Since 2014 Information Services have been exploring some Learning Analytics options within the VLEs. Projects and tools include those which allow students to see some of their own data, to help them understand their activity and learning patterns.
In order to function, a Virtual Learning Environment has to identify each user on login, and match that user identity with actions, e.g. opening a file, posting to a discussion board, completing a quiz. VLEs also record information such as login times, login duration, location, and activity whilst logged on, attendance, formative and summative grades, and other activity directly related to coursework. Only some of this data is available to staff users through the VLE interface.
Only teaching staff, designated administrative staff, and designated technical support staff can access some of this data inside the VLE. As part of our “Student Data from VLEs” project we have developed tools to surface some of this data for students.
All of this data is held securely inside the VLE database. Some grades, once finalised, may be transferred into student systems (such as EUCLID) and thus into the student transcript: this is managed locally by schools.
In addition to the ways in which the VLE’s tools call on this data for core functionality, you can access a variety of reports and tools to gain an overview of student activity within your course, to analyse the effectiveness of specific modules or tools, and alert you to items in need of attention. This may include an alert if an individual student has not accessed the course, or a specified part of the course, for some time.
You may also extract some activity data on individual students in order to discuss that data with that student, including identifying potential support needs.
Some anonymised and aggregated data, such as the class average score for a test, may be made available to all students on the course.
You may not extract the data from the VLE and hold it elsewhere in a potentially insecure area.
You may not extract the data and use it for purposes other than direct student support or course development. For example, any research which you may wish to do on patterns of activity as reflected in the student data for your course, would be regarded as a separate research project and would require the necessary ethics committee approval, including a statement on data management and planning, as with any other research involving personal data.
We have developed a "Course and Student Performance" self-enrol course for staff which illustrates the many built-in tools and reports for extracting and analysing data about content and student activity. This includes the Learn "Data for Students" tool developed for Learn.
To enrol, login to Learn and go to the "self-enrol" tab. The course is listed in the Staff self-enrol module.
We have developed a self-enrol course that explains the different reporting tools available for staff to access and interpret data collected by Moodle. This course contains some example data from demonstration students that will show you how this data might look and how it could be used in your course design and supporting your students. This includes understanding what data can be shared with students.
To self enrol into this Moodle course you will need to be registered as a Moodle user. You can login to Moodle using your EASE account or a manual login if applicable.
Learning Anaytics Community Exchange (LACE) EU project