Analytics allow us to deeply know students and guide them to success, but higher education is failing to leverage its use. This session explores the characteristics of analytics practice in teaching, learning and supporting students. It encourages participation of designers, developers, instructors and advocates across curricular and co-curricular landscapes.
Online education practitioners speak often of the "new traditional learner" - adult, working, parents, time-strapped, often first-generation, often needing extra supports - and yet we continue to offer - at best -a digital version of the same instructional and support services as offered on campus to the college student of a previous century.
This is not for lack of new tools: just in time, mobile, personalized, learner and context aware technologies are available to deeply leverage the path to student success in a new, digital framework. None of these tools show more promising results than learner analytics: deep pattern matching that provides us with current knowledge of each learner. Analytics provides real-time awareness by using machines to seek meaning in patterns only observable from a distance and better allowing us to know each student through their work, habits, behavior and even identity trends. Just as Seurat and Signac allowed us to understand images differently by observing points within larger patterns, analytics work provides a new data pointillism (Carmean and Robinson, 2016).
By studying blurry clusters of dots—in student demographics, behaviors and course work —we can provide timely safety nets to our students. Analytics gives us a window into student performance and allows us to know them in previously unseen ways. It enables more innovative curricular and co-curricular practice by expanding what can be known about our learners. New analytic tools are powerful predictors for needed supports and for timely use of information that changes student struggles to opportunities, solutions, supports and success.
This session will allow open-minded participants to explore and discuss the framework of analytics in higher education and the particular skills, interests and possibilities of creating new practice (and practitioners) specific to the needs of new learners in higher education. It will explore a university where tools, data and personalized learning ensure that students aren't merely names inside an LMS, but are as deeply "known" as is possible in the age of information.
Work of discovery demands a way of looking at educational technology and its practitioners with a sense of the possibility and promise in embedding analytics in the design and delivery of teaching, learning and learner support. Despite being adopted in other industries across the spectrum, the use of analytics is still new to higher education and where embraced, until now has been kept in silos of Information Technology or Institutional Research roles. This has not been a successful fit, as embracing the use of pattern-matching and nalytics is new to many who are now asked to take on the role of analytics worker. Technical and statistical worksers are being assigned roles not intuitive to their skills or interests. It is time for the academic side of the house, especially the online rooms of that house, to explore pattern matching in learning and student success.
Analytics is a way of knowing and serving our learners in real time; it is a new knowledge, not of historical numbers, but of our current students. It belongs to the role and interests of designers, student success professionals, and those who have always most deeply known our students: instructors. Practitioners across the online learning consortium are invited to a forum that will explore analytics, see it in action, and help the community determine how to move it more deeply into the tools we use to know our students, help them learn, ensure they succeed.