After a long period of waiting, and a short period of complaining, I’ve received my personal data from UBC’s Learning Management System (LMS), Blackboard Connect. I’m impressed with, and unsettled by, the amount of data that I’ve been given. It’s from every course at UBC that I’ve ever been enrolled in, including those that I dropped before classes began, and those that never even used Connect.
The documents include a 212-page PDF of Course Reports. These are the records that instructors can generate from within the Connect environment and evaluate student performance. They are a component of the Blackboard Learn tools that offer this lofty promise: “As you monitor student performance in your course, you can ensure all have an opportunity for success.”
Below are screen shots from that document. They show what an instructor sees when assessing student performance and assigning grades like participation through Connect. It demonstrates how students can be unfairly evaluated and is evidence of how Connect is failing to deliver upon its ambitious promise.
Course Activity Overview
The most important statistic in this image is the average time per user displayed on the bottom. This gives the instructor an idea of how an individual student’s performance relates to the rest of the class. In the case of my course, students were using Connect for an average of 19.48 hours each week. However, this statistic might be very misleading for instructors.
The practices for each student using Connect is heavily varied. Some may leave their browser windows open for extended periods of time, working on assignments and writing discussion board posts from within Connect, which will amount to a greater average time. Whereas others might complete their work outside of Connect and enter only briefly to submit their completed work.
How might these varied practices impact the participation grades of different students? Perhaps, a student with limited access to the internet would be discriminated against based on this performance tool as they would perform poorly compared to a student with a constant internet connection, who can login into Connect as frequently as they like. As well, a student who simply engages differently with Connect may receive a poorer grade in reflection of their practices and not their participation.
The above image shows my performance as compared to the class average. The blue bar represents the amount of time that I spent within Connect and the orange line is the average threshold, which I marginally surpassed. I would expect that instructors would take a cursory glance at this graphic to get a sense of where students are situated within their class.
In terms of my practices within Connect, I would do very little actual reading or writing within the system. I found that writing in the small window for discussion board posts and journal entries to be constraining and difficult. I also didn’t like going through the burden of logging in each time I needed to access a reading. So I’d often log in, download the readings, check what had been posted, and then write my posts and do my readings from outside of Connect. But during this time of relative inactivity, to my great benefit, I’d leave Connect open. If I hadn’t, my average time in course would be significantly lower.
In this course, I was slightly above the average in terms of time spent in course each week. Above and below me, there would be students who performed better and worse (to protect their privacy, their information has been redacted by UBC’s Office of Counsel). I would hope that instructors wouldn’t pay too much attention to the arbitrary statistic of average time spent in course. As limited means of access, and different practices from individual students, would heavily influence this field and make this a very biased means of evaluation.
The Performance Dashboard
The Performance Dashboard is another Connect Learn tool that instructors can use to evaluate students. Importantly, this is where a student’s total number of discussion posts are listed. It also informs instructors when a student is not logging into a Connect course often enough. This information is provided in the Days Since Last Login column. Note that the timestamp contains the precise second of the login.
As this course ended a couple of years ago, the table indicates that it has been 651 days since my last login. These statistics would be in comparison with other students, whose data would be above and below my own (again, redacted by UBC’s Office of Counsel for privacy). The kind of comparative analysis based on arbitrary statistics presented by the Performance Dashboard is highly suspect and goes against the standards of academic rigour.
Below, you can see how recent my last activity was on the discussion board and in my journal, my total post submissions and journal entries, and total submissions. Carefully monitored and heavily scrutinized, this data could be useful in providing a very basic comparison between students in the class. However, taken into consideration only at this level, it would be quite biased. For example, if my discussion board posts were all very short and not very useful, I might be graded better than someone who had less posts, but whose posts were much longer and of much greater value.
This kind of analysis is dangerous because it’s very superficial and does not consider the quality of the content of a student’s work. If an instructor were to rely on this tool, then the grade that was derived from this information would not be representative of the actual effort that a student had put into the course, and would be very unfair reflection on the student.
Student Activity Overview
This is a breakdown of my weekly Connect usage for this course. It could give an instructor an idea about when and how often a student is accessing the materials. For example, it looks like I’m heavily favouring Thursdays and, as I recall, assignments and discussion forum posts were due on Fridays in this course. This might give an instructor the impression that I’m leaving my course work until the last minute. Whereas, it could be the case that I’m preparing my assignments offline and taking the time to edit and improve them up until the deadline before I submit them.
Likewise, a student with limited access to the internet might have all their interactions with Connect during very brief periods, only a couple of times per week. Looking at a statistical analysis like this, the instructor could get the impression that the student is not sufficiently engaged with the materials, despite all of the time offline that the student is putting in.
These images show the total number of times and initial access time that I accessed course documents within Connect. For an online course like this one, it allows the instructor to see if a student is moving through the course modules at an appropriate pace, and provides them with an easy explanation if a student is not performing adequately.
But, as mentioned before, some students may not access Connect frequently, despite their engagement with the materials. For example, a student might download all the course modules at once and then access the materials offline. In the Performance Dashboard, that student wouldn’t appear to be performing very well.
If I were to take an online course in the future, I wouldn’t necessarily want this level of surveillance and scrutiny: this information is likely only to be used as evidence for why a student struggled in a course. There could be many reasons why a student might perform poorly, and the time at which a student initially accessed a learning module is not necessarily indicative of that student’s performance. In the future, I would go through and open all of these modules on the first day I accessed the course within Connect so that this data couldn’t inform my participation grade.
Value of the Data
It is my belief that the data being collected and provided to instructors through Connect’s learning analytics are a threat to the unbiased evaluation of students at UBC. The comparative presentation of these statistics are not indicative of the actual efforts of students and creates undue risk for them to be assessed on factors that are completely unrelated to their engagement with course materials.
And because this harm far out weighs any tangible benefits, I believe that UBC should stop collecting student data through learning analytics on Connect. Or, in order to better address these concerns, students should have complete, un-redacted access to these documents so they can understand how they’re being assessed in comparison to their peers. This would give them the opportunity to either change their working practices, or to at least argue and have evidence that they’re being unfairly evaluated.
But the most obvious means of addressing these concerns would be removing instructor access to these reports, which provide such cursory information that it can only mislead their grading practices, and offers far more potential for harm than any possible positive effects.
Two UBC students talk about how they use Connect and then watch a video that explains how Connect collects student data and generates reports that instructors can view. They express concerns about how this data is collected and about the affect that it may have on their grades. Overall, they believe that a more transparent framework needs to be established because of the potential impact of this data collection.
What do you think?
How might you change your practices on Connect now that you know more about how you’re being assessed? Do you think that any of your habits have influenced your grades in unfair ways? Would you like to see the data collection on Connect through learning analytics be disabled?
The Blog Series
The Connect Exposed blog series documents my inquest into data collection on Blackboard Connect, the difficult process of obtaining my data from UBC, and privacy concerns around the collection of student information.