Analytics 101

The future of higher education is analytics, and the future is now.

The analytics approach uses student data to proactively assess student needs, thereby producing actionable intelligence. Contrast analytics with the more traditional paradigm of reporting. In the latter, an organization uses data to identify results, such as the percentage of students that graduated within three years. In the analytics approach, on the other hand, an organization uses data to discern the opportunities and challenges facing a particular student at a particular time.

Numerous programs around CCD are already utilizing analytics to increase student success and enhance organizational efficiency (whether said programs realize it or not!). For example, the TRIO Student Support Services (SSS) program quantifies ten data markers to create a persistence score that feeds into a triage model of advising. TRIO SSS is also piloting a course predictor analytic that utilizes a student's previous academic performance in specific courses to discern the relative challenge of a particular course or course set in the upcoming semester.

"Know where to find information and how to use it; that is the key to success," notes a data wonk's proverb often attributed to Albert Einstein.

It is certain that higher education is swimming in an Olympic-sized pool of data. We can run report after report after report about demographics, success rates, enrollment, and much more. The siren call of analytics is search these data for variables with high explanatory and predictive power, as deciphered by contemporary social science and statistical methodologies. These data variables shine light on the path to increased student success and organizational efficiency.

Guided by data and research experts at the Higher Learning Commission, the Persistence and Completion Committee (PCC) at CCD is diligently swimming through that Olympic-sized pool of data in search of the most impactful variables of student success. Toward this end, the PCC is carrying out a social scientific inquiry using historical data from Institutional Research; student surveys of new, exiting, and graduating students; a meta-analysis of program level data from across the institution; and a qualitative analysis of anecdotal data accrued through the wisdom and experience of faculty and staff practitioners.

Identifying the impactful data variables at CCD is but the first step. Future directions include determining and implementing the information technology solutions to aggregate the data variables and process the statistical algorithms required by multivariate analyses. Then it will be onto creating intuitive and accessible analytics tools for implementation by faculty and staff practitioners.

The process will be both easier and more difficult than it sounds. Much like the game of chess, it is not that difficult to get down the basics, but the perfection of the craft will take much experimentation and learning as an institution.

The future of higher education is analytics, and the future is now.