Next steps in Learning Analytics

Groep jonge mensen met elkaar in gesprek rondom een tafel met papieren

Introduction

Learning analytics: analysing data to improve study success. It is a hot topic at Erasmus University and a dedicated project team consisting of representatives of the Schools, the Community for Learning & Innovation (CLI) and the office of the Chief Information Officer are working on the ‘next steps with learning analytics’.

Universities gather lots of data, for example for research, education and to run their operations. With the availability of all that data, opportunities for improving education and study success present themselves. The possibilities of learning analytics look very positive indeed, both for students, teachers, researchers and universities. However, we also need to have an eye on the downside and treat the privacy of all concerned with the utmost respect.

EUR project 'Next steps in learning analytics'

The EUR is currently undertaking several sub projects that link with learning analytics. We are contributing to the national acceleration plan “educational innovation with IT’ sponsored by the Ministery of Education, Culture and Science. As described on the corresponding website:

What are the preconditions that make the use of learning analytics a success? What is needed at an individual level, the institution level, and what is needed at the national level? Aspects that are important are, for example, types of educational data, data quality, reliability of analyses, privacy and ethics, security, personnel preconditions, organisational support, applicable insights and target groups, and (national) scientific research.

The sub projects

Deliverable/Goal

‘Goalsetting functionality’, eg. an App or website, for students. Students can use the app to clearly formulate their personal and/or study goals and link them to actions/reminders/nudges.

Deliverable/Goal

The course shall be focused on the usage of Learning analytics modules within Canvas. The course will focus both on ‘how to do it and how does it work’ and on ‘how can I use this to further improve my course from a didactical perspective?’

Deliverable/Goal

Giving teachers access to the ‘out of the box’ Learning analytics functionalities/modules of Canvas and to evaluate their findings in using those. Depending on teachers’ evaluations, we will either continue the usage of these modules, and/or look for additional options.

Note: the initial planning was to also give students access to the ‘out of the box’ functionalities in Canvas. But we found out that this would mean that students could also access data of other students. At this moment it is not possible to restrict that access so, for privacy reasons, we decided (for now) to only grant access to teachers.

Deliverable/Goal

Based on insights at the VU (‘Free university of Amsterdam’), Erasmus wants to create their own insights into the different types of ‘clusters of students’ that study at our University. The end goal is to have a visual representation of student clusters at Erasmus.

Deliverable/Goal

A dashboard that helps teachers and those who support education, to see in a glance how a specific course performs in the online environment, and what can be done to further improve that course didactically.

Deliverable/Goal

One repository that Erasmus researchers can turn to for high quality data to do research into education.

Deliverable/Goal

Creating of dashboards/reporting that gives insight in the progress towards the goals Erasmus has set for the quality of its education and that supports management decisions about education.

Deliverable/Goal

We need not explain that we need to use the data of our students and employees in the utmost responsible ways! The Privacy and Ethics board is set up to ensure that the different sub projects in this list use personal data in a responsible way.

Furthermore, the board will develop criteria and ways of working to structurally watch over the usage of Learning analytics at Erasmus.

Deliverable/Goal

Facilitating of the involvement of students with Learning analytics at Erasmus.

Within Canvas a separate course on Learning analytics is already available. We are looking at ways to involve students to create relevant information within that course.

Deliverable/Goal

Provide insights in the usage and/or successes of the online education offerings at Erasmus. Creating a platform where all reports and dashboards can be found to improve insights and hence the quality of our online education.

Deliverable/Goal:

Support the university with insights in (the effect of Covid-19 on) the development of student applications.

Questions?

We can imagine you have questions or comments about this. Check the FAQ below or contact us via learninganalytics@eur.nl.

We treat your privacy with the utmost respect. We have set up a Privacy & Ethics Board to discuss whether we’re steering the right (ethical) course and to advise us on privacy measures to take, such as using anonymized data where we can.

A combined taskforce with representatives of the Schools, the Community for Learning & Innovation (CLI) and the office of the Chief Information Officer (CIO) is undertaking several sub projects deriving from the input that the EUR students, researchers/lecturers and policy advisors gave last summer. Visit our web page to learn more about these projects.

When we talk about Learning Analytics, we mean using all sorts of educational data in order to improve education. Examples are as broad as predicting the enrolment of new students in a next academic year or enabling personalised learning through a digital coach that helps you in goalsetting during your studies.

By using Learning Analytics, we can contribute to future-oriented education, one of the seven pillars in the EUR strategy 2024. We can improve education by:

  • giving students insight in their learning process and by advising students to improve their learning process
  • giving lecturers/researchers and policy makers more insight in their educational process and by advising them in this
  • Improving enrolment, progression and graduation of students by using anonymized internal and external data.

Interested in the first findings of EUR students, researchers, lecturers and policy advisors during two conferences in summer 2019? They have been summarised in these visuals.

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