As head of SAS’ Research & Development Division, Armistead Sapp leads R&D employees worldwide to produce the highest quality software in areas such as business intelligence, advanced analytics, data management and customer intelligence, as well as industry-specific solutions and mobile applications. As CTO, he actively engages with and encourages SAS’ development teams to take full advantage of modern computing platforms that deliver value to customers.
Sapp is involved in many of the company’s STEM education initiatives, which seek to prepare students for today’s workforce opportunities. Many of those opportunities are in data science, driven by the rise of Big Data. Sapp oversaw the creation of SAS Analytics U, a higher education initiative that provides free SAS software, active user communities and learning resources to professors, students and others around the world.
Sapp also leads SAS’ P-20 division, which supports the advancement of data-driven decision making for administration and for teaching and learning. The division also develops SAS® Curriculum Pathways® (free Web-based curriculum resources), SAS University Edition (free software for teaching and learning), and mobile learning applications such as SAS Flash Cards, SAS Math Stretch, SAS Read Aloud and others.
He sits on the board of “Ready by 21,” which helps communities improve the odds that all children will be ready for college, work and life. He works with the Duke University School of Medicine’s Department of Pediatrics – Division of Neonatology, researching best practices and safety using SAS data mining tools. He is also on the advisory board of the Energy Production and Infrastructure Center (EPIC) at UNC Charlotte.
Sapp is a graduate of the University of North Carolina at Chapel Hill and co-authored the book, “Implement, Improve and Expand Your Statewide Longitudinal Data System: Creating a Culture of Data in Education.”
The rise of Big Data has created a skills gap where there is insufficient analytics talent being produced to meet the high demand from employers. SAS is working with higher education institutions to not only address our own workforce needs, but those of our customers. We have assisted in the establishment of Master’s degrees in Advanced Analytics at universities around the world. These programs teach students to use tools of data analytics and data science, including machine-learning techniques, to solve real world problems at scale. The graduates from these programs are prepared to make a contribution from the first day of work at their new job. SAS helped establish one of the first of these programs at North Carolina State University – The Institute for Advanced Analytics (http://analytics.ncsu.edu).
Today in the United States, SAS is working with Business-Higher Education Forum (http://www.bhef.com/) to establish undergraduate programs in data science. These will be multi-disciplinary certificates or degrees that will prepare graduates for jobs on the front lines of data science. The goal is to build out programs at a number of universities based on a common template. Each university can share and contribute and not have to invent a program in a vacuum. This should mean many more programs can be established so that Data Science education can be scaled to a national program quickly. As soon as the template is developed, SAS will help share it worldwide. If successful, developing these programs could be like a moonshot for data science.
Finally, last year we made SAS software and learning materials available at no charge to all learners worldwide. We hope that will spark the initiative of people to learn SAS programming who otherwise would have to have an employer or a degree-granting program provide the software. This software, called SAS University Edition (http://www.sas.com/en_us/software/university-edition.html), has been downloaded hundreds of thousands of times.
That said, at the instructional level, we must consider how technology is taught. The best way to teach technology is project-based learning (http://en.wikipedia.org/wiki/Project-based_learning), where students work together on a problem, solve it, and then demonstrate the solution. Most STEM jobs are project-based. Teaching technology in this way not only teaches the course’s concepts, it helps students learn to work together toward a common goal. Developing these skills is important, since nearly every technical job requires the ability to communicate and work in teams.
Today, most higher education courses are taught via lecture and lab…each student learns and works alone. Moving to a project-based approach makes learning more interesting and challenging. Many STEM majors drop out of programs in the first year saying the work is not interesting or challenging. I think we still are teaching STEM the way it was taught a hundred years ago, and it’s not working with 21st century students.
Another approach that is gaining some traction is flipping the classroom (http://en.wikipedia.org/wiki/Flipped_classroom). In a flipped classroom the lectures are online and the students watch them outside of class and projects are worked on during the class time.
Finally, the last decade has seen the rise of the smartphone – around 6.8 billion phones can access the internet. Every phone can be turned into a learning platform.
So how do we measure success, overall? Building a national longitudinal data system known as a P20W system (P is Preschool, 20 are grades K-12 and up 8 years of post-high school education, and W is Work) would allow the United States to track students over time and see what works and what doesn’t.
If we were to look at students who, in 9th grade, indicated interest in a STEM career, we could follow them as a cohort until the 5th year of work. We could see how many actually entered STEM careers, and see what those who did not enter STEM careers finally chose to do. By definition, longitudinal means repeated measures over time. Building a system that reported on groups, but could also track at the individual student level would allow us to track outcomes and intervene when a program isn’t working.
Learning is lifelong. Many people retrain multiple times in their work lives. Having a national longitudinal data system could answer questions like “how did people in the biotechnology retraining program in North Carolina do in securing jobs in biotech in the first 2 years after the training and are those people still in their jobs in year 5 and 10?.”
I am so passionate about educational longitudinal data systems that I co-authored a book titled “Implement, Improve and Expand Your Statewide Longitudinal Data System: Creating a Culture of Data in Education” on how states could implement one.
The US Department of Education is funding a SLDS in each state (http://www2.ed.gov/programs/slds/factsheet.html). I strongly believe that gathering the data and reporting on cohorts of students and their outcomes will help us improve education. If we cannot measure how a system is working we cannot make evidence-based changes to those systems.
SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. SAS focuses its philanthropic efforts on education initiatives geared towards increasing the STEM-skilled workforce. SAS uses a multi-pronged approach to provide support through many channels and using its resources to develop creative instructional materials. Examples of this approach include providing free interactive, standards-based curriculum software for grades 6-12 as well as free SAS software to students, professors and researchers at the university level. SAS collaborates with higher education institutions around the world to create degree and certificate programs in analytics and related disciplines, including the first Master of Science in Analytics program, at North Carolina State University. By supporting efforts that prepare more graduates for college, work and success in the 21st century, SAS continues to play a vital role in the global community.