Setting Learning Analytics in Context: Overcoming the Barriers to Large-Scale Adoption

Abstract

ABSTRACT:A core goal for most learning analytic projects is to move from small-scale research towards broader institutional implementation, but this introduces a new set of challenges because institutions are stable systems, resistant to change. To avoid failure and maximize success, implementation of learning analytics at scale requires explicit and careful consideration of the entire TEL technology complex: the different groups of people involved, the educational beliefs and practices of those groups, the technologies they use, and the specific environments within which they operate. It is crucial not only to provide analytics and their associated tools, but also to begin with a clear strategic vision, assess institutional culture critically, identify potential barriers to adoption, develop approaches that can overcome these, and put in place appropriate forms of support, training, and community building. In this paper, we offer tools and case studies that will support educational institutions in deploying learning analytics at scale with the goal of achieving specified learning and teaching objectives. The ROMA Framework offers a step-by-step approach to the institutional implementation of learning analytics and this approach is grounded here by case studies of practice from the UK and Australia

Privacy-driven Design of Learning Analytics Applications – Exploring the Design Space of Solutions for Data Sharing and Interoperability

“…The barriers related to data sharing and interoperability are part of the challenge of scaling up LA. As Ferguson et al (2014b) observe, few reports currently exist in the LA literature regarding deployment of scale. Moving from research and pilot environments to large-scale applications could prove difficult due to lack of data for learning analytics (Cooper & Hoel, 2015;Griffiths, Hoel, & Cooper, 2016).…”

Orchestrating learning analytics (OrLA): Supporting inter-stakeholder communication about adoption of learning analytics at the classroom

“…There is, however, not so much work on supporting inter-stakeholder dialogue to connect supply-side and demandside , even though these knowledge gaps and communication issues have been repeatedly identified as crucial by existing studies on LA adoption (Ali et al, 2013;Ferguson et al, 2014;Lonn, Aguilar, & Teasley, 2013;Macfadyen & Dawson, 2012), and even by studies on innovation implementation before the rise of LA (McIntosh, 1979).…”

Teachers as Producers of Data Analytics: A Case Study of a Teacher-Focused Educational Data Science Program

“…Picciano (2012) notes that higher education lacks qualified professionals, outside of educational data scientists and institutional researchers, trained to use and understand large sets of student data. Regarding learning analytics, Ferguson et al (2014) address this deficit of analytics professionals by suggesting that universities should begin to view the development of human resources as imperative for organization-wide learning analytics adoption. In practice, however, Bichsel (2012) suggests that while university administrators support analytics initiatives, the costs of such initiatives have been prohibitive.…”

“…In the current educational climate that pushes for increased institutional assessment, EDS is in the position to empower teachers not only to use educational analytics tools, but to become active participants in EDS. While the literature on teachers as participants in EDS is starting to gain traction in the learning analytics community (Clow, 2014;Ferguson et al, 2014), to date there have been few empirical studies focusing on teachers' motivations to participate in EDS and on the barriers they face while engaging in data analytics.…”