learning analytics in higher education
TRANSCRIPT
1
www.iadlearning.com
Learning AnalyticsYour next movement towards the future
of education
Jose A Omedes
2
www.iadlearning.comWhat raises interest in LA area?
Analysis of around 300 posts on the topic
20.11%
11.41%
9.24%
8.70%8.15%4.89%
3
www.iadlearning.comIndex
• Defining Learning Analytics
• The three elements of analytics: data, analysis and action
• Learning Analytics maturity and the predictive bridge.
• Learning Analytics benefits and experiences
• A new learning era
• Implementing learning analytics
• Learning analytics ethics
• Key take aways
4
www.iadlearning.comLearning Analytics Defined
“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”
International conference on learning analytics
5
www.iadlearning.comLearning Analytics Defined
Learning analytics is the measurement, collection, analysis and reporting of data aboutlearners and their contexts, for purposes of understanding and optimizing learning and
the environments in which it occurs
DATA
Basic asset.Raw material
to be transformed into analytical insights.
ANALYSIS
Process to addintelligence to data usingalgorithms.
ACTION
Critical step towards achieving the purpose:
Understanding& optimizing learning
International conference on learning analytics
6
www.iadlearning.comLearning Analytics and EDM
Educational Data Mining (EDM)
EDM focuses on the development of methods for exploring the unique types of data that come from an educational context. […] the objective of data mining in education is largely to improve
learning […]
Handbook of educational data mining
Educational Data Mining (EDM) ≈ Learning Analytics
7
www.iadlearning.comLA and EDM on Google
8
www.iadlearning.comData Types
Internal External
PROVIDED / OBSERVED
Learning Analytics
INFERRED
DERIVED
LearningAnalytics
Algorithms
PROVIDED: Consciously given
OBSERVED: Recorded automatically
DERIVED: Produced from other data
INFERRED: Produced using analytics
Usually based on correlation between data sets
9
www.iadlearning.comData Sources
Demographic DataNot Sensitive
Sensitive
Name, birthdate, Sex
Ethnicity, Disability, Scholarship
Academic Data
Prior Performance
Current Performance
Learner Content
Maths: A, Physics: B, Electromagnetism: B
Course 1: Assignment 1: 89% Assignment 2: 56%Course 2: Assignment 1: 35%, Assignment 2: 64%
Essay 1, Group Report B, Chat 1 …
Learning Activity Data Activity Records
2017/10/02- 10:50 Logged into LMS2017/10/02- 11:50 Accessed Library Catalog2017/10/02- 12:00 Check out library book “Human body anatomy”
Educational Context Data Context InfoCourse 1: start: 2017/09/02, duration: 10 weeks, instructor: Allan GreenCourse 2: start: 2017/08/05, duration: 15 weeks, instructor: Mike Brown
External DataSocial Account Profiles
Other apps info
Facebook, Twitter, Google +
eBook apps, xAPI enabled apps …
10
www.iadlearning.comData Sources
SIS(Student Information
Systems)
LMS / LRS(Learning Management
System)
Other Internal Systems
External Systems
Learning Analytics go beyond the LMS !!!
11
www.iadlearning.comAnalysis
Process of obtaining insights from data based ona set of statistical and machine learning based algorithms
ANALYSIS
Data Learning Analytics
12
www.iadlearning.comAnalytics maturity model
analysiscomplexity
(imposes demands on
data: volume, type, timeframe,
etc.)
Diagram Source: https://www.ibm.com/developerworks/community/blogs/jfp/entry/the_analytics_maturity_model?lang=en
13
www.iadlearning.comPredictive Analytics Bridge
DescriptiveDiagnostic
Predictive
AlgorithmsData
ReactiveUnderstand the past
ProactiveInfluence the present
14
www.iadlearning.comAction
Is the overall target of the learning analytics process
No action = Failure
Having in place the internal processes that lead to action is critical
CultureLeadership
15
www.iadlearning.comIs it worth? Benefits
Reduce drop out rates
Increase learners’ performance
Targeted proactive tutoringIncrease retention
Targeted proactive tutoring
Offer personalized learning experiencesAdaptive Learning / Adaptive content
Understand content consumption patterns & quality issues
Improve content & course quality
Instructional design
16
www.iadlearning.comIs it worth? Benefits
Cost efficient allocation
Understand which resources work and which don`t
Data-driven investment decisions
Identify and promote student success factors
Create student structured pathways towards graduation
Proactively drivesuccess
Curriculum design
17
www.iadlearning.com
Source: https://www.jisc.ac.uk/reports/learning-analytics-in-higher-education
Does it work?
18
www.iadlearning.comDoes it work?
Source: https://www.jisc.ac.uk/reports/learning-analytics-in-higher-education
Case studies show:
• Validity of the predictive models applied to learning analytics systems
• Interventions with at-risk students are effective• There are other benefits to taking a data-driven approach
19
www.iadlearning.comA new learning era … or not?
Learning Analytics: The coming third waveMalcolm Brown, Director, EDUCAUSE Learning Initiative
The Predictive Learning Analytics RevolutionEDUCASE ECAR Working Group Paper
Adaptive Learning Holds Promise for the Future of Higher Education BARNES6NOBLE at EDUCATION DIVE
20
www.iadlearning.comReality …
The world is more and more data-driven … Education is no exception.
“Learning analytics” is an important tool to improve education and to make high education institutions more competitive.
“Learning analytics” are successful only if there is action as a result of its implementation.
Institutions must cross the predictive analytics bridge to benefit from a new way of driving students success.
21
www.iadlearning.comThe decision automation leap
Prescriptive PrescriptiveHuman supported Fully automated
Learning Analytics
22
www.iadlearning.comThe decision automation leap
Impressive and completelyautomated
Really impressive !!!80% Unknown …
Never forget the human factor in education !!!
23
www.iadlearning.comImplementing Learning Analytics
How do I implement my learning analytics project?
24
www.iadlearning.comImplementing Learning Analytics
1 Start smallDurationScope
2 Don’t focus on technology Focus on specific problems you want to address
3 Go after quick winsShow there are positive outcomes and possible impact
4Involve from day one all the critical stakeholders
Don’t forget the people that would use the technology in the end
25
www.iadlearning.comLearning Analytics ReadinessUnderstand whether institutions are ready for learning analytics from multiple dimensions
LEARNING ANALYTICS READINESS JISC
Culture & Vision
Ethics & Legal Issues
Strategy & Investment
Structure & Governance
Technology & Data
LEARNING ANALYTICS READINESS INSTRUMENT
Culture & Processes
Data Management Expertise
Data Analysis Expertise
Governance / Infrastructure
Readiness perception
Kimberly E. Arnold
Steven Lonn
Matthew D. Pistilli
ANALYTICS MATURITY INDEX
26
www.iadlearning.comWhat is Readiness about?
Strategy & Vision
Culture
Governance and Processes
Ethics and Legal Issues
Investment
Technology
Data
ACTION
ANALYTICSMATURITYINDEX
27
www.iadlearning.comDon’t get trapped by the readiness loop
Strategy&Vision
Culture
GovernanceandProcesses
EthicsandLegalIssues
Investment
Technology
Data
ACTION
Readiness Assessment
1 Startsmall
2 Don’tfocusontechnology
3 Goafterquickwins
4Involvefromdayoneallthecriticalstakeholders
Start your seed project!
28
www.iadlearning.comTechnology Challenges
Data Capture Not all educational interactions happen in a digital environment
Predictions Accuracy All statistical processes draw conclusions subject to an estimated error
Partial View Learning processes go beyond what data tell us
Data Literacy Analytics consumers need the skills to interpret analytics properly
Data Variety Combine data coming from multiple sources and systems
Comparable AnalyticsNot all systems use same algorithms or measure the same wayOpen standards?
29
www.iadlearning.comLearning Analytics Ethics
Source: Accenture Tecnology: https://www.accenture.com/us-en/insight-data-ethics
Data Supply Chain
DATA ANALISYS ACTION
30
www.iadlearning.comLearning Analytics Ethics
DATA ANALISYS ACTION
• Consent
• Privacy
• Access
• Validity
• Right to opt out
• Safety
• Transparency
• Accuracy
• Validation
• Systematic &
random errors
• Obligation to act
• Failure to act
• Adverse impact
• Abuse / Gaming
• Discrimination /social
status
• Pedagogical impact
Complete ethical issues taxonomy by Sclater: https://analytics.jiscinvolve.org/wp/2015/03/03/a-taxonomy-of-ethical-legal-and-logistical-issues-of-learning-analytics-v1-0/
31
www.iadlearning.comKey Take Aways
• Learning analytics are an important asset for institutions providing important benefits but also competitiveness
• Institutions must cross the predictive analytics bridge and start influencing the future by changing the present.
• Learning analytics are about action. No action = Failure. Get ready to act and change !
• Launch your analytics seed project: start small, don’t focus on technology, go after quick wins, involve stakeholders.
• Develop your code of conduct and run analytics protecting all the stakeholders and specially the students.
32
www.iadlearning.comWhat raises interest in LA area?
Analysis of around 300 posts on the topic
20.11%
11.41%
9.24%
8.70%8.15%4.89%
33
www.iadlearning.comFor more info …
Thanks a lot!Jose A Omedes
Research and Development Director