From the code of practice for learning analytics:
- “Institutions should specify under which circumstances they believe they should intervene”
- “The type and nature of interventions, and who is responsible for carrying them out, should be clearly specified”
- “The impact of interventions on staff roles, training requirements and workload should be considered”
- “Analytics systems and interventions should be carefully designed and regularly reviewed to ensure that: students maintain appropriate levels of autonomy in decision-making; knowledge that their activity is being monitored does not lead to negative impacts; adverse impacts are minimised; staff have a working understanding of legal, ethical and unethical practice”
As with access, some interventions carry a risk of making a wellbeing or mental health problem worse, rather than better. Talking to someone about stress, depression or suicide requires both training and readily available support.
Data and algorithms will flag individuals with widely differing needs: personalised support is likely to be needed. Note that this may also apply where a concern may has been raised but appears to be a false alarm: as well as reviewing the model and process that led to the concern being raised, institutions should consider whether such individuals now need support to avoid them becoming self-fulfilling prophecies.
Institutions should therefore consider which interventions should be provided in a medical context, in case of a negative reaction or consequences, and should ensure that they can provide appropriate support before implementing any wellbeing/health application.