Learning analytics that supports learning while still respecting privacy?

Dai Griffiths| University of BoltonEDEN Conference| 17 June 2016

#laceproject, d.e.griffiths@bolton.ac.uk

Objectives of this workshop

To review some the ethical and privacy issues raised by learning analytics

To share and discuss policies on privacy and and ethics from participants’ countries and institutions

To reflect on changes or initiatives that might be needed in our institutions

Data policies and data ownership are major concerns among learning analytics researchers and practitioners

3LACE – Annual Review – Luxembourg – 16 February 2016

Visions of the future, 2025

Objectives:● To explore or expose underlying

assumptions or information leading to differing judgments on learning analytics

● To correlate informed judgments on the topic of learning analytics, which spans a wide range of disciplines.

Respondents: Experts and LACE contacts● Eight visions, invited to respond to at least three (random)● 103 responses (28% response rate) ● 487 responses to visions 3.6 per respondentReport is at http://www.laceproject.eu/project-deliverables/

The eight visions1. Classrooms monitor the physical environment to support

learning and teaching.

2. Personal data tracking supports learning.

3. Analytics are rarely used in education.

4. Individuals control their own data.

5. In 2025, open systems for learning analytics are widely adopted.

6. Learning analytics systems are essential tools of educational management

7. Most teaching is delegated to computers.

8. Analytics support self-directed autonomous learning

5LACE – Annual Review – Luxembourg – 16 February 2016

Main findings

• Enthusiasm and doubt: Learning analytics could be great, but will it be able to fulfil its potential?

• Policies and infrastructure: Strengthen the rights of data subjects, and create open architecture and applications.

• A consensus on pedagogy: Human mediated education, and avoidance of automated teaching.

• Power, ethics and data ownership: Satisfactory solutions to these are key factors for success of learning analytics.

6LACE – EDEN Workshop Budapest– 17 June 2016

Recommended actions (for blue items of previous slide)

•Privacy and ethicso Development of policies and

regulations for control by data subjects.

o Develop tools and systems to enable and enforce privacy policy

o Promote transparency and accountability in collection and use of data

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• InfrastructureoSupport development of common data models, specifications and policies. oSupport development of open infrastructure

How can we characterise the positions being taken in relation to ethics and privacy?

1) Adopt data driven processes, and adapt the institution accordingly: in education we need to get up to speed on the changes in the wider economic sector

From Bricks to Clicks

Adapted from Bricks to Clicks, UK Higher Education Commission, Jan 16http://www.policyconnect.org.uk/hec/research/report-bricks-clicks-potential-data-and-analytics-higher-education

• Worldwide, organisations are realising the significant value of big data and using data analytics to improve business.

• Tesco’s Clubcardo Personalised customer relationship managemento Predict when and where products will be sold

• Spotifyo Gathers over 600 gigabytes daily , holds 28 petabyteso Analysis suggests more music the user might likeo In 2013 Spotify predicted the Grammy Awards winners

• LinkedIn?

And now for education...

• The UK HE Commission believes that:o The UK HE sector currently possesses a rich and vast amount

of data, but is not making the most effective use of this valuable resource.

o The sector should seize the opportunities that data and analytics presents immediately.

• What are the implications for ethics and privacy as we know them in education?

Education, meet big data...

• Wikipedia: data sets that are so large or complex that traditional data processing applications are inadequate

• But it is not bigness that is driving change in education. Data sets in educational institutions are generally relatively manageable (though there are exceptions)

• The change is coming from the approach of “lets collect as much data as we can on our platform, and then fish in that pond to see what we can find that will enable us to offer a better/more profitable/more popular service”

• This is a dramatic shift in educational policy and ethics.

2) Proceed with caution: we have important ethical processes that should be respected.

Informed consent

• Informed consent has been a basic principle of research ethics since the Nuremberg Codeo Point 1: Required is the voluntary, well-informed, understanding

consent of the human subject in a full legal capacity.

• Ethics and privacy: OECD 2013o ...data should be obtained by lawful and fair means and, where

appropriate, with the knowledge or consent of the data subject.o Personal data should be relevant to the purposes for which they

are to be used, and, to the extent necessary for those purposes..o The purposes for which personal data are collected should be

specified not later than at the time of data collection

REGULATION (EU) 2016/679, 27 April 2016

‘On the protection of natural persons with regard to the processing of personal data.’ Article 5. • Personal data shall be:• (b) collected for specified, explicit and legitimate purposes and

not processed in a manner that is incompatible with those purposes;

• (c) adequate, relevant and not excessive in relation to the purposes for which they are processed;

• (e) kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which they are processed;

http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32016R0679&from=EN

3) We have no choice, but we need to conduct ourselves in a respectful way.

JISC code of practice 2015

• Institutions will define the objectives for the use of learning analytics, what data is necessary to achieve these objectives, and what is out of scope.

• The data sources, the purposes of the analytics, the metrics used, who has access to the analytics, the boundaries around usage, and how to interpret the data will be explained clearly to staff and students. Institutions should also clearly describe the processes involved in producing the analytics to students and staff or make the algorithms transparent to them.

• Students will normally be asked for their consent for personal interventions to be taken based on the learning analytics. (N. Sclater & Bailey 2015)

Open University Policy on Ethical use of Student Data for Learning Analytics (2015)

• “The OU has a responsibility to all stakeholders to use and extract meaning from student data for the benefit of students where feasible”.

• FAQs on their policy: “Unfortunately, it is not possible, at present, to have your data excluded. In order to have a complete dataset, the University will use all student data to analyse patterns of behaviour”

• Implication: if individuals were given the right to opt-out, then this could be seen as unethical, because opting-out reduces the efficacy of learning analytics which can improve the education of others.

The DELICATE checklist from LACE

• LACE has developed the DELICATE checklist as a helpful instrument for any educational institution to demystify the ethics and privacy discussions around Learning Analytics.

• Available at http://www.laceproject.eu/ethics-privacy/

Two technological factors that complicate the discussion

Factor 1: the historical balance in data collection is being upset by technology

● Education institutions have always gathered and stored data as they wished, with no permission from students○ Attendance registers○ Library use (very delicate in the USA!)○ Grades and examination results

● The use of that data was constrained by the technologies of paper, but Information technologies expand the possibilities enormously

● So maybe we don’t need to worry, we’ve always done this● Or maybe we need to be very concerned: the same laissez faire

attitudes with the new technology may lead us to a dystopia

Factor 2: techncial infrastructure constrains (or determines) policy options

• Who determines which data is made accessible by your learning platforms?

• Who ensures the security of the data that you gather?• Who controls access to the data?• Who controls the way that the data is analysed? • If you use third party systems, can you find out how the data is

analysed and used?

Technical infrastructure was a major concern in our Visions study• The LACE Visions of the Future study flagged up open

architectures and infrastructure as a learning analytics driver.

• There are ecosystems growing up around IMS Caliper (top down, largely driven by the big commercial platforms, e.g. Blackboard, Pearson), and around xAPI (bottom up, largely driven by a community of research institutions and learning analytics user groups).

• It is important to understand these options, and insist that they interoperate.

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If you want more...

Is Privacy a Show-stopper for Learning Analytics? A Review of Current Issues and their Solutionshttp://bit.ly/lace-privacy

An in-depth LACE report on interoperability for Learning Analytics http://www.laceproject.eu/wp-content/uploads/2016/01/LACE_D7-4.pdf

The three paradigmatic positions1. Proceed with caution, even at the cost of functionality:

respect long standing policy on research ethics and data privacy (Directive 2016/679, some national policies, e.g. Germany). If that means losing functionality, that is a price worth paying for maintaining our rights and values.

2. We have no choice, but must try to be respectful: the regulatory and economic environment demands that we leverage data analytics, but we must try to make data use as responsible and transparent as we can. (OUNL and JISC)

3. Adopt data driven processes, and adapt the institution accordingly: The world has changed, and people’s expectations for data use have changed too. Education needs to catch up with business, and create a data driven university. (e.g. American Public University System). Whatever changes to policy and organisation are needed will be carried out.

Discussion activity (if you are not in an institution, think

about an education sector in your country)

1. Situating your institutionsa. Is learning analytics an important driver for your institution (give a

rating from 1 to 10)b. Is policy on ethics and data privacy is an important issue, for your

institution? (give a rating from 1 to 10)

c. Which of the three paradigmatic positions corresponds to your

institution. 2. Discussing the implications

a. Are the institutions policies in line with this positionb. Do interest groups have contrasting attitudes? Are there actual or

potential conflicts in the institution? c. What are the technical systems that constrain or determine your

institution’s ethical and privacy policies on data?d. What questions would you personally raise in your institution, about

technology or policy?