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"You're not competent if you're autistic": Barriers and facilitators to identity development in teachers with disabilities in early childhood education.
No full textOral Presentation
Implications for future work - Knowledge Workers' Work from Home (WFH) experiences following COVID-19.
Full text linkThe manifesto for teaching and learning in a time of generative AI: A critical collective stance to better navigate the future.
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Can degree apprenticeships overcome barriers and improve diversity in IT?
No full textThis paper aims to demonstrate that degree apprenticeships can improve diversity in the IT workforce and help to overcome
barriers faced by New Zealand priority learners which deter them from engaging in higher levels of tertiary education. UK
degree apprenticeships are now well established and the impact these have had on social mobility and improving
participation in higher education by their disadvantaged communities is investigated. Early studies identified barriers to
participation and initiatives were designed to address these. Recent UK studies show positive impacts on social mobility,
increased diversity of apprentices and solid increases in productivity. New Zealand priority learners and the barriers they
face are discussed and significant parallels to the barriers faced by disadvantaged groups in the UK are found. Successful
New Zealand initiatives are examined and their common positive factors of mentorship, role modelling, and financial
support could be fulfilled at scale by degree apprenticeship pathway
Top-down target object detection through context.
No full textVisual attention is crucial for identifying the most salient regions in an image. However, when the objective involves higher-level visual tasks, such as target object detection, it becomes necessary to incorporate high-level information to guide the search for the target. This process, known as top-down saliency detection, leverages guidance sources like contextual information and target features to identify regions of interest that are more likely to contain the target object. In this paper, we propose a model that generates top-down saliency maps by adjusting the feature map weights of a universal visual attention model based on contextual information. While contextual information has traditionally been used to understand the gist of an image, it has not been integrated into the creation of saliency maps for target object detection. We demonstrate that incorporating contextual information into a visual attention model enhances target object detection performance. The proposed model, tested on six datasets, shows significant improvements in detecting target objects compared to models that do not utilize contextual information
