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The education of deaf and hard of hearing (d/DHH) students is largely dependent on the preferred mode of communication. Historically, the mode of communication for d/DHH students was determined by society rather than by students and families. This resulted in divisiveness between the Deaf culture and proponents of oral communication. The adoption of IDEA allowed family participation in the decision-making process. Advances in technology increased student access to sound, resulting in more educational placement options. Despite the positive changes, the complex nature of hearing loss and the wide variety in cultural considerations have made it difficult to determine the best approach to deaf education. Thus, educators and providers are left in a conundrum of which version of “traditional” deaf education is best for students.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

This paper aims to describe the design and evaluation of a pilot leadership development programme for infection prevention and control (IPAC) professionals during the COVID-19 pandemic. The programme’s aim was to improve IPAC knowledge and capacity in the health-care system by developing the leadership skills and capacities of novice and advanced Infection Control Professionals (ICPs), to respond flexibly, and competently, in their expanding and ever-changing roles.

The leadership programme was piloted with seven nurses, who were part of a clinical nursing team in New South Wales, Australia, over a 12-month period between 2021 and 2022. The programme was designed using a leadership development framework underpinned by transformational leadership theory, practice development approaches and collaborative and experiential learning. These principles were applied during programme design, with components adapted to learners’ interests and regular opportunities provided for collaboration in active learning and critical reflection on workplace experiences.

The authors’ evaluation suggests that the programme was feasible, acceptable and considered to be effective by this cohort. Moreover, participants valued the opportunities to engage in active and experience-based learning with peers, and with the support of senior and experienced ICPs. The action learning sets were well-received and allowed participants to critically reflect on and learn from one another’s experiences. The mentoring programme allowed them to apply their developing leadership skills to real workplace challenges that they face.

Despite a small sample size, the authors’ results provide empirical evidence about the effectiveness of using a practice development approach for strengthening ICP leadership capacity. The success of this pilot study has paved the way for a bigger second cohort of participants in the programme, for which further evaluation will be conducted.

The success of this leadership programme reflects both the need for leadership development in the IPAC professions and the applicability of this approach, with appropriate facilitation, for other professions and organizations.

ICP leadership programmes have not been previously reported in the literature. This pilot study builds on the growing interest in IPAC leadership to foster health system responsiveness and change.

This scoping review article aimed to systematically search the literature on the use, purpose and barriers of information and communication technology (ICT) for culturally and linguistically diverse (CALD) older adults in the host country. The review also conducted a search for literature on programs that aim to develop digital literacy skills for CALD older adults.

A scoping review approach was utilized to identify and search the available literature, and to map the key concepts. A total of 23 relevant articles were included following a systematic search across seven databases.

The review suggests that CALD older adults use ICT for various purposes, including social interaction, health management, information gathering, immigration, everyday routines and leisure. The barriers faced by these older adults in using ICT encompass fear and limited knowledge, language issues, lack of interest, limited access to technology and health concerns. The existing training programs focus on enhancing self-efficacy and confidence and promoting attitudinal changes toward ICT.

Despite the presence of empirical studies, few scoping or systematic reviews have focused on CALD older adults and technology. Research developments related to the technology use of CALD older adults and associated training programs have been fragmented and sporadic, resulting in gaps in the evidence base. This review fills such a gap to better understand the research status connected to CALD older people’s technology adoption and use.

This study explores the determinants of police officer support for pre-arrest/booking deflection programs that divert people presenting with substance use and/or mental health disorder symptoms out of the criminal justice system and connect them to supportive services.

This study analyzes responses from 254 surveys fielded to police officers in Delaware. Questionnaires asked about views on leadership, approaches toward crime, training, occupational experience and officer’s personal characteristics. The study applies a new machine learning method called kernel-based regularized least squares (KRLS) for non-linearities and interactions among independent variables. Estimates from a KRLS model are compared with those from an ordinary least square regression (OLS) model.

Support for diversion is positively associated with leadership endorsing diversion and thinking of new ways to solve problems. Tough-on-crime attitudes diminish programmatic support. Tenure becomes less predictive of police attitudes in the KRLS model, suggesting interactions with other factors. The KRLS model explains a larger proportion of the variance in officer attitudes than the traditional OLS model.

The study demonstrates the usefulness of the KRLS method for practitioners and scholars seeking to illuminate patterns in police attitudes. It further underscores the importance of agency leadership in legitimizing deflection as a pathway to addressing behavioral health challenges in communities.

Quality failures in grid infrastructure construction would cause large-scale collapses in power supply and additional expenditures by reworks and repairs. Learning from quality failures (LFQF) extracts experience from previous quality events and converts them into preventive measures to reduce or eliminate future construction quality issues. This study aims to investigate the influence factors of LFQF in the construction of grid infrastructure.

The related factors of LFQF, including quality management (QM) practices, quality rectification, and individual learning, were identified by reviewing literature about organizational learning and extracting experience from previous failures. A questionnaire survey was distributed to the grid companies in North, Northeast, Northwest, East, Central, and Southwest China. 381 valid responses collected and analyzed using structural equation modeling (SEM) to test the influence of these factors on LFQF.

The SEM results support that QM practices positively affect individual learning and LFQF. Quality rectification indirectly impacts LFQF via individual learning, while the results did not support the direct link between quality rectification and LFQF.

The findings strengthen practical insights into extracting experience from poor-quality issues and continuous improvement. The contributory factors of LFQF found in this study benefit the practitioners by taking effective measures to enhance organizational learning capability and improve the long-term construction quality performance in the grid infrastructure industry.

Existing research about the application of LFQF still stays at the explorative and conceptual stage. This study investigates the related factors of LFQF, including QM practices, quality rectification, and individual learning, extending the model development of learning from failures (LFF) in construction QM.

Prior research suggests that collaboration is key to sustainable community development and environmental management, and peer-to-peer learning (P2PL) may facilitate community building and collaborative learning skills. This study aims to examine the effect of P2PL on the enhancement of environmental management and sustainable development skills, community building and social capital (i.e. connectedness) and understanding of course learning objectives.

Quantitative and qualitative longitudinal survey data was collected in a sustainable development focused course offered at a large American public university that uses P2PL to explicitly facilitate community building and collaborative skills. Safety precautions and changing locational course offerings due to the COVID-19 pandemic in years 2020, 2021 and 2022 provided an opportunity to evaluate the impact of P2PL on these skills during both virtual and in-person formats. Additionally, this study compared in-course student evaluations with students taking other sustainable development-related courses with collaborative learning aspects to understand the wider effectiveness of this course structure.

This study finds that course format (virtual vs in-person) overall made no difference in either connectedness or conceptual understandings, and that students in both formats felt more connected to others than students taking other courses with P2PL. Scaffolding P2PL and supplemental peer support can yield improved connectedness and learning among students taking environmental coursework.

Sustainable development requires group collaboration and partnership building skills. Issues are consistently raised about the challenges to teaching these skills in higher education. The students and instructors in this research study identify P2PL strategies to address these challenges for in-person and virtual classroom settings.

This study is a radical interactionist analysis of family conflict. Drawing on both a negotiated order perspective and Athen's theory of complex dominative encounters, this study analyzes the role that domination plays in conflicts among intimates. As the family engages in repeated conflicts over roles, the family also engages in negotiations over the family order, what role each party should play, interpretations of past events, and plans for the future. These conflicts take place against a backdrop of patriarchy that asymmetrically distributes power in the family to determine the family order. The data from this study come from a content analysis of mothers with substance use problems as depicted in the reality television show Intervention. The conflicts in these families reveal that these families develop a grinding family order in which families engaged in repeated conflict but also continued to operate as and identify as a family. These conflicts are shaped by and reinforce patriarchal expectations that mothers are central to family operation. The intervention at the end of each episode offered an opportunity for the family to engage in a concerted campaign to try to force the mother into treatment and reestablish the family order.

This preliminary study aims to examine the use of a co-designed immersive virtual reality intervention programme in improving access to health care for people with intellectual disability.

A co-production approach was used to design a virtual reality intervention in collaboration with people with intellectual disability, their families and carers. A mixed-method single sample pre-test-post-test design examined using a virtual reality intervention simulating health-care environments to improve access of attending health-care appointments. Qualitative feedback was used to understand participants’ experience and opinions of using the digital technology.

The study found that the intervention did help people access health-care appointment and reduced their fear. Improvements were also found in quality-of-life post intervention. Positive feedback was provided from participants on using digital technologies indicating the novelty of the approach and potential further applications.

To the best of the authors’ knowledge, this is the first study which has used virtual reality to support people with intellectual disability access health care.

This paper aims to center the experiences of three cohorts (n = 40) of Black high school students who participated in a critical race technology course that exposed anti-blackness as the organizing logic and default setting of digital and artificially intelligent technology. This paper centers the voices, experiences and technological innovations of the students, and in doing so, introduces a new type of digital literacy: critical race algorithmic literacy.

Data for this study include student interviews (called “talk backs”), journal reflections and final technology presentations.

Broadly, the data suggests that critical race algorithmic literacies prepare Black students to critically read the algorithmic word (e.g. data, code, machine learning models, etc.) so that they can not only resist and survive, but also rebuild and reimagine the algorithmic world.

While critical race media literacy draws upon critical race theory in education – a theorization of race, and a critique of white supremacy and multiculturalism in schools – critical race algorithmic literacy is rooted in critical race technology theory, which is a theorization of blackness as a technology and a critique of algorithmic anti-blackness as the organizing logic of schools and AI systems.