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The Sixty Minute (Data Dashboard)

Makeover – in 1 hour 30 minutes!

Marieke Guy, QAA

Jon Rathmill, University of Kent

Tuesday 11th July 2017

16:00 – 17:30

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Introductions

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• Data analyst at Quality Assurance Agency for higher

education (QAA)

• QAA mission is to safeguard standards and improved

the quality of UK higher education, wherever it is

delivered in the world

• Does this by: delivering elements of revised operation model for quality assessment

managing assessment process for TEF

regulating Access to HE qualification

maintaining UK Quality Code

advising on degree awarding powers

carrying out review of Alternative Providers

Strategic international work (TNE)

Marieke Guy - QAA

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Jon Rathmill - University of Kent

• Planning Analyst in the Planning and Business

Information Office (PBIO)

• Previously worked in FE college MI department

• PBIO is responsible for the provision of management

information, both external and internal, on the

complete range of student academic activity.

• Migrating to use of Qlikview to display data and

statistics. Allows users to filter and shape reports to meet their needs

Quicker to disseminate data

Visualisations improve understanding

Standardised design across dashboards to help users

Allows greater data control – only certain users see certain things

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Overview of the Workshop

Time Session

Introduction session

16:00 – 16:30 Data in Higher Education (MG & JR)

Practical session: Sixty second dashboards

16:30 – 16:45 User stories (All)

16:45 – 17:00 Data sources (All)

17:00 – 17:20 Designing a dashboard (All)

Show and tell and feedback

17:20 – 17:30 Delegates present their dashboard (All)

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Data in Higher

Education

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Data Landscape

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• DLHE – Destination of Leavers in HE

• NSS – National Student survey

• LEO – Longitudinal Education Outcomes

• POLAR – Participation of Local Areas

• PRES – Postgraduate Research Experience Survey

• KIS – Key Information Sets

• HE-BCI – HE Business Community Interaction

• JACs – Joint Academic Coding System

• HECos – HE Classification of Subjects

• CAH – Common Aggregation Hierarchy

• HESA – Higher Education Statistics Agency

• TEF – Teaching Excellence Framework

• REF – Research Excellence Framework

Acronyms…

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“The HE sector has always been a data-rich

sector, and universities generate and use

enormous volumes of data each day.

However, the sector has not yet capitalised

on the enormous opportunities presented by

the data revolution, and is lagging behind

other sectors in this area.”

From Bricks to Clicks report, Higher education Commission

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• Data everywhere in the HE sector:

Collection by HESA and through surveys

Use in TEF, REF, league tables

• Data collection/use is (to some extent) in hand

(HEDIIP/data Futures) but data analysis isn’t

• Data ownership and management is slowly evolving

• Data seeping in to all aspects of HE provision and

decision making: programme design, retention, WP,

learning analytics

• Many staff concerned about their data capabilities

• Agencies need to work together (Bell review)

Data in HE

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“A business intelligence dashboard (BI

dashboard) is a software interface that

provides preconfigured or customer defined

metrics, statistics, insights and visualisation

into current data.

It allows users to view instant results into

the live performance state of business or

data analytics.”

Technopedia

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Where the Work is - IPPR

http://wheretheworkis.org/ - Institute for Public Policy Research

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Some Unis doing really well…

Liverpool HopeDe Montfort

Gloucestershire

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Business Intelligence

Analytics Lab Project

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• HESA data: Summary data from the HESA Student, Staff and Finance submissions

HE Business and Community Interaction (HE-BCI), Estates Management

and Destinations collections

Performance Indicators, Student Staff Ratios, Aggregate Offshore Record

(AOR)

• Heidi - web-based management information

service developed for accessing, extracting and

manipulating data

• Heidi plus – New BI service, more granularity,

more visualisation opportunities

, Heidi and

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• National analytics experimentation project led by

Jisc and HESA

• Aim to refresh Heidi Plus content with insights from

a wide range of alternative data sources

• Teams comprise staff from multiple institutions

• Teams themed – agile approach

• Working towards ‘proof of concept’ dashboards

• These dashboards will be further developed by

HESA

• 130 people, 70 institutions, on 6th round

BI Analytics Labs

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Labs Overview

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Team member Institution

Tom Wale University of Oxford (Product owner )

Jon Rathmill University of Kent

Carolyn Deeming Plymouth University

Marieke Guy QAA

Elena Hristozova University of Nottingham

Myles Danson Jisc (Scrum Master)

Kris Popat Cetis (Data Wrangler)

Neil Richards HESA/Jisc (Data viz)

Team Tom

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• Employability (including TEF planner)

• Staff

• Market insights

• Library resources

• Finance

• FE – in particular manufacturing and how it links to

local FE colleges

• Research

Theme areas

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Research Student Experience

I want to: Understand the progress and

completion of my research students,

and the issues that they face

So that I can: Ensure that my institution

can improve its research student

experience and improve the proportion

graduating, and how this compares with

others

Brexit and International Exposure

I want to: Understand my exposure to the EU

by subject for research in terms of research

students, staff and research income

So that I can: Understand what gaps I might

have should European students, staff and

income dry up, and whether this is particularly

different from other institutions

Preparation for REF

I want to: Understand how my

institution’s activity since REF14

contributes to REF21

So that I can: Understand how my

institution’s performance compares

with others operating in the same

subject areas

User stories

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• Low shelf data Publicly available & openly licensed

Vast, distributed, no common vocabulary, complex

May be patchy

Not designed to be combined with other data

Examples include demographic, geo-spatial, international, census

• High shelf data Closed licensing - available by subscription or is locked to third

party organisations

Examples include funding and regulatory, local councils, Government

bodies, fees and admissions, careers and trajectory, current study data,

staff, research, financial, estates or even institutions themselves

Low shelf vs high shelf data

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• HESA Student

• HESA Staff

• HESA Finance

• HEA – PRES data

• Eurostats

http://ec.europa.eu/eurostat/web/education-and-

training/data/database

• EU Community Research and Development

Information Service (CORDIS)

• RCUK – funding awarded – Gateway to Research

Data sources used

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BI Labs

Dashboards

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Kent Qlikview

Dashboards

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Practical session –

Designing dashboards

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Practical:

User stories (All)

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• Brainstorm possible themes

• Decide on a theme to be explored

• Craft up to three user stories for your dashboard

using the user stories template

In your groups

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User Stories

• As a: <user>

• When: <context>

• I want to: <feature>

• So I can: <benefit>

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Practical:

Data Sources (All)

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• Brainstorm HESA data fields that may be useful

(student, staff, finance, other)

• Brainstorm possible external data sources to use

• Have a look at: http://heidi-ckan.dev.jisc-betas.net/

• Think about connections between your data sets

(unique IDs)

• Think about the possible challenges your choices

may pose: High shelf vs low shelf data

Data quality, availability, licence

Time, cost, date

In your groups

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Practical: Designing

a Dashboard (All)

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• Pick an artist

• Agree on one user story to develop

• Create some sketches of what your dashboard

could look Think about potential users

Consider usability, layout, colour

Consider filters, searches, titles, legends, navigation

Sense check that it tells an honest story!

In small groups

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“It’s not good enough for there to

be a looming fear in the sector; we

should have an open forum for

debate about the detail of data, and

the best ways to use it.”

Ant Bagshaw, Wonkhe

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• Make friends: Find out who deals with data in your organisation

Find out what tools they use

Build up links with them

• Think about data: Start thinking about data, visualising data and the complexities of data

What data do you have? Google analytics, other?

Are there opportunities for embedding it on your website?

• Watch out for the M5 (Jisc, HESA, QAA) data

conference (3rd November – London)

• Get your staff involved in the BI Analytics Labs

work (Myles.Danson@jisc.ac.uk)

Future activities

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Resources

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• BI Analytics labs website: https://business-intelligence.ac.uk/

• BI Analytics labs data catalogue: http://heidi-ckan.dev.jisc-betas.net/

• Tablea public: https://public.tableau.com/s/

• Tableau HE: https://www.tableau.com/solutions/topic/education-

higher-ed

• The Seven Hats of Visualisation Design: A 2017 Reboot –

Slideshare – by Andy Kirk:

https://www.slideshare.net/visualisingdata/the-seven-hats-of-

visualisation-design-a-2017-reboot

• Neil Richards Tableau Public:

https://public.tableau.com/profile/neil.richards

• Subscribe JISC-HESA-BUSINESS-INTEL’ to listserv@jiscmail.ac.uk

• Twitter @HESA @jisc #hesajiscbi

Useful resources

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• All images from: Courtesy of Jisc and HESA

Pixabay – CC0 - pixabay.com/

or author’s own

Credits

qaa.ac.uk

enquiries@qaa.ac.uk

+44 (0) 1452 557000

© The Quality Assurance Agency for Higher Education 2016

Registered charity numbers: 1062746 and SC037786

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Thank you