Analytics ILL Kerr Gardiner FIL Conference 2019 Analytics

Analytics & ILL Kerr Gardiner FIL Conference 2019

Analytics Current activity Contents Analytics and ILL Opportunities Considerations Futures

(Learning) Analytics?

metadata recommendations Analytics aren’t new!

predictions Analytics aren’t new!

behaviour Analytics aren’t new!

Learning Analytics – a definition “learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (Siemens, 2012)

libraries Learning Analytics aren’t new!

teaching Learning Analytics aren’t new!

learning technology & space Learning Analytics aren’t new!

Types of learning analytics? Management Reading lists Who’s using the service Trends in departments KPIs Learner Focussed on individual Help them make choices Help them study effectively Curriculum Improved learning activities Identify areas that work Quality rather than quantity Wellbeing Pastoral Mental health

Jisc Learning Analytics Service Learning analytics Institutional analytics Educational analytics Now Cognitive Analytics and AI Future Better retention and attainment VLE data + Student record system + Attendance data + Library data Personalised and adaptive learning A more efficient campus Buildings data + Learning space data + Location data Improved teaching & curricula Teaching quality data + Assessment data + Curriculum design data Content data + Learning pathways data Improving teaching & curricula Efficient campus Retention and attainment

By department Universities have lots of data – but in silos By service By student cohort By location

What’s changing? Digital landscape Student experience Supplier offerings Catching up

Current activity

• Commercials: Current activity • VLE • LMS • e. Book suppliers • Jisc: • Learning Analytics Service • Project work – e. g. LA Cymru • Working with suppliers • Data Hub

Supplier analytics

• Commercials: Current activity • • VLE LMS e. Book suppliers British Library • Jisc: • • Learning Analytics Service Project work – e. g. LA Cymru Working with suppliers Data Hub

Jisc Learning Analytics Service Jisc Learning Analytics open architecture: core Presentation and Action Alert and Intervention system Data Storage and Analysis Other Staff Dashboards Jisc Learning Analytics Predictor Student Consent Learning Data Hub UDD Transformation Toolkit Staff dashboards in Data Explorer Data Aggregator Plugins and/or Universal x. API Translator Data Collection Student Records Student App: Study Goal Self Declared Data VLE Library 19 Attendance, Presence, Equipment use etc….

What does it mean for ILL?

Know where you are Why bother? Keep relevant Improve service

Need to understand your institutional perspective LA from an ILL perspective Libraries are not always part of the discussion Types of ILL analytics

LA from an ILL perspective Data for management Data for learning • Informed decisions on document management • Impact and value • Improve the user experience • Usage patterns • Engagement • Citation use

Opportunities Re-think current data What other data could you get Engage with suppliers Digital landscape Be part of your institutional discussion You’re best placed to know what could be achieved

Considerations

Where to start! LEGAL ETHICAL DATA QUALITY INTERPRETATION INSTITUTIONAL BARRIERS RESPONSIBILITIES STUDENT VIEW

GDPR Privacy Legal & Ethical Data ownership Transparency Consent Anonymity ‘I’m not a number’ Change student behaviour Student motivation Built in bias

USW “learning analytics can be the basis for better quality conversations with students about their expectations and aspirations. ”

University of Gloucestershire • We will use Learning Analytics to help all students reach their full academic potential. • We will be transparent about data collection, sharing, consent and responsibilities. • We will abide by ethical principles and align with our university strategy, policies and values. • Learning Analytics will not be used to inform significant action at an individual level without human intervention.

University of Greenwich • We will use Learning Analytics to help all students reach their full academic potential. • We will be transparent about data collection, sharing, consent and responsibilities. • We will abide by ethical principles and align with our university strategy, policies and values. • Learning Analytics will be supported by focused staff and student development activities. • Learning Analytics will not be used to inform significant action at an individual level without human intervention. • We will actively work to recognise and address any potential negative impacts from Learning Analytics.

Data considerations IS IT AVAILABLE? IS IT COMPLETE? IS IT CORRECT? DISPARATE SYSTEMS MERGING WITH OTHER DATA

• Data interpretation

Barriers & Responsibilities Institutional barriers Responsibilities • Lack of conversations • Lack of headspace • Not a priority • What are the institutional and personal responsibilities if the data shows ‘something’

Futures

What’s happening DIGITAL EXPANSION CURRENT FOCUS

More Devices More connected Digital Expansion More data Student expectations Open access

Government Current Focus Jisc & Suppliers Institutional Students & Parents

The Big Questions What does the digital landscape mean for ILL? What does open access mean for ILL? Should ILL engage with this trend of LA?

Starting the journey…. Today has been about raising awareness You are the specialists Have conversations Ask your systems people what is possible

The times they are a changing… Will you?

Useful readings • Learning Analytics Explained / Niall Sclater • https: //www. jisc. ac. uk/reports/learning-analytics-in-higher-education • https: //www. jisc. ac. uk/learning-analytics • http: //cdn. nmc. org/media/2015 -nmc-horizon-report-library-EN. pdf