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Table 2 Code of practice for Learning Analytics, adapted from Sclater (2016) and Draschler & Greller (2016)

From: A call to action: a systematic review of ethical and regulatory issues in using process data in educational assessment

Dimension Category Description
Regulation and privacy Responsibility Clarify who is responsible for legal, ethical and effective use of LA
Access Participants have the right to access information held about them (data, analytics & interpretations), to correct inaccurate personal data and to obtain copies of data
Stewardship of data Data should be administered in compliance with legal requirements. Only the minimum data required for analytics purposes should be collected, and data should be kept only for the period required. How to deal with external partners needs to be planned and specifieda
  Privacy Comply with legal provisions of data protection; restrict access to data and analytics
Ethics Transparency and consent Provide information about how and whether students and/or teachers should be informed about data collection, methods of analysis and results; Include provision for informed consent and right to opt out. Secure fresh participant consent if the analytics change during the studya
  Validity Monitor the quality, robustness and validity of data and analytics processes in order to develop and maintain trust in LA. Data should be accurate and algorithms valid
  Enabling positive interventions Establish rules about when to act on information about students derived from LA and consider what the consequences of not acting are
  Minimizing adverse impacts Identify the main adverse impacts in the application of LA, and how to deal with them. Demonstrate awareness of issues that reinforce discriminatory attitudes, or where increased social exclusion is expected
  1. aItalicised text indicates elements incorporated from Draschler & Greller (2016)