Learning analytics introduction

As described by Dietz-Uhler and Hurn (2016, p. 21,22): ‘Learning analytics can provide insights into what is happening with the learner in nearly real-time. Armed with this information, faculty can make suggestions to students that will help them succeed (Long & Siemens, 2011). For example, if a student has not read a discussion board post for a certain period of time, this may suggest to an instructor that the student needs an intervention or a nudge. Similarly, if a typically successful student suddenly performs poorly on an assignment, the instructor can intervene and seek to determine why the student performed poorly. Or, if a student repeatedly asks questions about the material or about course procedures, an instructor can examine usage data in an LMS and determine if, when, and how often the student has accessed the relevant LMS tools.’
Learning analytics can be a useful tool in supporting student engagement and retention. There are however some ethical considerations related to the use of learning analytics which include discussions around transparency, consent, choice, accountability, privacy and security (see, e.g., Slade and Prinsloo 2013; Pardo and Siemens 2014).
It is important to highlight that the analytics offered by Blackboard (as well as other tools) are purely indicative of the very specific metrics they report on and should not be used to make assumptions about the student. In line with The Open University’s policy on ethical use of learning analytics: ‘Students should not be wholly defined by their visible data or our interpretation of that data.’ (Open University Sep 2014, p. 8).
Blackboard Ultra offers a range of learning analytics which can be broadly categorised into Student Activity Analytics and Assessment Analytics.
Student Activity Analytics
Course Activity
The Course Activity is accessible via the Analytics tab and provide a high-level overview of the student engagement on the course which includes Missed Due Dates, Hours in Course and Days Since Last Access.

You can set Alerts to notify you when a student does not meet minimum criteria for online engagement.

Student Activity
If you click on the Analytics tab and then on a student’s name you will be able to access an overview of their individual activity on the course which includes their Marks, Progress and Activity log. You can also click on the Student Activity button in the top right corner to access more detailed analytics regarding the student’s activity per week (this is also accessible via Gradebook by clicking on a student’s name).

Student Progress
If Progress Tracking is enabled on your course, you can also see student engagement with it. To view progress of an individual, go to the Analytics tab, click on a student and go to the Progress tab. To see an overview of the entire cohort’s progression with individual items and sections, click on the three dots next to them and select Student Progress (this does not include assignments, tests, discussions and forms).

Assessment Analytics
Question Analysis
Go to the Analytics tab to find the Question Analysis functionality which provides analytics on Blackboard Assignments and Tests including statistics on overall performance, assessment quality and individual questions (this is also accessible via Gradebook by going to Markable Items and clicking on the three dots next to an item).

Question Analysis can also be accessed through the content area by clicking on the three dots next to a relevant item.

Items Statistics
Go to Gradebook and access the Markable Items view, click on the three dots next to an item and choose Statistics to access Mark Statistics, Marking Status and Grade Distribution.

Student Activity (with Assessment)
You can also access Student Activity overview for a specific assessment or test through the content area by clicking on the three dots next to a relevant item.

Students’ experience
As argued by Slade and Prinsloo (2013, p.1519), as opposed to students being producers or sources of data, ‘learning analytics should engage students as collaborators and not as mere recipients of interventions and services (Buchanan, 2011; Kruse & Pongsajapan, 2012)’.
Even though the analytics offered by Ultra are not visible to students, it is worth to consider how to involve students as co-interpreters of their own data which could promote its transparent use and support student self-regulation by helping them to monitor their own progress. We would like to encourage you to have an open discussion with your students on how you use analytics to support their learning.
Along with the Student Developers, working on the Blackboard Ultra transition project, we developed an infographic for students which explains what analytics are and how they can be used. The infographic is included in Student Guide to Blackboard accessible from each Blackboard unit.
Read more about Analytics in Blackboard Ultra
References
Dietz, B.,. & Hurn, J.E.(2013). Using learning analytics to predict (and improve) student success: A faculty perspective. Journal of Interactive Online Learning. 12, 17-26.
Long, P., & Siemens, G. (2011, September/October). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 31-40.
Open University Oct. (2014). Ethics use of student data for learning analytics policy FAQs. Retrieved from http://www.open.ac.uk/students/charter/sites/www.open.ac.uk.students.charter/files/files/ecms/web-content/ethical-student-data-faq.pdf
Pardo, A., & Siemens, G. (2014). Ethical and privacy principles for learning analytics. British Journal of Educational Technology. 45 (3), 438-450. https://doi.org/10.1111/bjet.12152
Slade, Sharon & Prinsloo, Paul. (2013). Learning Analytics Ethical Issues and Dilemmas. American Behavioral Scientist. 57. 1510-1529. https://doi.org/10.1177/0002764213479366