Spiritual and Pedagogical Accompaniment (SPA) program 2022

[Extract] This report accompanies the 2019-2021 Spiritual and Pedagogical Accompaniment (SPA) Program Report (https://acuspaprogram.edu.au/wp-content/ uploads/2022/09/ACU-SPA-evaluation-report.pdf) with updated information using the 2022 findings about impact of the program on pre-service teacher preparation for the profession. It also includes greater links to a variety of stakeholder voices about the impact of SPA from across the life of the program. The SPA program focuses on strengthening PSTs’ understanding of Catholic spirituality, mission, professional identity, and teaching practices. The name was amended in 2021 to recognise the interweaving nature of spirituality across all subject areas, the multifaith context of students and teachers in Catholic schools, and the support the Companions in the project provide to the PSTs in both spirituality and pedagogy. The program was piloted in 2019 with a small teaching and learning development grant from ACU, in 2020 a small BCE research grant and has since received Brisbane Catholic Education funding from 2021 onwards. In 2022 the Toowoomba Diocese provided funding to pilot a regional model. The program aligns with the Brisbane Catholic Education (BCE) priority to develop and maintain an employment force, while supporting schools and staff in BCE’s priority area of sustaining strong Catholic identities. The model includes PST’s having greater involvement with their SPA school, stronger connection to the SPA school Diocese, more support across their experience from the university through the university coordinator, and support across their experience from a Spiritual and Pedagogical Companion

Spiritual and Pedagogical Accompaniment (SPA) program (2019-2021)

[Extract] This report outlines the findings from the Spiritual and Pedagogical Accompaniment (SPA) Program from 2019-2021. This program focuses on strengthening PSTs’ understanding of Catholic spirituality, mission, professional identity, and teaching practices. It aligns with the Brisbane Catholic Education (BCE) priority to develop and maintain an employment force, while supporting schools and staff in BCE’s priority area of sustaining strong Catholic identities. The model includes greater involvement with their SPA school, and the support across their experience from a Spiritual and Pedagogical Companion

FJMP: Factorized Joint Multi-Agent Motion Prediction

Multi-agent motion prediction is an important problem in an autonomous driving pipeline, and it involves forecasting the future behaviour of multiple agents in complex driving environments. Autonomous vehicles (AVs) should produce accurate predictions of future agent behaviour in order to make safe and informed plans in safety-critical scenarios. Importantly, AVs should generate scene-consistent future predictions that predict the joint future behaviour of multiple agents, as this enables reasoning about potential future multi-agent interactions, which are critical for downstream planning. In this thesis, we address the problem of generating a set of scene-level, or joint, future trajectory predictions in multi-agent driving scenarios. To this end, we propose FJMP, a Factorized Joint Motion Prediction framework for multi-agent interactive driving scenarios. FJMP models the future scene interaction dynamics as a sparse directed interaction graph, where nodes represent agents and edges denote explicit interactions between agents. We then prune the graph into a directed acyclic graph (DAG) and decompose the joint prediction task into a sequence of marginal and conditional predictions according to the partial ordering of the DAG, where joint future trajectories are decoded using a directed acyclic graph neural network (DAGNN). We conduct experiments on two autonomous driving datasets and demonstrate that FJMP produces more accurate and scene-consistent joint trajectory predictions than existing approaches. Importantly, we show that FJMP produces superior joint forecasts compared to non-factorized approaches on the most interactive and kinematically interesting agents, which highlights the benefit of our proposed factorization

FJMP: Factorized Joint Multi-Agent Motion Prediction over Learned Directed Acyclic Interaction Graphs

Predicting the future motion of road agents is a critical task in an autonomous driving pipeline. In this work, we address the problem of generating a set of scene-level, or joint, future trajectory predictions in multi-agent driving scenarios. To this end, we propose FJMP, a Factorized Joint Motion Prediction framework for multi-agent interactive driving scenarios. FJMP models the future scene interaction dynamics as a sparse directed interaction graph, where edges denote explicit interactions between agents. We then prune the graph into a directed acyclic graph (DAG) and decompose the joint prediction task into a sequence of marginal and conditional predictions according to the partial ordering of the DAG, where joint future trajectories are decoded using a directed acyclic graph neural network (DAGNN). We conduct experiments on the INTERACTION and Argoverse 2 datasets and demonstrate that FJMP produces more accurate and scene-consistent joint trajectory predictions than non-factorized approaches, especially on the most interactive and kinematically interesting agents. FJMP ranks 1st on the multi-agent test leaderboard of the INTERACTION dataset.Comment: CVPR 202

What do secondary teachers think about digital games for learning : Stupid fixation or the future of education?

Digital games can support learning across many levels and fields of education. This article shares findings from a study of Australian high school English teachers designed with a mixed response questionnaire about using digital games in the classroom. The findings identified polarised teacher perspectives on the role of gaming in formal curriculum, tension in teachers’ ideal and enacted use of digital games, and a need for in-practice professional development on digital games. Implications include the need to optimise digital games use for learning in teaching and teacher education, and to address perceptions on the validity of gaming for classroom learning

Video gaming and digital competence among elementary school students

Engagement with video games can potentially advance student digital competence however, there is a digital skills gap by the time young people progress into adolescence. This current research explores how elementary school students’ digital self-efficacy might relate to experiences in video game environments to influence perceptions of digital competence. We examine the differential impact of sex, self-efficacy, and socioeconomic status (SES) on 7–10-year-old students’ (N = 613) perceptions of video gaming and their digital skills. Analysis revealed the unexpected finding that SES was inversely related to enjoyment for gaming and digital technology, with students in the lower-SES category responding more positively compared to students in higher SES categories. As expected, boys self-reported digital skills higher than girls across all SES categories. We argue for the use of gaming pedagogies to support learning in classrooms that accounts for nuances in students’ digital self-efficacy moderated by gender and SES

Advice on healthy eating and physical activity where it is needed most : empowering home-visiting human services to provide the right information at the right time to vulnerable families

Background: Excessive weight gain adversely impacts on the health, social and economic wellbeing of children and families. The aim of this pilot study was to assess the feasibility of a practice change intervention to improve the physical activity and healthy eating support offered by staff of human service organisations during home visits. Methods: The study employed a pre-post design. Sixty nine support staff and 29 managers from human service organisations from the Hunter New England Area Health Service (HNEAHS) region of NSW participated in the trial. Research officers provided staff with healthy eating and physical activity training, telephone support and resources, and encouraged managers to adopt a healthy eating and physical activity policy, and to support their staff in providing healthy eating and physical activity guidance to families. Results: Compared to pre-intervention, support staff of human service organisations were more likely to provide healthy eating and physical activity support to client families. The intervention was found to be acceptable to staff and managers. Conclusion: The findings of this study suggest that a variety of supportive, practice change initiatives may be a feasible approach to increasing obesity prevention support provided to disadvantaged families by human service organisation staff

autopsych : An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects

In this paper, we present autopsych, a novel online tool that allows school assessment experts, test developers, and researchers to perform routine psychometric analyses and equating of student test data and to examine the effect of student demographic and group conditions on student test performance. The app extends current open-source software by providing (1) extensive embedded result narration and summaries for written reports, (2) improved handling of partial credit data via customizable item-person Wright maps, (3) customizable item- and person-flagging systems, (4) item-response theory model constraints and controls, (5) many-facets Rasch analysis to examine item bias, (6) Rasch fixed item equating for mapping student ability across test forms, (7) tabbed spreadsheet outputs and immediate options for secondary data analysis, (8) customizable graphical color schemes, (9) extended ANOVA analysis for examining group differences, and (10) inter-rater reliability analyses for the verifying the consistency of rater scoring systems. We present the app’s architecture and functionalities and test its performance with simulated and real-world small-, medium-, and large-scale assessment data. Implications and planned future developments are also discussed

Long-term results of protocol kidney biopsy directing steroid withdrawal in simultaneous pancreas-kidney transplant patients

Introduction: We sought to determine whether protocol biopsies could be used to guide treatment and improve outcomes in simultaneous pancreas-kidney (SPK) patients. Methods: Between 2004 and 2013, protocol biopsies were performed on SPK patients at 3–6 months and one year post-transplant. Maintenance immunosuppression consisted of a calcineurin inhibitor, anti-proliferative agent, and corticosteroid. Corticosteroid was withdrawn in negative early biopsies, maintained in subclinical/ borderline biopsies, and increased if Banff IB or greater rejection was identified. Endpoints included presence of interstitial fibrosis and tubular atrophy on biopsy at one year (IF/TA), rejection episodes, and renal and pancreas function at five years’ followup. Results: Forty-one SPK transplant patients were reviewed and a total of 75 protocol biopsies were identified. On early biopsy, 51% had negative biopsies, 44% had borderline rejection, and 5% had subclinical rejection. Renal and pancreas function were not significantly different at one, two, and five years post-transplant between negative vs. borderline early biopsy patients. No difference in the degree of IF/TA was found between these two groups. Conclusions: To our knowledge, this is the first study to evaluate protocol biopsies as an investigative tool prior to steroid withdrawal in SPK patients. Our study suggests that there are no detrimental functional or histological effects at five years post-transplant, despite weaning steroids in the negative biopsy group

Sheep Updates 2014

This session covers nine papers from different authors: Genetic Research: A brave new world of opportunities 1. China\u27s Appetite - The implications for WA, James Kynge, Chairman, FT Confidential Research, Emerging Markets Editor, Financial Times, London. 2. The genetics warm-up - the secret language of genetic research and its impacts on WA\u27s sheep flock, Professor David Lindsay, University of Western Australia, Perth WA The strength of genetic data: is it really valuable? 3. Genetic research in Western Australia - What have the compromises in production been? Johan Greeff, Senior Geneticist, Department of Agriculture and Food Western Australia 4. Show me the money - the case for genetic selection, John Young, Farming Systems Analysis Service, Kojonup WA 5. Using ASBVs and Indexes, Luke Stephen, Project Officer MERINOSELECT, Sheep Genetics, Armidale NSW Concurrent 6. New traits for the sheep industry, Dr Graham Gardner, Associate Professor in Biochemistry, Toxicology and Nutrition at Murdoch University, WA 7. Genomics and DNA testing: new tools for ram breeders to accelerate gain Dr Stephen Lee, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy Campus, SA 8. Producer case study: using genetic data and tools to make a better product, Bindi Murray, Livestock Manager, Kunmallup Pastoral Co, Woodanilling WA. 9. New Sheep CRC - vision for future genetic progress, James Rowe, CEO, Sheep CRC, UNE, Armidale NS