The learning analytics readiness instrument

Abstract

Little is known about the processes institutions use when discerning their readiness to implement learning analytics. This study aims to address this gap in the literature by using survey data from the beta version of the Learning Analytics Readiness Instrument (LARI) [1]. Twenty-four institutions were surveyed and 560 respondents participated. Five distinct factors were identified from a factor analysis of the results: Culture; Data Management Expertise; Data Analysis Expertise; Communication and Policy Application; and, Training. Data were analyzed using both the role of those completing the survey and the Carnegie classification of the institutions as lenses. Generally, information technology professionals and institutions classified as Research Universities-Very High research activity had significantly different scores on the identified factors. Working within a framework of organizational learning, this paper details the concept of readiness as a reflective process, as well as how the implementation and application of analytics should be done so with ethical considerations in mind. Limitations of the study, as well as next steps for research in this area, are also discussed.

Where is the evidence?

“…The first relates to the Learning Analytics Readiness Instrument (LARI), designed to help institutions gauge their readiness to implement learning analytics. It is ready for use, but has not yet been deployed (N=560 respondents, 24 institutions) [49]. The second analyses the financial benefits for an institution of using an early alert system.…”

Guiding Early and Often: Using Curricular and Learning Analytics to Shape Teaching, Learning, and Student Success in Gateway Courses

“…The emergence of analytics in higher education institutions is a relatively recent occurrence. While the corporate world has used the nomenclature “business intelligence” for decades, analytics as a term, much less a process, was not used in colleges and universities until Goldstein and Katz () put forth “academic analytics” for the first time (Oster, Lonn, Pistilli, & Brown, ). Bischel () defines analytics as “the use of data, statistical analysis, and explanatory and predictive models to gain insights and act on complex issues” (p. 6).…”

“…Oster et al. () go further, describing readiness as “a necessary condition for institutions to be able to perform educational functions consistent with their individual missions … particularly towards student success” (p. 174). The reflective process that Arnold et al.…”

“…() and Oster et al. () propose is one that any institution should consider using, as it has the potential to produce a great deal of organizational learning involving large swaths of the college or university community.…”

“…Additionally, analytics is not a solitary process; as Oster et al. () and Pistilli et al. () describe, multiple staff participants from across many different facets of an institution are needed to implement analytics effectively.…”