Recent news from the world of higher education has been a real mixed bag. There was the feel-good story from Morehouse College, where billionaire tech investor Robert F. Smith shocked everyone with the surprise pledge in his graduation speech to pay the student debt of that school’s class of 2019.
The month before, the news was more sordid, as high-profile celebrities became the public face of a college admissions scandal. The two stories seem starkly different at first glance, but what they have in common is the fact that they shed light on the economic situations faced by students and families when it comes to higher education. These are the types of situations that colleges and universities are using data to try and manage.
Congratulations to the class of 2019! That’s congratulations for the completion of all the hard work that earned a diploma, and also congratulations on some very good timing. The class of 2019 is entering the best job market in nearly 50 years.
As with any graduating class, though, there will be competition for the best jobs, and the skills that might determine who employers pick might not be what you think. Despite the appeal of data analysts – one of the college majors drawing the most attention from both students and employers – it isn’t just about the data. Which is not to say there isn’t plenty of data to look into about this year’s graduating class. Let’s dive into it a little more and explore the job prospects for the Class of 2019.
Student debt is continually in the headlines, and with good reason. In the U.S. alone, more than 44 million people owe $1.5 trillion in student debt, which averages to more than $34,000 per borrower.
The student debt crisis promises to be a focal issue in the 2020 presidential election, with Democratic presidential candidate Elizabeth Warren announcing her plan to cancel student debt for many borrowers. What do you need to know about this crisis? How can analytics help? Let’s take a look in today’s “Hot Topic” blog.
It’s a saying we’ve all heard in one history class or another: Those who do not learn from the past are doomed to repeat it. The maxim can apply to business intelligence as well – especially when it comes to predictive analytics. In fact, learning from past experiences is key to making predictive analytics work.
Data analysts are able to use past results to plot out the most likely outcomes in the future. Many colleges and universities are using predictive analytics to increase retention. Let’s take a look at how they’re doing it and exactly what information they are using to make the most informed decisions.
It is a tense time in the world of higher education. The schools that aren’t putting pressure on themselves to respond to popular trends and try to stay ahead of the curve are certainly receiving pressure from their communities to do so – whether it’s from a Board of Trustees or reflected in feedback from students and parents.
It’s easy to find the talking points that make it sound like an administration is making necessary changes to improve the way a school is using technology. But doing the work to back up the talk is a different story. A recent situation at the University of Texas at Austin provides a look at what not to do in this situation. Here’s how you can avoid falling into the same trap.
There are many factors that go into how an instructor uses data at the higher education level. It could simply be that faculty member’s comfort level with collecting and using data to inform decision-making. It could be the way information is gathered – whether it’s at the administrative level and even makes its way to the instructor. It could be that the data is gathered but never used to determine next steps.
Whatever the situation, it is a fact that not everyone is using data to make decisions that can benefit the students in their classrooms. Here are some ways instructors in higher education might be able to better use the data available to them – or even get that data in the first place – to improve student outcomes.
It’s often said that when it comes to data in higher education, institutions have more data than they know what to do with. In those instances, it’s best to start with small, measurable tasks, so as not to get overwhelmed by the sheer amount of data.
The same is true at the government level. States have lots of data about topics like residents’ educational attainment and salary history, and they are working to organize the systems in which that data resides. The Data Quality Campaign, an organization advocating for better use of education data, is working to get states to move from collecting data only for accountability and compliance purposes to using that same data to answer critical policy questions and to work towards supporting students and helping them be successful.
A new project shows one way that can happen at the higher ed level. (more…)
On the one hand, some courses are so full that extra sections have to be added and students are placed on waitlists. Colleges and universities offering those particular courses have to turn down more students than usual as they deal with increasing numbers of applications. On the other hand, small liberal arts colleges are forced to seek out financial partners to stay afloat or they must consider shutting down entirely.
Both situations stem from the same issue, being weighed by all students considering continuing their education. The question is no longer which college should I apply to? It is more often, is college worth the debt I am going to incur? And, to put it more specifically: Will I be able to pay down that debt once I graduate? (more…)
When you think data and analytics, chances are you think numbers. But it’s not just numbers, especially in the field of higher education. Sure, there are grades and tuition and percentages and calculations, but there are also pieces of information that are qualitative instead of quantitative.
The students and their experiences provide data that is every bit as valuable as the countless numbers that are being crunched on college campuses. Some schools are struggling with how to measure those experiences…while others have figured it out by going straight to the source.
Many colleges and universities are focused on using data and analytics to help students succeed. But what does that look like in practice?
The answer is different depending on the schools. One thing they have in common, though, is that they rely on data that shows them which classes students are struggling in the most. Here are a few ways institutions of higher education have found success intervening on behalf of students who need help.