Dennis Day
Dennis is a Senior Consultant with Collegiate Project Services.
Latest posts by Dennis Day (see all)
- Student Success: It is personal! - June 21, 2016
- What Role does Predictive Learning Analytics play in Student Success? - April 26, 2016
- What does sport analytics have in common with student success? - February 23, 2016
Even with sophisticated predictive analytics, we’re still 12th????
Imagine: You dash into the weekly President’s Council at your college or university and pronounce: “We are 12th amongst our peers in degree attainment!” Not sure what the reaction would be?
At the Fall 2015 EDUCAUSE Annual Conference a paper was presented by the EDUCAUSE Center for Analysis and Research (ECAR) on “The Predictive Learning Analytics Revolution.” This paper opened with a similar statement: “The United States is 12th internationally in degree attainment (associates or above) among 25 to 32 year olds.” This statistic is supposed to pull at our patriotic feelings of wanting to be the best in all things and somehow shake us into action.
Take-Aways from the ECAR paper
The ECAR paper describes learning analytics, how data is collected, what we use it for and how it becomes predictive in learning analytics to leverage student success. This paper presented at EDUCAUSE takes the premise further by showing how predictive analytics are being leveraged at colleges and universities.
Being 12th is not bad when you consider that there are 196 countries throughout the world. Our national pride takes a hit because as a country we believe we have the most well-educated, highly functional employed population in the world. Emotionally being 12th does not sit well; intellectually it shows that we can and should be able to improve. But how?
ECAR points out that student data has existed for decades: it can be analyzed in ways to assist colleges and universities in their efforts to improve student’s persistence, degree completion and attainment.
As additional statistical data is available, further analysis leads to a more refined picture of our students, our learning systems and the outcomes. Throughout the ECAR article very specific examples are shown demonstrating how some institutions have taken advantage of tools and products to affect learning success, prediction of course completion, degree attainment and, in some cases, course selection leading to degree completion.
Common themes have been identified in the study of these systems and the development of the predictive learning analytics at each institution. What we are noticing, is that once again, the schools experiencing marked improvements in retention and completion rates are viewing the predictive analytics as part of a bigger picture.
How do we leverage learning data for student success?
Initially it takes strong and consistent leadership to shepherd a transition to predictive learning analytics. Organizational politics, territorial-ism and resistance can sink an initiative before it begins. Committed leadership on the executive level and the departmental level is critical to getting everything started and finding or defining the institutional priorities.
Campus climate and institutional culture must be understood and developed to accept the use of data driven decisions and predictive analysis. Engaging in the technical and the emotional discussions cannot be avoided if true change is to occur at the college or university.
Knowing the limitations and capacities of the institutional technology is important– we must recognize if the technology can do what the administration wants to accomplish. System architecture, data capacities, and software availability all impact the possibilities associated with predictive learning analytics.
Certainly campus policies will need to be adopted to meet these uses as determined by your administration and institutional priorities. Ethical use standards will need to be explored that are consistent with federal and state laws and with the institutional mission.
Assessing the human resources needs of these systems and operations is vital; knowing the technical skills of your personnel is one aspect; knowing the skills needed to have a successful project is another. If a gap exists, then training will be needed. Sharing or teaching comprehension of what predictive analysis is and how it works is another area to address among faculty and staff.
Building this comprehensive plan takes a holistic approach, utilizing all campus and community stakeholders. Advancing methods of assisting students to be successful has become more sophisticated and multi-layered. Utilizing predictive analytics can be another tool in our belt of knowing how our students will do in their courses. The data is there for the using, we just need to direct our efforts on how to use the data to be aware of which students are likely to be successful, which students may need some assistance and which students need significant interventions.
The fact we are internationally ranked 12th in degree attainment is not as simplistic as it sounds. As in our institutions, we need to look at the big picture. What does 12th mean? What are all the factors involved? How do we begin to address all the factors and not just the data and the pieces to which they point?
That President’s Council meeting you dashed in to? The discussion may be thoughtful and put into context through a discussion of what 12th means and the institutional goals. As we each answer that question at our individual institutions in a more holistic approach, we believe our national goals and pride may finally begin to see the desired results.
