Data-driven accountability in Australia : an unfolding story with lessons for leaders

Throughout the world, state and nation standardised testing of children, has become a "huge industry" (English, 2002). Although English is referring to the American system which has been involved in standardised testing for over half a century, the same could be said of many other countries, including Australia. It has been only in recent years that Australia has embraced national testing as part of a wider reform effort to bring about increased accountability in schooling. The results of high-stakes tests in Australia are now published in newspapers and electronically on the Australian federal government's MySchool website (www.myschoold.edu.au). MySchool provides results on the National Assessment Program - Literacy and Numeracy (NAPLAN) for students in Years 3,5, 7 and 9. Data are available that compare schools to statistically similar schools. This more recent publication of national testing results in Australia is a visible example of "contractual accountability", described by Mulford, Edmunds, Kendall, Kendall and Bishop (2008) as " the degree to which [actors] are fulfilling the expectations of particular audiences in terms of standards, outcomes and results" (p.20).

Use of 3D visualisation to enhance groundwater stable isotope data and its interpretation, Lockyer Valley, southeast Queensland

The use of stable isotope ratios δ18O and δ2H are well established in assessment of groundwater systems and their hydrology. The conventional approach is based on x/y plots and relation to various MWL’s, and plots of either ratio against parameters such as Clor EC. An extension of interpretation is the use of 2D maps and contour plots, and 2D hydrogeological vertical sections. An enhancement of presentation and interpretation is the production of “isoscapes”, usually as 2.5D surface projections. We have applied groundwater isotopic data to a 3D visualisation, using the alluvial aquifer system of the Lockyer Valley. The 3D framework is produced in GVS (Groundwater Visualisation System). This format enables enhanced presentation by displaying the spatial relationships and allowing interpolation between “data points” i.e. borehole screened zones where groundwater enters. The relative variations in the δ18O and δ2H values are similar in these ambient temperature systems. However, δ2H better reflects hydrological processes, whereas δ18O also reflects aquifer/groundwater exchange reactions. The 3D model has the advantage that it displays borehole relations to spatial features, enabling isotopic ratios and their values to be associated with, for example, bedrock groundwater mixing, interaction between aquifers, relation to stream recharge, and to near-surface and return irrigation water evaporation. Some specific features are also shown, such as zones of leakage of deeper groundwater (in this case with a GAB signature). Variations in source of recharging water at a catchment scale can be displayed. Interpolation between bores is not always possible depending on numbers and spacing, and by elongate configuration of the alluvium. In these cases, the visualisation uses discs around the screens that can be manually expanded to test extent or intersections. Separate displays are used for each of δ18O and δ2H and colour coding for isotope values.

“What’s going on here?” The pedagogy of a data analysis session

Data analysis sessions are a common feature of discourse analytic communities, often involving participants with varying levels of expertise to those with significant expertise. Learning how to do data analysis and working with transcripts, however, are often new experiences for doctoral candidates within the social sciences. While many guides to doctoral education focus on procedures associated with data analysis (Heath, Hindmarsh, & Luff, 2010; McHoul & Rapley, 2001; Silverman, 2011; Wetherall, Taylor, & Yates, 2001), the in situ practices of doing data analysis are relatively undocumented. This chapter has been collaboratively written by members of a special interest research group, the Transcript Analysis Group (TAG), who meet regularly to examine transcripts representing audio- and video-recorded interactional data. Here, we investigate our own actual interactional practices and participation in this group where each member is both analyst and participant. We particularly focus on the pedagogic practices enacted in the group through investigating how members engage in the scholarly practice of data analysis. A key feature of talk within the data sessions is that members work collaboratively to identify and discuss ‘noticings’ from the audio-recorded and transcribed talk being examined, produce candidate analytic observations based on these discussions, and evaluate these observations. Our investigation of how talk constructs social practices in these sessions shows that participants move fluidly between actions that demonstrate pedagogic practices and expertise. Within any one session, members can display their expertise as analysts and, at the same time, display that they have gained an understanding that they did not have before. We take an ethnomethodological position that asks, ‘what’s going on here?’ in the data analysis session. By observing the in situ practices in fine-grained detail, we show how members participate in the data analysis sessions and make sense of a transcript.

Autopoiesis, language, literacy and the brain

When we attempt to speak about the relationship between language, literacy, and the brain, we find ourselves ill equipped to deal with these conceptually and qualitatively different phenomena. Immediately we must straddle different academic traditions that treat each of these as separate “things”. Broadly speaking, the study of language firstly belongs to the domain of biology, then to anthropology, sociology, and linguistics. At its most functional, a study of literacy education is a study of a particular technology, its diffusion techniques, and the abilities and motivations of people to adopt, or adapt themselves to, this technology. The brain is most commonly studied in the field of neurology, which is also a sub-discipline of biology, biochemistry, and medicine.

An indication that non-informative vision eliminates the Kinaesthetic Fusion Effect

This study investigated the Kinaesthetic Fusion Effect (KFE) first described by Craske and Kenny in 1981. The current study did not replicate these findings. Participants did not perceive any reduction in the sagittal separation of a button pressed by the index finger of one arm and a probe touching the other, following repeated exposure to the tactile stimuli present on both unseen arms. This study’s failure to replicate the widely-cited KFE as described by Craske et al. (1984) suggests that it may be contingent on several aspects of visual information, especially the availability of a specific visual reference, the role of instructions regarding gaze direction, and the potential use of a line of sight strategy when referring felt positions to an interposed surface. In addition, a foreshortening effect was found; this may result from a line-of-sight judgment and represent a feature of the reporting method used. The transformed line of sight data were regressed against the participant reported values, resulting in a slope of 1.14 (right arm) and 1.11 (left arm), and r > 0.997 for each. The study also provides additional evidence that mis-perceptions of the mediolateral position of the limbs specifically their separation and consistent with notions of Gestalt grouping, is somewhat labile and can be influenced by active motions causing touch of one limb by the other. Finally, this research will benefit future studies that require participants to report the perceived locations of the unseen limbs.

Are low CO2 emitters in rural areas also socially excluded? An empirical investigation of travel diary data from rural Northern Ireland

The reduction of CO2 emissions and social exclusion are two key elements of UK transport strategy. Despite intensive research on each theme, little effort has so far been made linking the relationship between emissions and social exclusion. In addition, current knowledge on each theme is limited to urban areas; little research is available on these themes for rural areas. This research contributes to this gap in the literature by analysing 157 weekly activity-travel diary data collected from three case study areas with differential levels of area accessibility and area mobility options, located in rural Northern Ireland. Individual weekly CO2 emission levels from personal travel diaries (both hot exhaust emission and cold-start emission) were calculated using average speed models for different modes of transport. The socio-spatial patterns associated with CO2 emissions were identified using a general linear model whereas binary logistic regression analyses were conducted to identify mode choice behaviour and activity patterns. This research found groups that emitted a significantly lower level of CO2 included individuals living in an area with a higher level of accessibility and mobility, non-car, non-working, and low-income older people. However, evidence in this research also shows that although certain groups (e.g. those working, and residing in an area with a lower level of accessibility) emitted higher levels of CO2, their rate of participation in activities was however found to be significantly lower compared to their counterparts. Based on the study findings, this research highlights the need for both soft (e.g. teleworking) and physical (e.g. accessibility planning) policy measures in rural areas in order to meet government’s stated CO2 reduction targets while at the same time enhancing social inclusion.

Utility of routine data sources for feedback on the quality of cancer care: an assessment based on clinical practice guidelines

Background Not all cancer patients receive state-of-the-art care and providing regular feedback to clinicians might reduce this problem. The purpose of this study was to assess the utility of various data sources in providing feedback on the quality of cancer care. Methods Published clinical practice guidelines were used to obtain a list of processes-of-care of interest to clinicians. These were assigned to one of four data categories according to their availability and the marginal cost of using them for feedback. Results Only 8 (3%) of 243 processes-of-care could be measured using population-based registry or administrative inpatient data (lowest cost). A further 119 (49%) could be measured using a core clinical registry, which contains information on important prognostic factors (e.g., clinical stage, physiological reserve, hormone-receptor status). Another 88 (36%) required an expanded clinical registry or medical record review; mainly because they concerned long-term management of disease progression (recurrences and metastases) and 28 (11.5%) required patient interview or audio-taping of consultations because they involved information sharing between clinician and patient. Conclusion The advantages of population-based cancer registries and administrative inpatient data are wide coverage and low cost. The disadvantage is that they currently contain information on only a few processes-of-care. In most jurisdictions, clinical cancer registries, which can be used to report on many more processes-of-care, do not cover smaller hospitals. If we are to provide feedback about all patients, not just those in larger academic hospitals with the most developed data systems, then we need to develop sustainable population-based data systems that capture information on prognostic factors at the time of initial diagnosis and information on management of disease progression.

On the data consumption benefits of accepting increased uncertainty

In the context of learning paradigms of identification in the limit, we address the question: why is uncertainty sometimes desirable? We use mind change bounds on the output hypotheses as a measure of uncertainty and interpret ‘desirable’ as reduction in data memorization, also defined in terms of mind change bounds. The resulting model is closely related to iterative learning with bounded mind change complexity, but the dual use of mind change bounds — for hypotheses and for data — is a key distinctive feature of our approach. We show that situations exist where the more mind changes the learner is willing to accept, the less the amount of data it needs to remember in order to converge to the correct hypothesis. We also investigate relationships between our model and learning from good examples, set-driven, monotonic and strong-monotonic learners, as well as class-comprising versus class-preserving learnability.