional Policies and Examples of Good Practice

- University of Edinburgh. Assessment and Feedback Principles – an example of institutional guidelines for fair and transparent assessment.
- EDUCAUSE (2022). Privacy and Student Data: Principles for Responsible Use.
- SURF (Netherlands). Trust and Ethics in Learning Analytics – with an emphasis on institutional policies and privacy protection.
- Codes of Ethics of the University of Zagreb, the University of Rijeka, and other Croatian universities and higher education institutions: they cover fundamental principles, ethical rules for teaching and research/creative work, and the procedures of ethics bodies.

Digital Tools Useful for the Workshop

- Hypothes.is – for collaborative annotation of sources and commenting on guidelines.
- Padlet or Miro – for collaborative mapping of challenges and policy proposals.
- Overleaf (or Google Docs) – for collaborative writing of policy proposals in groups.
- Moodle “Workshop” activity – for submitting proposals and peer assessment.

Recommendation for Participants

When developing your policy proposal, rely on:

1. Principles – fairness, transparency, responsibility.
2. Privacy protection measures – encryption, data minimisation, students’ right of access to their data.
3. Tools and practices – which technologies to use responsibly (e.g., Moodle Analytics compared with commercial AI platforms).
4. Role of teachers – supporting students in understanding how their data is used.