With the wealth of data available to colleges and universities about current students, it can be easy to forget that there is just as much information about former students. And in a social media-connected world, it’s easy to continue gathering data on alumni about everything from what they are doing for work to how often they are giving to the university.
For many higher education institutions, fundraising from former students is the most common way of keeping track of alumni. But there are many opportunities to use data to track alumni engagement and increase efficiency in the advancement office. Let’s examine how. (more…)
Fans know where to find the University of Alabama football program – it’s usually at the top of the polls.
But now, the University of Alabama football program also knows where to find its fans. Or, at least, it’s trying.
The school is trying to boost attendance and to keep fans in their seats at Bryant-Denny Stadium by using location-tracking data. They are tracking which students come to the game and who is staying until the end of what are usually non-competitive contests in the fourth quarter. Students who use the location-tracking app and come to the game are awarded Loyalty Points, and then they are awarded more points if they stay all the way through the game.
Alabama’s approach may be unique, but they are certainly not alone in gathering information directly from students. Schools are looking for data wherever they can find it – and as the technology offers increasing opportunities to do so, colleges and universities are looking to apps that a student carries with them to provide that data. Let’s take a look.
Technology can only do so much. It can provide incredible insights that organizations might not have imagined possible…but only if the people putting it together do it the right way. Take, for example, the recent story about a start-up that used artificial intelligence to help improve disaster response. The company used census information to predict where people would need the most help in case of, for example, an earthquake to help emergency responders quickly get to the people who needed help.
Among other problems, the start-up was mostly using residential census data, so stores where a large number of people might be trapped in a disaster would be ignored if rescuers relied solely on the information the start-up was providing. The lesson? The data is only as good as the people entering the information.
For many higher education organizations, so much emphasis is placed on analyzing data that it almost seems too obvious to point out: that data needs to be reliable. But how often are organizations stopping to look at data quality? (more…)
It is a term thrown around every time a school mentions its use of data – analytics will make the institution more “efficient.” But what does that mean when it comes to the world of higher education?
Does a particular process become more efficient? Does the school run more smoothly overall? Is it saving time or is it saving money? The answer can include all of those things. Here are some specific ways analytics can make an institution of higher education more efficient, and how sometimes efficiency can mean thinking outside the box…or outside the mailbox, as the case may be.
You only get one chance to make a first impression. Sound advice for socialization, sure, but it can also apply to the world of higher ed. (Beyond the chats at the water cooler, that is.) It is advice that might be heeded during a professor’s first class of the semester…or maybe even the first few minutes of every lesson that professor is teaching.
But it can also be applicable to the technology an institution of higher education is using. Many colleges and universities are increasingly using data for a number of purposes – to increase retention, to identify and help struggling students, or to make processes more efficient, to name just a few. A data dashboard can help or hinder the analytics process. It is the first impression a user gets with the data, and if it is too clumsy to navigate, a user might not come back to work with the data in a meaningful way. If it is easy to use, it could benefit everyone in the community. Here is some advice about how to find success with dashboards, and what makes a good dashboard in the first place. (more…)
Many colleges and universities are using higher ed analytics in one form or another, as they figure out how to best improve student performance or the school’s bottom line. For the most part, this is an individual venture on the part of the school, figuring out what data it can use to make a difference on its campus.
The United Kingdom is working on a different approach. It has spent the past year using a national learning analytics service. Institutions in England, Scotland, Wales, and Northern Ireland pool their resources and have opportunities to learn together about how to best use learning analytics. Here’s what collaboration around learning analytics through a diverse group of schools looks like.
With many colleges and universities considering expansion – new buildings, bigger spaces – they are increasingly turning to data analytics for their real estate needs. They are also considering how to balance the needs of a physical university with student demands for virtual learning.
I recently attended the European University Information Systems (EUNIS) 2019 Annual Congress in Norway, in which the discussion of university real estate featured prominently. Here are some of my takeaways from the event.
Often the conversation about higher education starts at the college level. But there are many lessons that colleges and universities can learn from the elementary and high school models when it comes to building a successful program.
As far as student success, that groundwork could be laid as early as pre-Kindergarten. In his book, How Schools Work: An Inside Account of Failure and Success from One of the Nation’s Longest-Serving Secretaries of Education, Arne Duncan makes the case that schools need to shift from their current K-12 model to a PK-14 model to best keep up with a twenty-first-century economy, and they also need to make more data-driven decisions. Here are some of the takeaways from his book.
Colleges and universities are using data in ever-growing ways. They analyze data in order to figure out which programs are doing well or whether new programs need to be added. They then examine the data to identify past patterns that might help predict what will happen next. And the data is increasingly being put to work in the field of artificial intelligence.
The use of artificial intelligence in U.S. education is predicted to grow by almost 50% over the next few years. Its uses range from the immediate and practical to the aspirational. Let’s take a look at how schools are using data in the field of AI, both directly with students and for administrative purposes on the back end, as well as the challenges the technology can present.
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.