PIRAC

Resources: Original IRAC paper, Using PIRAC

PIRAC (Purpose, Information, Representation, Affordances, Change) is a framework for offering a bit of design guidance for learning analytics first formulated in Jones et al (2013) - much of the following originated in that paper

The idea is that application sof learning analytics/data-informed-teaching will be more effective if consideration of all parts of the PIRAC framework are considered. The argument is that too much of learning analytics focuses on the information and representation aspects and not enough on the other aspects.

Purpose#

Olmos & Corrin (2012), amongst others, reinforce the importance for learning analytics to start with “a clear understanding of the questions to be answered” (p. 47) or the task to be achieved. If you start the design of a learning analytics tool/intervention without a clear idea of the task (and its context) in mind, then it’s going to be difficult to implement.

Why are we doing this? What's the purpose? Whose purpose? What is the nature of the context and the learning task? Who is involved? How will they be involved in the design?

Information#

Is all the relevant Information and only the relevant information available?

While there is an “information explosion”, the information we collect is usually about “those things that are easiest to identify and count or measure” but which may have “little or no connection with those factors of greatest importance” (Norman, 1993, p. 13). This leads to Verhulst’s observation (cited in Bollier & Firestone, 2010) that “big data is driven more by storage capabilities than by superior ways to ascertain useful knowledge” (p. 14). There are various other aspects of information to consider. For instance, is the information required technically and ethically available for use? How is the information to be cleaned, analysed and manipulated? Is the information sufficient to fulfill the needs of the task? In particular, does the information captured provide a reasonable basis upon which to “contribute to the understanding of student learning in a complex social context such as higher education” (Lodge & Lewis, 2012, p. 563)?

Representation#

Does the Representation of the information aid the task being undertaken?

A bad representation will turn a problem into a reflective challenge, while an appropriate representation can transform the same problem into a simple, straightforward task (Norman, 1993). Representation has a profound impact on design work (Hevner, March, Park, & Ram, 2004), particularly on the way in which tasks and problems are conceived (Boland, 2002). In order to maintain performance, it is necessary for people to be “able to learn, use, and reference necessary information within a single context and without breaks in the natural flow of performing their jobs.” (Villachica et al., 2006, p. 540). Olmos and Corrin (2012) suggest that there is a need to better understand how visualisations of complex information can be used to aid analysis. Considerations here focus on how easy is it to understand the implications and limitations of the findings provided by learning analytics?

Affordances#

Are there appropriate Affordances for action?

A poorly designed or constructed artefact can greatly hinder its use (Norman, 1993). For an application of information technology to have a positive impact on individual performance it must be utilised and be a good fit for the task it supports (Goodhue & Thompson, 1995). Human beings tend to use objects in “ways suggested by the most salient perceived affordances, not in ways that are difficult to discover” (Norman, 1993, p. 106). The nature of such affordances are not inherent to the artefact, but are instead co-determined by the properties of the artefact in relation to the properties of the individual, including the goals of that individual (Young, Barab, & Garrett, 2000). Glassey (1998) observes that through the provision of “the wrong end-user tools and failing to engage and enable end users” even the best implemented data warehouses “sit abandoned” (p. 62). Tutty, Sheard and Avram (2008) suggest there is evidence that institutional quality measures not only inhibit change, “they may actually encourage inferior teaching approaches” (p. 182). The consideration for affordances is whether or not the tool and the surrounding environment provide support for action that is appropriate to the context, the individuals and the task.

Change#

How will the information, representation and the affordances be Changed?

The idea of evolutionary development has been central to the theory of decision support systems (DSS) since its inception in the early 1970s (Arnott & Pervan, 2005). Rather than being implemented in linear or parallel, development occurs through continuous action cycles involving significant user participation (Arnott & Pervan, 2005). Beyond the systems, there is a need for the information being captured to change. Buckingham-Shum (2012) identifies the risk that research and development based on data already being gathered will tend to perpetuate the existing dominant approaches from which the data was generated. Bollier and Firestone (2010) observe that once “people know there is an automated system in place, they may deliberately try to game it” (p. 6). Universities are complex systems (Beer, Jones, & Clark, 2012) requiring reflective and adaptive approaches that seek to identify and respond to emergent behaviour in order to stimulate increased interaction and communication (Boustani et al., 2010). Potential considerations here include, who is able to implement change? Which, if any, of the three prior questions can be changed? How radical can those changes be? Is a diversity of change possible?

References#

Jones, D., Beer, C., & Clark, D. (2013). The IRAC framwork: Locating the performance zone for learning analytics. In H. Carter, M. Gosper, & J. Hedberg (Eds.), Electric Dreams. Proceedings ascilite 2013 (pp. 446--450).