In the introduction to this series, I discussed the student success problem and how the complexity of solutions creates confusion when determining what student success tools are best for your institution. In this section, I’ll discuss at a high level the following groups of products:
There’s a lot to unpack here, so if you know what you’re looking for feel free to skip ahead to the products you’re most interested in reading about. Without further ado, let’s begin!
Student Information Systems (SIS):
The SIS may not need much of an introduction as most institutions have some form of an SIS in place for student support. The SIS is a repository for student data – hence “Student Information” System. The SIS stores, tracks, and catalogs student data like high school transcripts, grades, course schedules, admissions data, financial aid, and disciplinary information.
In many cases, the SIS will also have the capability for students and faculty to communicate together – though I’ll note its important to investigate whether this and other functionality is done natively, or through an integration with another platform like the LMS.
Most if not all SIS systems also allow for the administration to view, pull reports, and analyze historical student information. This is great for categorizing student groups that are likely to contain potentially at-risk students. Typically, first-generation students, students from low socio-economic backgrounds, those on financial aid, etc. have been the groups of focus in recent years. From those groups, an institution can make various decisions on how it wants to approach supporting them.
Further, most if not all offer a dedicated student portal. Students can access things like their grades, course information, etc. From a self-efficacy standpoint, this component of the SIS is fantastic for the student to see where they stand in a particular course or if they are off-track to getting the degree they want.
Lastly, I’ll share some experience with you: With any major software implementation (like an SIS) it’s important to know how intensive a task any potential integration may be – first to get the SIS up and running, and then how other systems you implement will integrate with it.
For example, integrating with an LMS for faculty-student communication that I mentioned above. Depending on what’s in (or not in) your tech stack, performing this due diligence on the front-end could save many headaches – not to mention a lot of time and money – down the road. The value is tremendous, but there’s no denying it takes a lot of work and investment to run efficiently.
Learning Management Systems (LMS)
If your institution offers online-based content, courses, documents, or eLearning materials and programs – congratulations! You have an LMS.
The LMS is essentially a digital learning environment – allowing faculty to manage their courses, make materials available, and students to access those materials and lectures remotely.
The LMS contains some pretty useful data for student success purposes – particularly for online-only students, but also how on-campus students engage with it. Many LMS providers package some form of analytics with their platform.
Research has shown that students who engage with LMS tools frequently are more likely to be successful, and this makes perfect sense. If a student isn’t doing their work, attending/watching their lectures, etc., odds are they aren’t going to be very successful. There’s even a recently coined adage for it – “Log off, drop out”.
That’s probably the most valuable component of the LMS’s data when used for student success; Not just that the platform itself makes access to education easier for the student, but also that you can actively identify the engagement levels of each student with the data within the LMS. You can also see what materials students access, which gives insight into not just that a student is using the LMS, but how.
In combination with grades and other pre-enrollment factors, you can paint a pretty decent predictive picture for online and even hybrid students using LMS data.
Admittedly, LMS data on its own is pretty limited compared to other sources (i.e., students and faculty have to actually use the LMS in the first place), but in general, the student engagement argument here holds true: The lower the engagement, the higher the likelihood that a student won’t persist.
Customer Relationship Management (CRM) Platforms
CRMs, like the SIS, also may not need much of an introduction. There are dozens of vendors that offer CRM products that cross multiple industries, and all are pretty good at what they do. Essentially, if you think of running a university like running a small city (which in practice, it pretty much is), the CRM is what keeps everyone and everything organized and moving ahead.
CRMs for higher education work much the same way as CRMs for any other business – keeping tabs on your customers. In higher ed, the “customers” are your students. The CRM serves institutions by providing a centralized platform to monitor and track students from recruitment, enrollment, to when they become alumni and (hopefully) donors.
The plethora of benefits having a CRM provides have been well documented in higher ed over the last 25 or so years. Higher education’s adoption of CRM platforms have opened doors for virtually any operational department via faster service, greater communication, event scheduling, and other aspects of the student/customer lifecycle.
CRMs also play a significant role for the folks on the student success side of the house. Many CRMs give users the ability to manually input data about students. For faculty, things like class attendance and behaviors can be input to raise a possible flag on that student. That flag then goes to the advisor, and if its a serious problem, reach out to the student to talk about it and get them assistance should they need it. They also hold incredibly valuable data student data that – with the right kind of analytics – can provide a pretty good picture of risk among your students. Of all the uses a CRM has, student success is, in my opinion, the most important.
Business Intelligence (BI)/Visualization Platforms
This category of tools is where we get into potentially unfamiliar territory. While some forward-thinking institutions were early adopters of BI and visualization technologies, the effects on student success have been as wide-ranging as the vendors that offer them.
To complicate things even more, since these tools are often in place alongside the more familiar tools we’ve already discussed, without strong data-governance practices in place, it can be difficult to pin any impacts to student success directly to the BI/Viz tools themselves. In extreme cases, these tools can actually make the process of making decisions based on the data you’re evaluating more difficult. We’ll discuss data governance in another blog, but for now, suffice it to say solid data governance is critical.
That said, My personal attraction to these tools comes from my own curiosity – inputting seemingly flat or stagnant data into these tools can often reveal interesting findings simply because you’re able to change how you’re seeing and interpreting the data. For this reason, BI/Viz platforms are still valuable assets to have at your disposal (again, provided you have the right support in place at your institution).
One glaring shortcoming with these tools, however, is the old saying “You are what you eat”. In economics terms, the output is a function of the input. These tools are only as good as the data being fed into them. Some offerings out there do have rudimentary built-in analytics, but again, those analytics are only as potent as the data being fed into the tool.
Another requirement that I’ve learned from my experience implementing such tools at firms and institutions I’ve worked with (reinforced by countless anecdotes from other enterprise BI/Viz tool users, so I’m confident it wasn’t just the nut behind the wheel) is that they really require dedicated full-time staff and university support to be effective. Some institutions have this robust support for their institutional research teams to fill these Bi/Viz administrator roles to parse and analyze towards the answers your executives need. Many though, do not.
Without dedicated data analytics and BI/Viz staff within your IR teams, it can be very frustrating working with these tools because, by their nature, they simply rearrange and organize data. In large part, the grunt work is left up to the people using the tool.
Advising Platforms
Advising platforms are toolkits for – you guessed it – academic advisors. These platforms help advisors and students both, whether it be documentation or a catalog of interactions. Many CRMs include modules or packages that incorporate an advising platform. Some institutions have even homegrown their advising platforms.
Among others, the key benefit of any advising platform is to help advisors identify and support at-risk students. As we’ve discussed, much of the work to get the data that drives this is manual. Faculty may have the ability to input absences, notes on student progress and behavior, etc. They input what they see to inform advisors as they reach out to potentially at-risk students. These inputs are incredibly valuable, the only drawback being the reliance on faculty and advisors to adopt the platform and be diligent about inputting data.
Many advising platforms today also offer some form of a degree audit tool as well. These make it easier for students to see what path their chosen degree requires, not to mention easier for advisors to keep them on track. Selecting classes and checking progress are two of the most common features people look for, along with connecting students to different resources across campus to suit their needs.
The unfortunate reality of advising tools is that they are not the end-all-be-all of student support.
Classroom Collaboration
Classroom collaboration, similar to mobile applications discussed below, cut a wide swathe. An extension of collaborative learning, classroom collaboration in its simplest form is a situation in which a group of students learn and engage together on an educational topic or task. Students in a collaborative classroom depend upon – and hold accountable – each other. They engage each other through questions, discussion, and sharing resources, strengths, and weaknesses as a means to a deeper educational experience.
Why class collaboration makes its way on the list is because technology has drastically expanded the capabilities of collaborative classrooms and collaborative learning in general. As recently as 10 years ago, the collaborative reach of learning was limited to individual classes.
In recent years, technology has changed this entirely. Online forums, chat rooms, and virtual meetings allow students to participate in collaborative education and learning far beyond the brick and mortar classroom – quite literally around the world in some instances. There are many options for bringing classrooms together in this way you may be familiar with, whether it be a chat software like Slack, or a virtual meeting environment like Skype or Cisco’s WebEx.
Mobile Applications
Choosing between mobile applications these days can feel a lot like walking into a Baskin Robins. There are virtually endless varieties and flavors to choose from so this section will be pretty brief – frankly, to explain every nuance would take up too much time and ink (as if we hadn’t already).
For just about everything related to solving the “student success” problem – from helping students know when a professor’s in for office hours, to when study rooms are available across campus, or registering for on-campus events, tutoring sessions, and on, and on, and on – there’s an app for that.
Recently, many institutions have even begun footing the bill for in-house applications developed by their faculty to address their specific needs and focus areas.
The problem with using mobile apps to measure student engagement – similar to BI and Viz tools – is that output is heavily dependent input. In this case, the inputs of a successful mobile app requires are that students actually use them. On average, mobile app engagement isn’t all that following the obligatory download during orientation.
While your individual mileage may vary at your campus (s/o to Georgia State for their incredible app and swipe card-derived results over the last decade), but mobile app initiatives require a tremendous amount of oversight and student nudging for engagement to be effective.
Analytics Companies:
Now we get to the heavy hitters – the analytics companies.
Analytics companies separate themselves from the pack because, for many, they aren’t focused on becoming an ERP or a student portal. They do just what you think – they analyze data. Many are pretty good at it.
Tried and true “analytics” vendors represent a much narrower facet of EdTech, but even still there has been much discussion at conferences, in publications, blogs, and online forums about the impact these analytics providers have delivered to institutions across the country.
Many players you’ll probably be familiar with in the other spaces we’ve discussed – like CRMs, LMSs, and Advising Platforms – have “analytics”. What separates them is not just their analytics capabilities (which are substantial) but also the data sources they have access to and, ultimately, use.
Analytics from a CRM group, for example, might then place heavy emphasis on SIS data, focusing on things like grades, or pre-enrollment attributes. Analytics from an LMS might also then place heavy emphasis on student engagement and clicks through their platform because that’s the data they have the best access to. While these analytics have had great uses, they are still limited.
The Takeaway:
I hope you’re seeing the recurring theme here. All of these tools have the potential to be very impactful and all are useful to have in your toolbox so long as you understand one universal caveat: With the exception of CRM platforms, pretty much all these offerings fall victim to the same economic law of production – Output is a function of the input.
Inputs in both terms of data sources, and of campus resources and staff. Both are equally important to be successful. No matter what EdTech brand is behind the service or how much the tool costs, the outputs will only be as good as the inputs.
One data source we haven’t yet discussed is where Degree Analytics separates itself. Wireless data – meaning WiFi and Bluetooth. Right now, there’s only one company out there that uses wireless data in tandem with other data sources on campus like the SIS to get as close to the complete picture of the student experience as possible (Spoiler alert: It’s us).
We’ll speak to this in detail in part 2, so stay tuned!
Marc is a founding member of Degree Analytics and serves the company as Director of Strategic Partnerships. His focuses include new business development and aligning Degree Analytics’ capabilities and services with the strategic goals and institutional missions of partners. He has spent his career using data to drive strategic and financial decision making in manufacturing, healthcare, and higher education. Marc believes every student has the capability to be successful and obtain the degree of their choice – all they need is a little support from the right places at the right time.