- Avoiding Bias: Learning analytics must be designed to avoid reinforcing biases that could disadvantage certain groups of learners. Data used to train AI models should be representative and diverse to prevent biased outcomes.
- Equitable Analytics: It is important that the insights provided by learning analytics support all learners equitably. Special care should be taken to ensure that predictive models do not unfairly label or disadvantage specific individuals or groups.