Policy Enablers and Barriers to Maximizing Learning Analytics

• In Event: 77.028 - Can Learning Analytics Improve Learning?

Abstract

Although progress has been made in recent years with state-level longitudinal data systems and, in many cases, district-level data and assessment systems, the impact of data and assessment on day-to-day instructional practices continues to be sporadic and inconsistent in most districts and schools across the country. In a 2012 study of the implementation of student information systems (SIS) and learning management systems (LMS), typically related to systems integral to learning analytics, Gartner Inc. (2012) found that almost 70% of information technology (IT) professionals reported that the use of data by the teacher was not a focus of the implementation plan. Unfortunately, leaving teachers out of the equation in system implementation limits the potential for learning analytics. Learning analytics offers teachers and teams of teachers as well as school and district leaders a much clearer picture of student achievement, with detailed information to inform school reform efforts. Using the data as an academic improvement tool, not as a way to judge teacher effectiveness, provides teachers with time to reflect and differentiate instruction in ways that did not exist even five years ago. Addressing gaps in capacity limits the use of data and assessment in a meaningful way. In some cases, this is because of the overwhelming quantity of data without an organized approach to using it. In others, useful data is not available in a timely manner. Regardless of the reason, states, districts, and schools must build and improve capacity to experience the potential of learning analytics to improve student outcomes.
The learning analytics initiatives and data that will be briefly described in this presentation show states and districts moving from being data collectors to being data analyzers, able to use the vast amount of information being collected in a secure, practical, customized, and predictive system. Ultimately, the examples provide a glimpse into how districts are preparing to take advantage of learning analytics to meet the needs of each student. This transition is not just about implementing new or better data or assessment systems, or even improving the analysis of data. Education systems must also consider capacity in infrastructure and human capital, data use culture in schools and communities, and policies that enable the meaningful use of data to effectively apply and use learning analytics.
States and districts quickly uncover the need to comply with, revise, or establish certain policies as they work to implement learning analytics as a core component of their teaching and learning. These policies may be in response to federal, state, or local laws or requirements or to address a new area identified as needing clarification or direction. In some cases, existing policies may appear to hinder the practical use of learning analytics for students, while others seek to open the door to effective and efficient uses of data while keeping security and privacy at the forefront.

Author

• Mary Ann Wolf, The Friday Institute (NC State University)