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A Pragmatic Approach to Using Artificial Intelligence and Virtual Reality in Digital Game-Based Language Learning
Get PDFComputer Assisted Language Learning (CALL) applications have many benefits for language learning. However, they can be difficult to develop for low-resource languages such as Irish and the other Celtic languages. It can be difficult to assemble the multidisciplinary team needed to develop CALL resources and there are fewer language resources available for the language. This paper provides an overview of a pragmatic approach to using Artificial Intelligence (AI) and Virtual Reality (VR) in developing a digital game-based language learning (DGBLL) app for Irish. This pragmatic approach was used to develop Cipher - a DGBLL app for Irish (Xu et al, 2022b) where a number of existing resources including text repositories and NLP tools were used. In this paper the focus is on the incorporation of Artificial Intelligence (AI) technologies including AI image generation, text-to-speech (TTS) and Virtual Reality (VR), in a pedagogically informed manner to support language learning in a way that is both challenging and enjoyable. Cipher has been designed to be language independent and can be adapted for various cohorts of learners and for other languages. Cipher has been played and tested in a number of schools in Dublin and the feedback from teachers and students has been very positive. This paper outlines how AI and VR technologies have been utilised in Cipher and how it could be adapted to other Celtic languages and low-resource languages in general
‘I’m not burning out, I’m rusting out’: investigating the causes of rustout in teacher educators in Ireland and the United Kingdom
Get PDFHigher Education-Based Teacher Educators (TEs) are responsible for the preparation of future teachers across the continuum of education. However, despite their significant role in the education ecosystem, their well-being and professional satisfaction often remain overlooked in research and policy. For example, while burnout among academics is extensively studied, it remains under-researched, particularly among TEs. Even less attention is paid to rustout, a phenomenon characterised by professional underutilisation, intellectual stagnation and unfulfillment. Rustout is not a universal experience. However, its presence acknowledges that occupational stress is non-linear and nuanced and that it can vary depending on organisational and personal resources. Like its better-known counterpart, burnout, untreated rustout can have individual and organisational consequences, such as poor mental health,
career dissatisfaction and accelerated employee turnover. Through an analysis of surveys and
interviews with TEs across Ireland and the United Kingdom (UK), we explore the factors that may contribute to rustout. Guided by rustout literature and validated through collaborative reflection, this paper reveals three core themes: (1) administrative overload and erosion of
autonomy, (2) misalignment between professional aspirations and job tasks and (3) systemic barriers to professional growth. Some participants reported being ‘prevented from thriving’, while others actively sought ways to mitigate rustout through new challenges or external
opportunities. More broadly, the study shines a light on the ‘silence’ surrounding rustout in academia. The findings also highlight the detrimental effects of rustout on individual wellbeing and suggest that it is not merely a pre-retirement phenomenon but can emerge at
various stages of a TE’s career. Practical implications emphasise the need for Higher Education (HE) sectors and leaders to put ‘rustout’ on the mental health literacy agenda, to balance job demands with resources and to acknowledge the trade-off that can occur when operational efficiency is prioritised over professional well-bein
Brain tumor segmentation using MRI images
No full textThis thesis concentrates on the development and optimization of a deep learning methodology for precise brain tumor segmentation utilizing multi-modal MRI data and advanced methods such as attention mechanisms and optimization techniques. Brain tumor segmentation is an essential part of diagnostic and treatment planning; yet, it presents difficulties due to the intricate morphology of tumors, fluctuating intensity levels, and the necessity for models that generalize effectively across heterogeneous datasets. This research incorporates attention mechanisms and optimization techniques into a CNN-based architecture to enhance the accuracy and robustness of tumor segmentation in both public (BraTS) and real clinical datasets.
The proposed model employs multi-modal MRI sequences (T1, T2, T1ce, FLAIR) to acquire complementary information, hence enhancing segmentation accuracy by emphasizing certain features within each modality. Attention processes are integrated to improve the model’s capacity to discern crucial areas, especially in challenging instances with fuzzy tumor margins. Furthermore, innovative optimization
methodologies, including the Multiverse Optimizer (MVO), Red Deer Algorithm (RDA), and Ebola Optimization Search Algorithm (EOSA), are utilized to enhance feature selection, optimize hyperparameters, and guarantee effective training. The findings indicate that integrating attention mechanisms with improved model parameters markedly enhances performance metrics, including the Dice Similarity Coefficient
(DSC) and Intersection over Union (IoU), resulting in superior segmentation outcomes relative to contemporary approaches.
To ensure practical applicability, the research includes the development of a Brain tumor segmentation using MRI images Docker-based API that enables straightforward deployment of the segmentation model in clinical environments, delivering real-time outcomes and seamless connection
with hospital systems. Additionally, explainability techniques like Grad-CAM are utilized to elucidate the model’s decision-making process, hence augmenting trust and reliability for clinical applications. The research findings underscore the possibility of integrating deep learning, attention mechanisms, and explainability tools to develop effective and clinically pertinent solutions for brain tumor segmentation, hence enhancing diagnostic processes and patient outcomes
“Just a Cog a Big Machine”. A study of prevalence, intervention and psychological experience in the aftermath of burnout and work-related mental illness in Irish hospital doctors
Get PDFBurnout and psychological distress continue to be prevalent issues for practising physicians. This programme of research aimed to determine the prevalence of work stress and burnout of Irish hospital doctors, to identify priority interventions to tackle work stress and burnout in this group and to expand our understanding of the psychological experiences of hospital doctors in the aftermath of work-related mental health crises. This programme of research included a national cross-sectional survey of 1,749 hospital doctors, a qualitative, deductive, thematic analysis of 32 hospital doctors of mixed grade from the survey cohort and an in-depth, descriptive phenomenological analysis of the experiences of 6 senior consultant hospital doctors from the survey cohort. Study 1 found that almost one third of hospital doctors were experiencing burnout, 59.7% of
respondents had low levels of work life-balance, 81.9% had high levels of work stress with the efforts of work not balanced by the rewards of work, furthermore 29.2% reported insufficient work ability. Study 2 found that adequate staffing levels, statutory leave and adequate cover when on leave are the most urgently needed interventions for tackling work stress and burnout among hospital doctors in Ireland. Findings indicate that doctors do not receive the support they need from their clinical line managers. Study 3 provided a rich description of how senior consultants use reflective processes to come to terms with experiences of mental health crisis. In the aftermath of this major, negative life event doctors engaged in two types of reflection, ‘situational sense-making’ to make sense of their experiences and ‘transformative self-reflection’ which involves reflection in a deeper way on themselves and their lives on a broader scale. The process of coming to terms with mental health crisis
was complicated when support from employers was perceived as poor. Findings suggest that hospital doctors in Ireland have higher levels of burnout than their international peers. Primary interventions which work on fundamental, system issues such as shortcomings in staffing, cover and leave should be prioritised to tackle work stress and burnout. Doctors who supervise others need to be resourced with training and time to excel as people managers. Doctors themselves can help by rejecting mental health stigmatisation, embracing compassion and self-care and role modelling healthy habits to their peers and junior colleagues. Reflective processes which contribute to recovery from burnout and mental health crisis should be encouraged and special attention should be paid to the support provided by the employer and supervisors during help seeking, recovery, return to work and beyond, as being poorly supported at this vulnerable time can deepen distress experienced
Image Registration and Deep NeuroFuzzy Networks for Mitigating Atmospheric Turbulence Effects in Consumer-Based Optical Imaging
Get PDFConsumer-based optical imaging systems are characterized as big data processing systems, which are drastically affected by atmospheric turbulences that add geometric distortions and blur effect to the images when used in outdoor condition. Physics-grounded simulators have been proposed recently to generate synthetic data but the generalization to the real-world turbulent images is not so good. In this paper, we combine the characteristics of image registration, deep neurofuzzy methods, and channel-attention based discriminative learning strategy to propose image registration, neurofuzzy based denoising, and deblurring network (RND2Net). The RND2Net is designed on a principle that it does not require turbulent image pairs (ground truth images) to train the network, which closely resembles the real-world situation used as consumer devices. The registration module focuses on the region-based fusion techniques while the denoising and deblurring module incorporates deep neurofuzzy network along with dense residual blocks and channel attention mechanism to train the network. The RND2Net is also designed to reduce the noise and blur effect from images, while generalizing on the down-stream tasks, such as text recognition. Experimental results show that the RND2Net yields better performance quantitatively as qualitatively on synthetic and real-world datasets in comparison to existing state-of-the-art methods
The urban political ecology of worsening flooding in Phnom Penh, Cambodia: Neopatrimonialism, displacement, and uneven harm
Get PDFThis paper investigates worsening flooding damage recently experienced in Phnom Penh, Cambodia. Contrary to Cambodia government leadership assertions that these floods have been caused by climate change, the study adopts an urban political ecology framework to uncover their actual underlying causes, which are rooted in political decisions, economic interests, and prevailing power dynamics. We argue that three processes have significantly contributed to the adverse flooding outcomes. First, rapid and uncoordinated urban land transformations have exacerbated flooding, disproportionately benefiting the economic elites. Second, inadequate governance of waste management systems and flood protection infrastructure has further compounded flooding. Last, state-sanctioned land reclamation projects of lakes and wetlands, which favor business and political elites, have displaced the urban poor and rendered the city, but particularly this group, more susceptible to flooding risks. All these processes are linked to Cambodia’s neopatrimonial political economic system, and are sustained by informal practices, coercion, and financial profits for elites. The urban poor tend to suffer the most, facing displacement risks and worsening vulnerability to floods. Our research transcends the rural-urban dichotomy, revealing the interconnectedness of this system across different contexts, including the influence of illicit gains from land enclosures on development.
It also aims to contribute to international debates by highlighting that flood damage and losses are not solely caused by climate change but are
also shaped by political-economic factors specific to each location
Medical student experiences of Case-Based Learning (CBL) at a multicultural medical school
Get PDFEducational research highlights active approaches to learning are more efective in knowledge retention and problem-solving. It has long been acknowledged that adapting to more active ways of learning form part
of the challenge for new university students as the pedagogical distance between the didactical approach largely followed by secondary school systems the world over difers quite signifcantly from the often more student-led, critical approach taken by universities. University students encounter various learning challenges, particularly during the transition from secondary school to university. Poor adaptation and low performance in the frst year of tertiary education can lead to higher failure rates and potential withdrawal from study programmes. Adopting active
learning strategies early in this transition phase is crucial for supporting students’ adaptation and success. Gaining student engagement with active learning can be a signifcant challenge when there is an expectation to participate in a discussion or voice an opinion. Case-based learning (CBL), with its scafolded form of learning, is an approach that could provide the support needed to help multicultural learners adapt to their new learning environment in a non-threatening classroom-based setting. The research question in this study was: what features of CBL
support active learning
Preliminary Findings from an Integrated STEM Intervention using Programmable Robotics in Irish Primary Schools: Building a Real-World Integrated Curriculum in STEM
Get PDFThis paper presents the design and implementation of a multi-phase research project evaluating an integrated STEM intervention (BRICS) using programmable robotics (LEGO SPIKE Essentials) in Irish primary schools (n = 14) during the 2024-25 academic year. Preliminary findings from Phase One are reported. Prior to engaging with the BRICS intervention, both teachers (n = 19), and children (n = 338) aged 9 – 12 years, self-reported broadly neutral-to-positive STEM-related attitudes and self-efficacy. Furthermore, both participant groups were found to hold attitudes toward science which were less positive by comparison to other STEM disciplines. Interviews with professional learning leaders (n = 2) suggest this may be attributed to teachers holding varying STEM-related confidences
Perceptions of coastal vegetated ecosystems: A systematic review across geographical and sectoral dimensions
Get PDFCoastal vegetated ecosystems such as mangrove forests, seagrass meadows, and tidal marshes provide a wide array of ecosystem services. They also play a vital role in climate change mitigation through carbon
sequestration. However, they are among the most threatened ecosystems globally. This study addresses a key knowledge gap by conducting a systematic review of academic literature on sectoral perceptions of these ecosystems. Through content analysis, we identified
common research themes across regions and examined how members of the public, private, and civil society sectors perceive coastal vegetated ecosystems. The results reveal regional differences: Asian countries tend to emphasize utilization and economic benefits, while North
America and Europe focus more on conservation and management. Several studies explored perceptions of climate change mitigation. Our findings highlight gaps in perception between the private and government agencies. Understanding these diverse sectoral perspectives can
inform policy interventions to enhance conservation efforts and strengthen governance strategies
Cur chuige ionchuimsitheach i dteagasc na léitheoireachta Gaeilge sna hardranganna bunscoile i scoil tumoideachais
Get PDFI suíomhanna tumoideachais in Éirinn bíonn daltaí tumtha i dteanga nach teanga an bhaile í ag a bhformhór. Sna hardranganna bunscoile cleachtar léitheoireacht na Gaeilge agus an Bhéarla. Ach is beag eolas atá againn ar an dóigh a léann páistí tumoideachais sa Ghaeilge, sa dá theanga nó ar na scileanna agus straitéisí a bhíonn in úsáid acu agus iad ag léamh. Tá ganntanas treorach agus taighde ann ar an bhealach is éifeachtaí leis an délitearthacht a chur chun cinn, nó le freastal ar riachtanais dhifriúla na bpáistí thar dhá theanga. Le cleachtas ionchuimsitheach a chur chun cinn tá géarghá leis an eolas seo. Sa staidéar seo baintear úsáid as measúnaithe múnlaitheacha, ailt taighde agus ábhar léitheoireachta nua le múinteoirí a spreagadh le machnamh a dhéanamh ar an gcleachtas reatha. Fiosraítear grúpaí dírithe léitheoireachta mar fhéidearthacht le freastal ar riachtanais éagsúla agus le tacú le múinteoirí cur lena straitéisí ionchuimsitheacha le páistí 9-11 bliana d’aois