Justin T. Dellinger recently celebrated his fourth anniversary with the LINK Research Lab at the University of Texas at Arlington, where he currently serves as Associate Director and project lead for a new series of learning analytics courses in edX. Prior to his time in LINK, Justin worked in the Division of Digital Teaching and Learning and the Center for Distance Education doing instructional programming and design, and in the Department of History as a graduate assistant and online lecturer. Justin has also taught K-12 in the Dallas-Fort Worth metroplex. He has almost fifteen years of experience with educational technology and is actively involved in the growing learning analytics community. His current research interests include multiple-pathways learning, online course design, and learning analytics. He is currently pursuing his Ph.D. in Educational Leadership and Policy Studies at the University of Texas at Arlington investigating the adoption and implementation of learning analytics in K-12 schools.
“As learning analytics has continued to grow and mature as a field, researchers have progressively investigated meta issues such as ethics, policy, and adoption and developed codes of practice to help higher education institutions better use large-scale learning data and analytics. In particular, two important projects have studied the adoption of learning analytics in Australia (Learning Analytics in Australia) and the European Union (SHEILA). However, most research has focused on postsecondary or workplace contexts, and there is a significant gap for K-12.
“To date, only a small number school districts have systematically implemented large-scale learning analytics projects. However, given the growing emphasis on data-driven education, the prevalence of technology solutions and vendors, and a push toward personalized and adaptive learning, these projects will increasingly play a role in the K-12 context. Learning analytics has the potential to provide students, teachers, and leaders with actionable, real-time data to help individualize interventions and make better-informed decisions overall. However, implementing a project is no easy task.
“Leaders face a number of significant challenges in the learning analytics implementation process that can make or break a successful adoption. Some of these factors include more technological items such as systems interoperability, infrastructure, and appropriate tool/solution selection. Yet, initial research indicates that K-12 leaders do not have a full understanding of the tools that they adopt and the data that the technologies collect. Use of “black box” systems that rely on minimal datasets, but have high costs, might also further existing equity imbalance. Additional issues include the necessity of big-picture mindsets that recognize the complexity of the process, building stakeholder trust and buy-in, and creating applicable scaffolding and professional development for users. Finally, there are different local, state, and federal policies that impact adoption such as funding, data use, reporting, and accountability.
“Ultimately, the goal of my research is to increase student success by developing a model that illuminates key factors, details, and considerations that will contribute to improving learner performance. Moreover, my hope is that this model can enhance the likelihood of a successful learning analytics implementation. Doing so could decrease overall costs and promote greater equity.