learning analytics bij de universiteit utrecht

Learning analyticsat

Utrecht UniversityJohan Jeuring

Utrecht University De Onderwijsdagen November 8, 2016

Learning analytics is the measurement, collection, analysis and reporting of

data about learners and their contexts, for purposes of understanding and

optimising learning and the environments in which it occurs.

Call for Papers of the 1st International Conference on Learning Analytics & Knowledge (LAK 2011)

Optimizing learningStudie-adviseur

Teacher

System/student

And not

Students work hard before a deadline

Students look most at videos about difficult topics

Powell, Stephen, and Sheila MacNeill. Institutional Readiness for Analytics A Briefing Paper. CETIS Analytics Series. JISC

1. for individual learners to reflect on their achievements and patterns of behaviour in relation to others

2. as predictors of students requiring extra support and attention

3. to help teachers and support staff plan supporting interventions with individuals and groups

4. for functional groups such as course team seeking to improve current courses or develop new curriculum offerings

5. for institutional administrators taking decisions on matters such as marketing and recruitment or efficiency and effectiveness measures

What do we do with learning analytics at Utrecht University?

A lot!

• Blended learning and learning analytics project within Educate-IT

• Portfolio in master veterinary science

• European WATCHME project on workplace-based feedback and assessment and professional development by means of learning analytics

• Many more experiments, PhD research, tooling (myMediasite, Scalable learning, DWO, Communicate, FeedbackFruits, …)

Nothing

Utrecht university has an institutional policy for the role of ICT in education (Educate-IT), but

there is no institutional infrastructure for learning analytics (yet)

Ownership of dataSummative assessment data is owned by the university, and may be used for awarding grades, assessment of programs

Other data from student activities is owned by the student and the university, and may be used for optimizing learning and teaching

The data is not owned by the tool in which students perform activities

Location of data

In the tools students and teachers use

Accessing the data

• Through the tool

• Calling

• Using an API

Opinion 1

Don’t use a single tool (Blackboard, Osiris, myMediasite) for learning analytics across an institution

Opinion 2

All software used in education should provide access to student activity data through an API

A learning analytics service• Collect student activities

• Facilitate creating a student / knowledge model

• Map activities on knowledge model

• Visualize knowledge / progress for students and teachers

Evolution and biodiversity4. Wat zijn de belangrijkste veranderingen die geleidelijk in de vinkenpopulatie zullen plaatsvinden? a. De eigenschappen van elke vink binnen een populatie zal geleidelijk veranderen. b. Het aandeel van vinken binnen de populatie die andere eigenschappen hebben, zal veranderen. c. Succesvol gedrag dat de vinken hebben geleerd, zal worden doorgegeven aan de nakomelingen. d. Er zullen mutaties voorkomen, om aan de behoeften van de vinken te voldoen tijdens de gewijzigde omstandigheden.

Interpretation

A. Essentialistic (misconcept)

B. Correct

C. Anthropocentric (misconcept)

D. Teleologic (misconcept)

Technologies• Learning Record Store

• xAPI

• Student model (but also group profile, and predictions based on previous groups)

• Bindings with various tools: Remindo, Scalable learning, Presenter’s wall, Communicate, Traintool, myMediasite, …

Student activities

Learning record store

xAPI

RESTful web services

HTTP POST or GET statements, results are stored in an LRS

Recipes

Build (or buy) a separate learning analytics service/infrastructure

Opinion 3

Opinion 4

For institutional learning analytics: use the rich data already available: grades, assessment results, etc.

Don’t start with collecting data about students accessing on-line material, watching video’s, etc.

Conclusion• Develop an institutional policy for learning

analytics

• Watch out for tool-specific learning analytics

• Develop or buy a separate learning analytics service and move software providers to provide the relevant data

• Start with using data that is already there, and is easy to interpret