safeviz was created to address and provoke the following questions about learning analytics.
- Does the dashboard comply with local privacy laws and institutional policies?
- Is there a minimum sample size which protects individuals from being identified?
- Is access control to the dashboard with appropriate authentication?
- Are users limited to view only their own data and aggregated cohort data?
- Can stakeholders view data, metrics, models and algorithms?
- Can they find out who has access to the data and how it's being used?
- Can stakeholders correct inaccurate data about themselves?
- Is the dashboard accessible?
- Has user testing been carried out?
- Are recommendations provided to the user?
- Are the recommendations practical and tied to data e.g. online student shouldn't be directed to physical library?
- Is feedback personalised where appropriate?
- Have students been involved in the design?
- Are appropriate institutional review processes in place?
- Is the language used sensitive, beneficial, encouraging?
- Have you looked at what students might be doing to game the system?
- What are the opportunities for associated human intervention?
- Has consideration been given to demotivation and the impacts of continual monitoring?
- Has the data been appropriately contextualised (and not reducing the individual to a metric)?
- Is attention given to data security, maintenance, retention and access policies?
- Are data management agreements in place?
- Has the data been cleaned effectively?
- Are the chosen metrics based on evidence?
- Are continual review processes to place?
- Is there a review process to ensure quality control of the analytics? comply with local privacy laws and institutional policies?
- Is there a minimum sample size which protects individuals from being identified?
- Is accessed controlled to the dashboard with appropriate authentication?
- Are users limited to view only their own data and aggregated cohort data?