Reducing grant application numbers : the shame stick or prize carrot?

Researchers spend an average of 38 working days preparing an NHMRC Project Grant proposal, but with success rates of just 15% then over 500 years of researcher went into failed applications in 2014. This time would likely have been better spent on actual research. Many applications are non-competitive and could possibly be culled early, saving time for both researchers and funding agencies. Our analysis of the major health and medical scheme in Australia estimated that 61% of applications were never likely to be funded...

Grant application: QUT Learning and Teaching scheme 2012 Cracking the Code - A checklist to complement CRAs for first year Justice students.

Widening participation brings with it increasing diversity, increased variation in the level of academic preparedness (Clarke, 2011; Nelson, Clarke, & Kift 2010). Cultural capital coupled with negotiating the academic culture creates an environment based on many assumptions about academic writing and university culture. Variations in staff and student expectations relating to the teaching and learning experience is captured in a range of national and institutional data (AUSSE, CEQ, LEX). Nationally, AUSSE data (2009) indicates that communication, writing, speaking and analytic skills, staff expectations are quite a bit higher than students. The research team noted a recognisable shift in the changing cohort of students and their understanding and engagement with feedback and CRAs, as well as variations in teaching staff and student expectations. The current reality of tutor and student roles is that: - Students self select when/how they access lectures and tutorials. - Shorter tutorial times result in reduced opportunity to develop rapport with students. - CRAs are not always used consistently by staff (different marking styles and levels of feedback). - Marking is not always undertaken by the student’s tutor/lecturer. - Student support services might be recommended to students once a poor grade has been given. Students can perceive this as remedial and a further sense of failure. - CRA sheet has a mark /grade attached to it. Stigma attached to low mark. Hard to focus on the CRA feedback with a poor mark etched next to it. - Limited opportunities for sessionals to access professional development to assist with engaging students and feedback. - FYE resources exist, however academic time is a factor in exploring and embedding these resources. Feedback is another area with differing expectations and understandings. Sadler (2009) contends that students are not equipped to decode the statements properly. For students to be able to apply feedback, they need to understand the meaning of the feedback statement. They also need to identify, the particular aspects of their work that need attention. The proposed Checklist/guide would be one page and submitted with each assessment piece thereby providing an interface to engage students and tutors in managing first year understandings and expectations around CRAs, feedback, and academic practice.

Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model

Background A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7–December 31, 2009, at a postal area level in Queensland, Australia. Method We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space–time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. Results The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: −0.341; 95% credible interval (CI): −0.370–−0.311) and the socio-economic index for area (SEIFA) (posterior mean: −0.003; 95% CI: −0.004–−0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007–0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Conclusions Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period.