The 2019 National Historically Black Colleges and Universities Week Conference (HBCU) was held September 8 – 11, 2019 at the Renaissance Washington in Washington DC. The conference focus was on how HBCUs can successfully compete for top opportunities while providing education and economic experiences that can improve standards of living for the students, people, and communities they principally serve.
When I first started in higher education data analytics in 2013, after transitioning from academic astrophysics, my initial impression was: “This is it, huh?” I was a bit underwhelmed by the sophistication of the data tools and analyses that were used for decision making. Of course, over the course of 6 years in various positions in IT and IR at the University of Kentucky (UK), including three years as Executive Director of Institutional Research and Lead Data Scientist, I learned that using data analytics at an enterprise scale was far more complex than I had imagined. The barriers to success will be familiar to anyone who has spent any time in the higher education industry: source data systems that are not integrated, not accessible, and not designed for reporting or analytics; the unglamorous but hugely important work of educating people, updating processes, and changing culture; and all the natural complexity inherent to an organization that can daily see over 50,000 people set foot on campus.
Our latest eBook explores the topic of analytics programs specific to community colleges. It is an unfortunate truth that discussions of analytics and predictive modeling in higher education often neglect to include community colleges. This may be due, at least in part, to the fact that the majority of community colleges have an open-door admissions policy. Not requiring SAT scores or a specific high school GPA means they often have less robust data sets on incoming students than universities with stricter acceptance requirements.1 But the absence of specific data points does not mean analytics programs are not needed at community colleges, only that those data needs are different.
After all, more than a third of credit-seeking community college students are nontraditional (over 24 years of age), a stat which begs the question: do the high school grades of a 42-year-old professional looking to expand a skillset really tell us much about their likely success as an adult learner? Community colleges have a unique set of challenges and, like their four-year counterparts, data can help
address these challenges, boost student success, and support institutional goals. Follow along to learn six best practices for building and maintaining a community college analytics program.
The RTM Higher Education Congress held in Washington DC from August 4-6, brought together CIOs, Academic Affairs, and Enrollment Management professionals from across the country. A rich array of topics were discussed covering everything from leadership challenges, modernization of today’s colleges, diversity, strategic budgeting, removing obstacles to graduation, creating student experiences for future-relevant careers, classroom technologies, cloud storage, cyber security, and crisis management.
Despite the diversity of themes, three salient points ran through almost all the sessions:
1) Higher education needs to consider the student’s perspective and educate students for the world they will inherit;
2) Effective leadership is crucial to the sustainability of the institution;
3) Data-driven decision making is needed in all business units, from admissions through advancement.
Our latest eBook explores the topic of IT Trends in higher education. In the decades since online classrooms and digital databases first arrived on the scene, education and technology have become increasingly interdependent. From data-driven insights about student success to entire shifts in business models, technology has disrupted the industry of higher education and seems to have no intention of stopping. Read on to learn five significant ways that technology and education are intersecting today, in ways that will effect change in the higher-ed industry in the years to come.
North Carolina Analytics Day on June 20, 2019, hosted by Appalachian State University, was a wonderful opportunity for Tableau users across North Carolina and the region to learn, network, and share ideas with each other. In a special session, HelioCampus showed how to build Sankey Diagrams using Tableau extensions. Our own Burke Foley, Senior Product Engineer, is shown presenting below:
Last week I had the opportunity to head out to Denver, Colorado with the HelioCampus team for the AIR Forum. This event is our chance to learn from institutional research practitioners on how they are using analytics at their institutions. It was great to learn about all the different ways institutions are tackling data visualization, reporting, and more; and for us to share how we are working with our clients on combining, analyzing and visualizing data from across the student lifecycle.
I recently had the opportunity to attend the HEDW Conference in Ann Arbor, Michigan. The conference was a real testament to how Colleges and Universities are viewing and using data to make more informed decisions. Whether it be for enrollment, retention, student success or advancement, they understand how to best harness the power of data for institutional improvement.
As part of its annual Tom Tom Fest, Charlottesville hosted its Applied Machine Learning Conference earlier this month. Our HelioCampus data scientists and engineers joined other local data science practitioners for a day of robust discussion, practical guides to new techniques, and machine learning concepts applied in innovative ways to solve real-world problems.
Our latest eBook explores the topic of Institutional Planning for higher education. A lot is riding on universities’ performance metrics: enrollment and recruitment numbers, student outcomes and livelihoods, and funding. In fact, more than 30 state governments in the U.S. have policies or formulas that allocate funds to public institutions based on student performance factors 1. Universities with the ability to improve performance with comprehensive and data-driven institutional planning stand to fare better than their peers.
