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Analytics for Learn for lecturers
  

This page contains information about Analytics for Learn (A4L) and links to additional guides for lecturers. We start with background information about the 'Early Warning Signals with Blackboard Analytics for Learn' project. Followed by showing you the benefits of A4L for you as a lecturer. Then we explain how you can enable the reports for yourself and the students in your course. Then we show examples of the four reports that are available to you in your course environment. If you were looking for information for study advisors please go here.

Why do we need early warning signals?

Some students encounter problems at the start of their studies but often this becomes visible when the exam (at the end of the course) is not passed. By signaling suboptimal study behavior in the first weeks of a course study and providing timely interventions behavior can be changed. Interventions can be diverse such as advice from a study advisor, extra guidance from a lecturer, or students studying more or differently. Analytics for Learn (A4L) can provide early warning signals. The use of signals in higher education in the Netherlands is relatively new. Research in the US (Purdue University) has shown a strong relationships between stent behavior in the electronic learning environment and study success. The EWS project is part of the large project Progress Volg.

What is Analytics for Learn?

Analytics for Learn is a system from Blackboard that provides course analytics in a report format. Information about activity and grades in the electronic learning environment (Nestor/Blackboard) will be combined with information from the Student Information System (SIS/Progress.NET). A4L transforms this information into insightful reports for lecturers, students and study advisors. Reports for lecturers and students are accessible in the course environment, reports for study advisors are accessible from a RUG analytics environment. Reports can show the activity and/or grades of a single student compared to the average of all other students in the course. It is important that teaching assistants, study advisors or other lecturers have the 'instructor of assistant' status. If they are enrolled as students their actions will be incorporated in the reports.

Why is Analytics for Learn interesting to me?

Analytics for Learn (A4l) gives you the possibility to analyze your course and students' behavior in more detail. You can identify students who not active in the course and see the relationship between their activity and their performance (based on the grade center).. By examining different statistics regarding your course and its contents you can both assist students in earlier stages of the course, as well as improve the content or structure of your course.

Why is Analytics for Learn interesting for my students?

Students can access a report in their course environment which shows them their own activity and grades compared to the average of the other students in the same course. Students can reflect on their activity and performance and increase their efforts if necessary or seek support.

The EWS project is explained to students in more detail during a 2 minute movie which is available on YouTube via: https://www.youtube.com/watch?v=j0ZkDiSDtGo

Enabling the Analytics reports for students and lecturers.

Analytics for Learn is currently only used within the pilots of the Early Warning Signals project it is turned off by default in all courses. Please use these instructions to enable this functionality. Reports are only visible to your students and you if you turn the functionality on. Please follow these instructions to make the course report available to your students. Please follow these instructions to create your course reports for you and other course lecturers.

Which reports are available for lecturers?

When using Analytics for Learn you can generate several reports, each of which uses different information for a specific purpose. These reports allow you to examine the behavior of your students in the electronic course environment by giving an overview of their average activity and performance. It also shows you how (and if) the students use the information you provide to them in the course environment. This information can be used to improve your course. Here you find the reports available to lecturers.

During the pilot lectureres have access to the reporting services. For information on how to access these reports, please follow these instructions.

Where can a student find his/her Personal Course Report and what does it look like?

A students' "Personal Course Report" is accessible from a page in Nestor. A short introduction to the EWS project and the EWS movie can also be found on this page. An example of this page in Nestor can be found here. An example of a student report can be found here.

A note of caution

The aim of the A4L reports witing the context of the Early Warning Signal project is to provide as early as possible signals that might reflect an increased risk for study-related problems.

Please bear in mind when interpreting the reports or discussing them with a student or colleague that the report shows no hard evidence of student's efforts nor time spend studying. If all course materials are available at the start of a course, a student can download all content in the first week. He/she can study this content for hours (outside of Nestor) or not even look at the material at all. Not downloading the material doesn't mean the student has not studied the content because he/she might have received a printed version from a fellow student. In addition, a student who seems inactive in the digital learning environment might follow all classes, makes extensive notes and is actively involved in discussions within and outside class.

Questions and support

If you have any technical questions please contact us at nestorsupport@rug.nl or call us at 050 363 8282.

If you want to know more about Analytics for Learn or the Early Warning Signals project or if you want to take part in the pilot, please Esther Bouma (e.m.c.bouma@rug.nl or 050-3636434).

Links referred to:

1/ Enabling Analytics for Learn in your course

2/ Making the student report available to your students

3/ Making course reports available to you and other course lecturers

4/ Course reports explained

5/ Example of a student report