The 5th International Conference on Writing Analytics provided participants with an overview of relevant issues framing the discourse related to formative assessments and writing analytics. A key goal of the conferences was to explore the value of analytics to STEM and humanities fields. The conference organizers sought to bring together critics and proponents of analytics to discuss how it can improve student learning and student success.
Bart Rienties and his team of data wranglers at the Open University have conducted research that found use of analytics is highly correlated with student learning and successful teaching (Nguyen, Rienties, Toetenel, Ferguson, & Whitelock, 2017). Nonetheless, what if instructors don’t consult learning dashboards? What if disciplines like NCTE (National Council of Teachers of English) outright reject predictive analytics because they fear technology may ultimately replace teachers? What if instructors don’t understand the data they receive? In fact, research conducted on teachers’ use of analytics suggests some faculty aren’t interested in data or don’t understand how to interpret it: Herodotou et al’s large-scale study of 240 instructors in 10 learning modules at Open University found “many teachers struggled with providing actions and support based upon analytics data” and “most of the 70 teachers who were given access to OUA dashboards engaged rather irregular (sic) and infrequent (sic) with predictive data.”