Cover Page

Learning Analytics in Higher Education


John Zilvinskis

Victor Borden

EDITORS





Number 179 • Fall 2017

Jossey-Bass

San Francisco

Editors’ Notes

For the last few years, we have been thinking and talking about the learning analytics phenomena with colleagues and each other, and watching passionate interest well up from disparate sources. We both attended several Learning Analytics & Knowledge (LAK) conferences hosted by the Society for Learning Analytics Research (SoLAR). When the conference was hosted in Indianapolis in 2014 a majority of the sessions featured computer scientists displaying successful predictive analytic programs; whereas at the 2016 conference in Edinburgh, Scotland, there was a push to emphasize the ways these projects measure the experience of learning. We have also noticed the last two or three annual forums of the Association for Institutional Research, a number of presentations regarding learning analytics, often with packed crowds of institutional research staff who have been tasked with contributing to the development of learning analytics on their campuses. We also noted that the Association for the Study of Higher Education Annual Conference has had a few sessions dedicated to learning analytics that have been attended by a small, yet dedicated, group.

In each of these experiences, we've noticed different takes on learning analytics from the scientist, higher education institution administrative staff, and scholar perspectives. Motivating our work is a question: “Why haven't learning analytics become prevalent within higher education?” Considering the ways technology has been incorporated within the academy over the past two decades (e-mail, websites, learning management systems), it would seem that learning analytics would be a natural evolutionary step—however, this hasn't happened at the pace or to the extent that we might have expected. In our research on the topic, we've noticed that the complexity of higher education as an enterprise, matched with required resources and understandings needed to successfully implement learning analytics, present immense challenges to incorporating these technologies effectively and productively.

Therefore, we conceptualized an issue of New Directions for Higher Education that would inform campus leaders, faculty, and staff about the scope and type of activities and initiatives required to bring learning analytics to their campus. The goal of this volume is to introduce the reader to a basic understanding of learning analytics and the types of projects and initiatives that several leading practitioners have adopted and adapted, providing substantive examples of implementation, and expert learnings on some of the more nuanced issues related to this topic.

In the first chapter, we offer basic definitions of learning analytics, as well as an overview of who collaborates within learning analytics, exposing several broad issues for the reader to consider while reading the rest of the book. In the second chapter, Candace Thille reports findings from her and her colleagues’ work with the Open Learning Initiative at Stanford University to inform the reader of the nuances of measuring student learning in digital environments, while describing the technology needed to achieve this feat and the assessment infrastructure required to improve teaching and learning in the digital environment.

Chapters 3 and 5 provide examples of developing learning analytics applications on the campuses of large universities. In Chapter 3, our colleagues from Indiana University (IU), Cathy Buyarski, Jim Murray, and Becky Torstrick, describe the implementation of learning analytics across the diverse campuses of IU, incorporating both an internally developed early warning system and externally developed (commercial) e-advising program. Steve Lonn, Timothy McKay, and Stephanie Teasley describe in Chapter 5 initiatives to create a culture of learning analytics at the University of Michigan through the development of symposia, grants, and faculty task forces.

In between these chapters, Matt Pistilli focuses on the key roles of feedback and intervention in virtually all types of learning analytics projects and initiatives. In Chapters 6 through 8, the authors explore several compelling issues related to learning analytics. John Fritz describes how and why including students, and promoting student responsibility for learning, is critical within learning analytics initiatives, based on his experiences at the University of Maryland, Baltimore County, as well as related efforts elsewhere. Jeffrey Johnson provides a rich analysis of issues related to ethics and justice that arise when working with student data generally as well as specifically with the types of applications now prevalent in the learning analytics realm. Chapter 8 presents findings from a national Office for Learning and Teaching–funded project in Australia that focuses on developing new thinking about how to characterize modern student experience that preserves the use of strong conceptual underpinnings that have historically guided research on student experience, and using analytics as a way to break the old molds and form new ones. In the final chapter, as the editors of the volume, we discuss some of the themes found within the issues, such as collaboration, interrogation, justice, and independence.

We believe that this volume can substantially inform readers who have been considering the implementation of learning analytics on their campus. However, we recognize that it is by no means comprehensive or complete, as new research and understandings are constantly emerging around this topic (just follow the comprehensive coverage by EDUCAUSE, SoLAR, and ACM); meanwhile, scholars within computer science, learning technologies, learning sciences, and education have contributed comprehensive understandings of learning analytics as a scholarly field (both fundamental definitions and cutting edge research are presented in the Journal of Learning Analytics). This issue of New Directions for Higher Education serves as an entrée into the world of learning analytics for those who are, or who will soon be, exposed to this topic and expected to make decisions in the coming weeks, months, and years about how to engage constructively in using technology to improve student learning and persistence to completion.

John Zilvinskis
Victor Borden
Editors