The DELICATE checklist contains eight action points that should be considered by managers and decision makers planning the implementation of Learning Analytics / Educational Data Mining solutions either for their own institution or with an external provider. The eight points are: 1. Determination: Decide on the purpose of learning analytics for your institution. What aspects of learning or learner services are you trying to improve? 2. Explain: Define the scope of data collection and usage. Who has a need to have access to the data or the results? Who manages the datasets? On what criteria? 3. Legitimate: Explain how you operate within the legal frameworks, refer to the essential legislation. Is the data collection excessive, random, or fit for purpose? 4. Involve: Talk to stakeholders and give assurances about the data distribution and use. Give as much control as possible to data subjects (permission architecture), and provide access to their data for the individuals. 5. Consent: Seek consent through clear consent questions. Provide an opt-out option. 6. Anonymise: De-identify individuals as much as possible, aggregate data into meta-models. 7. Technical aspects: Monitor who has access to data, especially in areas with high staff turn-over. Establish data storage to high security standards. 8. External partners: Make sure externals provide highest data security standards. Ensure data is only used for intended purposes and not passed on to third parties. We hope that the DELICATE checklist will be a helpful instrument for any educational institution to demystify the ethics and privacy discussions around Learning Analytics. As we have tried to show in this article, there are ways to design and provide privacy conform Learning Analytics that can benefit all stakeholders and keep control with the users themselves and within the established trusted relationship between them and the institution.

1. The DELICATE Checklist
to implement trusted
Learning Analytics
LACE Project is supported by the European Commission
Seventh Framework Programme under grant 619424.
Drachsler, H. & Greller, W. (2016). Privacy and Analytics – it’s a DELICATE issue. A Checklist
to establish trusted Learning Analytics. 6th Learning Analytics and Knowledge Conference
2016, April 25-29, 2016, Edinburgh, UK.
D
DETERMINATION – Why you want to apply Learning Analytics?
u What is the added value (Organisational and data subjects)
u What are the rights of the data subjects (e.g., EU Directive
95/46/EC)
E
EXPLAIN – Be open about your intentions and objectives
u What data will be collected for which purpose?
u How long will this data be stored?
u Who has access to the data?
L
LEGITIMATE – Why you are allowed to have the data?
u Which data sources you have already (aren’t they enough)
u Why are you allowed to collect additional data?
I
INVOLVE – Involve all stakeholders and the data subjects
u Be open about privacy concerns (of data subjects)
u Provide access to the personal data collected (about the data subjects)
C
CONSENT – Make a contract with the data subjects
u Ask for a consent from the data subjects before the data collection
u Define clear and understandable consent questions (Yes / No options)
u Offer the possibility to opt-out of the data collection without consequences
A
ANONYMISE – Make the individual not retrievable
u Anonymise the data as far as possible
u Aggregate data to generate abstract metadata models (Those do not fall
under EU Directive 95/46/EC)
T
TECHNICAL – Procedures to guarantee privacy
u Monitor regularly who has access to the data
u If the analytics change, update the privacy regulations (new consent needed)
u Make sure the data storage fulfills international security standards
E
EXTERNAL – If you work with external providers
u Make sure they also fulfil the national and organisational rules
u Sign a contract that clearly states responsibilities for data security
u Data should only be used for the intended services and no other purposes