Scholarly and Professional Sources
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European Commission (2018). General Data Protection Regulation (GDPR) – key legal framework for data protection in the EU.
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OECD (2021). AI and the Future of Skills, Education and Learning – includes discussions on the ethical implications of using AI in education.
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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
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University of Edinburgh. Assessment and Feedback Principles – an example of institutional guidelines for fair and transparent assessment.
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EDUCAUSE (2022). Privacy and Student Data: Principles for Responsible Use.
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SURF (Netherlands). Trust and Ethics in Learning Analytics – with an emphasis on institutional policies and privacy protection.
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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
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Hypothes.is – for collaborative annotation of sources and commenting on guidelines.
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Padlet or Miro – for collaborative mapping of challenges and policy proposals.
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Overleaf (or Google Docs) – for collaborative writing of policy proposals in groups.
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Moodle “Workshop” activity – for submitting proposals and peer assessment.
Recommendation for Participants
When developing your policy proposal, rely on:
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Principles – fairness, transparency, responsibility.
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Privacy protection measures – encryption, data minimisation, students’ right of access to their data.
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Tools and practices – which technologies to use responsibly (e.g., Moodle Analytics compared with commercial AI platforms).
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Role of teachers – supporting students in understanding how their data is used.
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