Academic Analytics and the Completion Agenda (#LAK12)

In a survey of the use of academic analytics Goldstein (2005) finds that the level of satisfaction with academic analytics increases as the complexity of the technology platform increases, which seems to suggest this offsets the 50% higher investment such technologies require to implement. The survey also reveals that central finance, central admissions and institutional research are the most likely users with department head and staff, deans and their staff and central human resources least likely to engage.

More recently the need to measure learning outcomes and increase student retention is changing the nature of analytics. Financial and strategic imperatives mean analytics that can prevent drop-outs are gaining the attention of senior figures and technology providers. At a conference of colleges in the US Gliniecki expressed this by suggesting “we used to focus on just bringing them in, but now it’s about what happens to them”. And Bill Truehart, president of Achieving the Dream, summarises that “there is a different expectation now, and it is about completion.”

I always wonder how someone ‘completes’ learning, especially in the context of the lifelong agenda (and the infinite rooms philosophy) – to what extent is modelling programme completion a useful tool for learning?  ‘Teaching to the test’ is a common reported problem across English schools that draws from a form of analytics that represents itself in the school league table. Here examinations, the typcial measure of completion, combine hierarchical survelliance and normalise judgement (Foucault, 1977). In this sense analytics may become a tool for exercising power – possibly why Goldstein finds such popularity for their use within central adminsitration. Modelling social relationships as an “index of power” seems to be a commonly understood goal in mobile phone analytics for example.

Goldstein concludes that our ability to achieve advances in academic analytics is not likely to be limited by technology. It will be understanding the meaning of data and not using tools is likely to present the biggest challenge. One must hope however that the field does not succumb to information as an implosion of meaning. Baudrillard suggests that where we think information produces meaning, the opposite occurs – information devours its own content. In the hyperreal society the real becomes confused with the model. This seems a very pertinent warning when trying to model student behaviour in the context of completion. I am aware of many occassions when “completion” was not a motivation for me undertaking some study and bore no relation to my experience of learning. It is crucial that the student, and not their data, remains the focus of learning.


Baudrillard, J. (1994). Simulacra and Simulation. Ann Arbor: The University of Michigan Press.

Goldstein, P. J. (2005). Academic Analytics : The Uses of Management Information and Technology in Higher Education. Retrieved from

Foucault, M. (1977). Discipline and Punish: The Birth of the Prison (1991st ed.). London: Penguin.

Kolowich, S. (2010). Technology and the Completion Agenda. Inside Higher Ed. Retrieved from

Kolowich, S. (2010). The Completion Agenda. Inside Higher Ed. Retrieved from