eLearning Roadtrip

When I Think of Student Success

The tendency to link software with student success has accelerated since 2012, as the educational technology sub-sector known as "integrated planning and advising for student success" has gained prominence through a series of grants funded by the Bill & Melinda Gates Foundation to colleges and the tech partners they have selected to help the colleges improve student performance. These days, more than 100 companies offer integrated planning and advising technology platforms and tools for student success includes that serve a wide variety of functions, from deciding where to go to college, to facilities and course scheduling, from helping students select select majors to staying on track with program completion. Student success is a huge part of the current ed tech market scene. (Disclosure: In my current day job, I work for a company with a large part of its business dedicated to Student Success.)

EDUCAUSE has led efforts to help institutions explore both the promise and the risks of Integrated Planning and Advising for Student Success (iPASS). Per their website:  "iPASS is an integrative approach to student success that promotes shared ownership for educational progress among students, faculty, and staff. It encompasses services that help students formulate and advance toward educational goals, including advising, counseling, progress tracking, and academic early alerts. iPASS technologies can contribute by documenting and tracking students’ educational plans, improving data analysis, offering self-service resources that reduce advisor workloads, and triggering interventions based on student behavior or faculty input."

There have been two Gates Foundation-funded rounds of grant-making by EDUCAUSE in support of student success. The first was the Integrated Planning and Advising System project, designed to get schools and their tech partners to collaborate on getting platforms and practices to work together better. I was involved in the first IPAS round when the Predictive Analytics Reporting (PAR) Framework was contracted by the Gates Foundation to evaluate the 19 "student success + software initiatives" that were funded in that first go-round. We visited the 19 IPAS campuses that were working with specific tech company partners to further the implementation of a tech platform that could help campuses with student planing and advising platforms. PAR had used the PAR Student Success Matrix we had developed to help our own PAR members make the connection between predictions of  student risk with selection of interventions. We were able to determine and demonstrate measured effectiveness with particular groups of students under particular circumstances - sort of like getting the most effective prescription for dealing with a particular medical condition. We had been excited about our own results; the fact that we were going to be able to evaluate student success impact with our matrix of time-in-program and actionable predictors with a broader set of institutions was thrilling.

By the time the second round of grants were funded, the name of the initiative had become "integrated Planning and Advising for Student Success: iPASS". The connection between tech and advising (e.g. watchlists, early alerts), tech and planning (e.g. curriculum pathway planners, strategic scheduling), program fit and course navigation (e.g. obstacle course GPS), integrating predictive analytics with real-time student activity stream data.) As it happens, the iPASS initiative helped spark PAR Framework's acquisition by Hobsons in January, 2016, when two state systems of education proposed integrating PAR's predictives and intervention measurement with Starfish's real time student activity data stream used to build student watchlist/advisement capabilities as part of their iPASS grant proposal.

5 years, two major initiatives and several rounds of small planning and implementation grants later, EDUCAUSE has produced a library of student success resources for educational practitioners, on everything from "Things you should know about IPAS" (yes, that acronym is different than in the previous paragraph; more on that in a bit) to implementation handbooks, data tables and evaluation reports. and  from https://library.educause.edu/resources/2013/8/integrated-planning-and-advising-services-ipas-research.

It has been great to be a participant in this wave of innovation in education, where data is being used as currency for more effective decision-making in schools and colleges. No doubt, when we look back on how decisions were made in 10 years from now, we are going to wonder how we managed to live without platforms that help visualize patterns, red-flag student risks before they become problems, provide a 3D map of an academic transcript that can cross-walk among formal and informal learning experiences. 

Even so, I need to say something.

When I think of student success I never, ever think of software first. 

Software can make things easier to do, of course. It offers far better ways to keep track of searchable information requiring any manipulation. I'd rather build formulae in a spreadsheet, and have huge collections of data fueling explorations that report results in approachable visual reports and dashboards. Learning management and content management and curricular tracking, assessments and performance support are all more available, more accessible and more targeted at specific points in the educational experience than ever before.

Just as data associated with online and digital transactions help inform marketeers of our retail intentions even before we know for certain, ourselves, patterns of students behaviors can raise red flags before students are even aware that they may be drifting into dangerous territory for "students like them".

Technological inventions, applied to performance and learning problems, can help solve those problems. In doing so, the inventions become innovations, human ingenuity applied to solve performance problems in novel and compelling ways.

Innovative educational entrepreneurs  - "edu-preneurs', if you will - see an opportunity for tech in schools and are compelled to create products that promise to disrupt education as we know it. They point to deep data science and predictive analytics as if these analysis techniques are beyond the norm.

It's seems important to remind ourselves that in education, the most most important innovator in this value chain are not necessarily the ed tech entrepreneurs. Rather, the ones on the front lines of teaching and learning, supporting student achievement putting new tech tools to the test in the service of student success are todays true innovators. 

It's important to have shared articulated expectations of "the norm", so that one can identify those not yet achieving at that level, and how one inspire those working "above average" to continue to improve. Common expectations of meaning and outcomes are essential elements of student success that gives all students a shot at achieving their dreams. We need to include ALL students in our considerations of success, not just those attending college for the first time, going to school full time, or living on campus. We need to keep the student at the center.

With thanks to Kalah Burks and Rebecca Wheeler, University of South Alabama, for the great conversation that shook this post out of my head.

Karen Swan and the Amazing Multi-institutional PAR Student Success Matrix

Back in June 2013 the PAR Framework openly published an intervention assessment framework called the Student Success Matrix to help PAR members figure out how to respond when confronted with predictions of which students were likely to drop out. "What should we do to respond to these predictions showing our students at risk?" our members asked.  At that time Dr. Karen Swan, Stukel Distinguished Professor of Educational Leadership at the University of Illinois Springfield, reminded us that there are already lots and lots and lots of things that academic advisors, faculty and other student success professional already do to help students succeed in school. Going back through the professional literature, she and Dr. Peter Shea, SUNY-Albany, helped us find models of student engagement and participation relevant to our work at hand.

Karen proposed a framework to map interventions using predictor behaviors of success and points in the academic completion cycle.  Over the past year Karen and Peter have worked closely with Sandy Daston, PAR Framework Director of Student Success and the entire PAR SSMx working group (Hae Okimoto, University of Hawaii System; Jennifer Freed, Dan Huston, and Fermin Ornelas, Rio Salado College; David Shulman, Broward College; Denise Nadasen, Jack Neill and Karen Vignare, UMUC; Patsy Moskal and DeLayne Priest, University of Central Florida; Michelle Wiley, Penn State World Campus; Mysti Reneau, Community Colleges of Spokane) to refine processes and tools for promoting intervention measurement. This group of experienced educational practitioners and decisionmaker has helped determine what can actually be done for student at risk - even down to knowing how to support those 37 students that are most likely to fail Math 101 this semester. 

PAR institutions have begun the process of inventorying, tagging, describing measuring and evaluating literally hundreds of interventions currenty in use on campuses to help student succeed. Thanks to the SSMx we have accelerated the process of connecting predictions of risk to the interventions that will mitigate risk. 

This post is to acknowledge Karen's leadership and contributions to PAR's thinking about using predictions as cataysts for taking action, and for linking interventions to predictions to underscore the importance of linking predictions to action.

 

The Big Data Landscape

If you post the term "Big Data" in your Google search window today, more than 2 billion google search results will appear. If you perform a similar search on Bing, you will see that more than 1,790,000 Big Data links have been added to the Internet in the past 24 hours alone. Clearly, there is big interest in big data.

This graphic by Matt Turck and Shivon Zilis is an exceedingly helpful image for understanding the breadth and complexity of the Big Data landscape. Matt Turck's blogpost  also provides great information for understanding some of where this emerging market is taking us. 

 

 

For those of us working in post-secondary education circles, the emergent interests in big data, analytics, learning analytics and related evidence-based decision-making endeavors have been inspired by possibilities of better experiences, more personalization and better behavioral targeting. Still most education stakeholders who are giving learning analytics some consideration may be surprised to see the depth, breath and sophistication of the big data world.  While WCET's work on the PAR Framework has certainly contributed to a growing awareness on the power of predictive analytics for academic risk identification and the value of collaborative, multi-institutional data mining to improve student success, we are mindful that our student success focus touches a relatively narrow, targeted part of the Big Data picture. This graphic offers a more complete picture of the total ecosystem.