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Managing information: studying engagement through activity monitoring and traffic

lights

Professor Jo Smedley

Centre for Excellence in Learning and Teaching

January 2014

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Abstract

“The learner journey of every student is important from many perspectives. A USW initiative is enabling greater transparency

of data across the University on student engagement as a key element of maximising student success and enhancing retention. Examples of learner journeys will demonstrate activity monitoring from 2012/13

and 2013/14 through various USW technological data sources. Targets for retention will be explained using

the “traffic lights” system with reflections on performance.”

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Seminar Aims

• Raise awareness of the importance of retention

• Promote retention and success initiatives in local and global contexts

• Demonstrate learning analytics as an enhancement approach

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Performance Indicators: Retention and Success

• % of full time undergraduate degree students retained during year

• % of full-time undergraduate degree students progressing with clean passes at first sitting

• % of full-time undergraduate entrants returning the following year

• % of full-time undergraduate students completing a three year degree in three years

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Retention and success

• Belonging and attachment

• UK Higher Education market

• Student life cycle

• Learning Analytics

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Learning Analytics

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Target Setting

Induction

Traffic Lights

Data Mining

Activity Monitoring Learning

Analytics

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Questions

• About your course retention targets

• About student engagement

• About student retention

• About induction

• About learner analytics• Queries

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Summary

• Retention and success developments

• Learning Analytics community of practice

• Contributions for development* * * * *

Webpage: http://celt.southwales.ac.uk/does/sa/Email: jo.smedley@southwales.ac.uk

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Internal data

Module surveys x n

Student experience surveys x n

Big Data

• Internal data

• Activity monitoring

• External data

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External data

NSS

PRES

PTES

HESA

DLHE

International Student

barometer

Big Data

• Internal data

• Activity monitoring

• External data

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Big Data

• Internal data

• Activity monitoring

• External data

Activity monitoring

Blackboard Interactions

GlamLife interactions

Number of missed QMP Assignments

Googlemail Interactions

Logons from student areaTier 4 sign-ons

Estates info(entry etc)

Student Representation

Library interactions

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Activity Monitoring

• Technological interactions– BlackBoard, Googlemail, PC login, GlamLife

• Predictive equation– Bus./Comp./Music Tech/Drama/Graphics/Acc.– Profiles

• Data visualisation

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2012-2013

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2012-2013

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Induction

• Activities– Funded new induction activities to strengthen

student sense of “belonging”– Goal: improved student achievement, success and

retention

• Impact

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”Definite bonding between them.

And faster than in previous years... “

Geology

“The students have bonded particularly

well, they have been much more

willing to approach staff and confident

in how they interact with us” Chemistry

“Decrease in student

withdrawals attributed to the

induction activity” Forensic

Science

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Student Life Cycle

Raising Aspirations

Better Preparation

First Steps in H.E.

Moving Through

Student Success

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Student Life Cycle

• Are you aware of the main reasons why students withdraw from your programme?

• Are you aware of the steps they have to take in order to officially withdraw?

• What advice would you give to a student contemplating withdrawal?

Reference: http://www.ulster.ac.uk/star/resources/Anagnostopoulou_Parmar.pdf

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Learning Analytics: Techniques and Methods

• Statistics: hypothesis testing• Business Intelligence: effective reporting • Web analytics: technological interactions• Artificial intelligence/data mining: data patterns • Operational research: statistical methods• Social Network Analysis: online/offline links • Information visualisation: making sense of data

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Ref: Cooper, Adam. A Brief History of Analytics A Briefing Paper. CETIS Analytics Series. JISC CETIS, November 2012