Dr David Williams, Dr Andrew Browne, and Kunwar Madan

Defining Academic Impoverishment and Understanding Academic Impropriety

Abstract

This paper grows out of our preliminary research into the root-cause analysis of academic impropriety in academic programmes. Our initial ideas were formed when we noticed that the last several years have provided particular challenges to third level institutions around the area of assessment. Incidents of academic impropriety have long been a concern for the sector, but the move to online exams has highlighted this further. The study then moved on to explore data collected on cases of academic impropriety over a several-year period at Dublin Business School. This data was explored using visualization techniques to expose any peculiar trends. Two of the main trends discovered were: 1) A lack of clear understanding around the idea of Academic Impoverishment and 2) High incidents of cases that were resolved as not academic impropriety. The researchers hypothesize that the results show a lack of clear definition and understanding around academic impoverishment and academic impropriety amongst staff and students. The researchers propose to move this study into its next phase which will be a qualitative analysis around these ideas. This paper highlights the quantitative results and proposes the next steps.

Dr Barnaby Taylor

Into the Abyss: Text Prompts, Tactics, and (Digital) Tools

Abstract

This paper explores the possibilities inherent in using generative artificial intelligence to synthesise theories and concepts in order to create a position paper, in this case, combining theories of relationism in football and the principles of Universal Design for Learning in order to explore new ways of developing engagement and participation in the contemporary classroom. This paper then examines the process and implications of using ChatGPT to develop a paper in this way as well as considering the impact that the process can have on the future of learning and teaching in higher education.

Vanessa Stafford

Reflection on Applying CoP Research to a Teaching CoP Challenge: Kaplan Mini Talks

Abstract

A community of practice (CoP) is an organic, self-organising space, where collective knowledge deepens, strengthening practice and forming member identities (Farsworth et al., 2016; McIntosh & Nutt, 2022; Wenger, 2000). However, the recognition and support of a CoP by external structures are strong factors to its success (McIntosh & Nutt, 2022). Consequently, at Kaplan Business School, the Director of Academic Learning and the Academic Learning Team, have developed a framework intended to enhance the collective knowledge sharing capabilities of its teaching CoP. This action stems from the acknowledgement that the Academic Learning Team’s professional development program is an influential external factor to the success of a teaching CoP. Kaplan Mini Talks is a scaffolded presentation template for educators who wish to share informal classroom reflections of practice with their peers in the context of working in a non-research-focused business school. This approach offers a unique solution to the challenge of promoting scholarly teaching within a proud teaching-only institution that does not have a research focus and therefore lacks the supports to facilitate traditional, primary, action research. Although this initiative is in its infancy, it has so far received a positive reception. The Director of Academic Learning will provide a reflection of practice on the process of launching this initiative and share future goals, via her own Kaplan Mini Talk. Keywords: Community of practice, professional development, higher education business school, presentations, teaching-focussed institutions.

Dr Thomas Macagno

Nurturing Sustainability Changemakers through Transformative Learning and Design

Abstract

Globally, society faces significant problems, from climate crisis to persistent poverty. Education for Sustainable Development offers an approach to achieving a sustainable society. The challenge is creating changemakers with the knowledge, mindset and transversal skills to innovate. Teaching sustainability tends to be discipline-specific, taught content-heavy via ‘spoon-feeding’ neglecting student agency changes. To overcome these challenges, we developed a programme to ‘teach’ innovation for sustainability that combines transformative learning and design thinking as the pedagogy. Classes were anchored by solving a real-world sustainability challenge, facilitating experience transformation into new knowledge. Design Thinking is a transdisciplinary methodology that helps different disciplines collaborate on addressing complex problems. However, there is limited empirical evidence to support the effectiveness of this transformative pedagogy in sustainability education. What is the value of combining Design Thinking and Transformative Learning as a pedagogy in sustainability education? Based on the University College Dublin (UCD) Innovation Academy Professional Diploma of Innovation for Sustainability, we address this research question by exploring the impacts of the programme design. Data was collected during and after the programme through students’ reflections, a post-programme survey, and observation field notes. Findings show that the programme design supported developing a sustainability mindset, sustainability literacy, transversal skills, and creative confidence. All characteristics support becoming a changemaker.

Dr Rita Day, Trevor Haugh, David Rinehart & Louise Cooke-Escapil

Student Involvement in the DBS Applied Research and Theory Journal

Abstract

One of the DBS strategic objectives is “to create graduates who have the skills, knowledge and attributes… such that they can successfully progress to employment or further education” (DBS, 2021).The DBS Applied Research and Theory Journal took a proactive approach to meeting this goal by involving students in the journal. This presentation will cover the triangulated approach used to involve students in order to develop skills which transfer beyond an academic environment (Huang and Chang, 2004) This included accommodating work experience and having students manage various journal events. The journal team used the characteristics of active learning theory to manage these initiatives. These include getting students to: Actively participate Use own their initiative Work with others Discover own way of completing tasks (Lorenzen 2001, Ni Uigin 2014) This project produced three preliminary findings; firstly we found the journal team should consider the creation of learner objectives for similar projects (Surg 2022, Weiner & Watkinson 2014). We also found these schemes allowed us to develop an authentic learning experience with students (Kahn & O’Rourke, in Barrett et al, 2005). Finally, we found that other areas of the organisation have introduced similar schemes and more collaboration across areas would be beneficial.

Ananya Sahu

Adoption of DevOps in the Software Development Team Challenges and Recommendations

Abstract

The software industry is advancing. Faster time to market is a competitive advantage, but it is challenging to balance quality and speed. It is critical to comprehend and use the concepts and practices that can assist firms in reducing their time to market. Traditional waterfall models take longer to deliver a product than new approaches like Agile, Lean, and Extreme Programming. While Agile shortens the development cycle, synchronizing the objectives of the development and operations teams is challenging. DevOps as an Agile extension aims to close this gap by encouraging shared accountability. The development team faces more issues than any other level in an organization, as the team focuses on developing new features and carrying out DevOps activities. This thesis surveyed 21 IT specialists and yielded 3 significant challenges that the teams are facing. The absence of support from management and administration. DevOps requires learning an extensive toolkit. Accepting the new working style is challenging. DevOps brings an additional burden on the teams. A lot of tasks are repetitive and time-consuming. Automation smoke testing can be a good solution to improve accuracy and help reduce efforts. Recommendations are provided to assist in resolving the issues. Support for DevOps should come from all organizational levels. Sufficient training and adaptability are necessary to grasp DevOps ideas. Knowledge sharing within development teams. The survey approach targeted a pertinent cross-sectional population and collected and evaluated data comprehensively. An empirical method that uses inductive reasoning seeks to evaluate the issues. The questionnaire focuses on the DevOps problems, team dynamics, and participant backgrounds. Purposive recruitment of participants is carried out by judgment sampling and convenience sampling methods. For a thorough grasp of research findings, the study analysis combines quantitative (descriptive statistics) and qualitative (thematic analysis) approaches.

Jayshri Gupta

Navigating the Facts: Unveiling Veracity with Integrated Knowledge Graphs and Graph Neural Networks

Abstract

In the digital era, where information proliferates at an unprecedented rate, distinguishing between truth and rumours has never been more crucial. The surge of misinformation poses a formidable challenge to societal trust and informed decision-making. This research introduces an innovative approach to automated fact-checking, leveraging the synergistic potential of integrated datasets, knowledge graphs, and graph neural networks (GNNs) to pioneer a new frontier in the battle against misinformation. By harnessing the LIAR, FEVER, and Fake News Challenge (FNC-1) datasets, this study constructs a comprehensive knowledge graph that encapsulates a wide array of information, enriched with real-world context and inter-entity relationships. The methodology extends beyond traditional fact-checking algorithms by incorporating GNNs, which analyses the graph-structured data to infer the credibility of information. The model's architecture is designed to dynamically assimilate new data, refine its understanding of factual relationships, and adapt to the evolving landscape of information. This allows for a nuanced analysis of claims, considering not just the content of a statement but its contextual veracity within the vast web of global knowledge. Preliminary results demonstrate a significant enhancement in the accuracy and efficiency of fact-checking processes, outperforming existing models in both precision and recall. This research not only offers a novel solution to the pressing issue of misinformation but also contributes to the broader discourse on the application of artificial intelligence in media integrity. Furthermore, this work lays the groundwork for future exploration into the integration of diverse data sources and advanced computational techniques, opening new avenues for the development of more resilient and intelligent fact-checking systems.

Jayshri Gupta

Unveiling Frontiers in Applied Research:

Innovations and Challenges in Sign Language Synthesis and Fact-Verification Knowledge Graphs

Abstract

Applied research has been a cornerstone of my professional journey, offering a pathway to translate theoretical knowledge into solutions that cater to pressing societal needs. Through my reflections on varied projects, the essence and challenges of applied research come to the forefront, revealing both its rigor and its potential for profound impact. Firstly, my work on an Indian Sign Language generator epitomizes the hurdles and rewards inherent in applied research. Confronted with the daunting task of processing over 50,000 videos, the project required innovative methodologies to extract nuanced gestures—a critical step towards creating a robust communication tool for the deaf community. This experience highlighted the significance of perseverance and creative problem-solving in overcoming dataset limitations and technological constraints. Currently, my ongoing research on developing a knowledge graph for fact-checking showcases the complexities of integrating multiple datasets with varying information labels. The amount of data is huge. The pursuit to harmonize these discrepancies has paved the way towards a potential novel approach. Since, it is an ongoing project, there are going to be hurdles on the way. These endeavours illuminate the vital role of applied research methods as a subject of study. Through this lens, I have honed my ability to navigate the intricate imbalance between theory and practice. The study of applied research methods has not only equipped me with the tools to address specific challenges but has also ingrained a mindset geared towards innovation, collaboration, and resilience. This abstract aims to engage the audience into the world of applied research, where challenges fuel the journey towards groundbreaking discoveries and societal advancement.

Dr Shahram Azizi Sazi

Artificial Intelligence for Human well-being; Applications in Physiotherapy

Abstract

We aim to design, develop and deploy AI-enabled technology in physiotherapy domain for Cerebral palsy (CP) kids. CP is a typical disorder in most premature new born which has significant impact on the person’s mobility and movement. CP is caused by damage in brain cells which control the person mobility and balance. There is no particular treatment for CP, however medical experts have suggested physiotherapy, Occupational therapy and hydrotherapy to retrieve the functionally of some of damaged cells and compensate the neural communication using the heathy cells. Undoubtedly, this research is significantly diverse in terms of theory and applications. This research has been segmented into four phases: Phase I: Understanding of Business problem (Feb 2017-December 2021): an extensive research and exploration, interviews, feedback from Neurodisability and practices consultants, Physiotherapists, and Occupational therapists have been accomplished. Phase II: Understanding of Hardware devices & physio concepts and techniques (January 2018-Now) We have been striving to audit the list of available physio/OT devices and carried out the research feasibility from Tech perspective. Phase III: Robotic design and device automation (Feb 2019-now) The original material and initial tools are available; however, mechanical mobility and Motability are on-going research and yet to be completed. For this research we are using more than 20 sensors to measure different features of CP body. Phase IV: AI-Enabled programming and integration (Feb 2021-now) From AI perspective, sensors and data generators are fully designed. Modelling pipelines, structures, and integration is also available to some extend, however, this phase is in the early stage in real-world context and from user experience point of view.

Asil K. H. Naser

Predictive Analytics for Optimizing Fundraising Strategies: A Data-Driven Approach

Abstract

This research paper explores the application of predictive analytics in optimizing fundraising strategies for non-profit organizations. In an era where data plays a pivotal role in decision-making processes, leveraging advanced analytics techniques can significantly enhance the effectiveness of fundraising campaigns. By analyzing historical donor behavior, demographic trends, and various external factors, organizations can develop predictive models to anticipate donor preferences, optimize resource allocation, and maximize fundraising outcomes. This paper will delve into the methodologies, challenges, and potential benefits of implementing data analytics in fundraising efforts, providing insights for non-profits seeking to enhance their fundraising capabilities. Despite the increasing availability of data and the potential benefits of leveraging analytics in fundraising, many non-profit organizations continue to rely on traditional methods, resulting in suboptimal outcomes. There is a gap between the theoretical potential of data analytics in fundraising and its practical implementation within the non-profit sector. This lack of adoption can be attributed to various challenges, including limited resources, lack of expertise, and concerns regarding data privacy and ethics. 

Terri Hoare

Graph Learning Approaches to Extract Actionable Insights from Electronic Health Records Challenges in Data Preparation and Opportunities using Generative AI

Abstract

This research explores the application of machine learning techniques to knowledge graph representations of Electronic Health Records (EHRs). The problem is to extract actionable insights from EHRs to support decision making by medical staff. Healthcare providers look to better understand what influences patient journeys so they can improve individual outcomes as well as identify optimal treatment paths. Treatments are rarely a single event, especially for serious illnesses. The aim is to understand pathways of patient journeys through intensive care treatment by modelling and storing the patient journeys as a knowledge graph of symptoms, tests, treatment plans, and outcomes, together with secondary and following treatment plans and outcomes. Machine learning is applied to the graphs. Knowledge graphs are a type of knowledge representation that can effectively organize and represent enormously large volumes of connected data so that the representation can efficiently be used by advanced applications. A critical element in machine learning on EHR knowledge graphs is to convert the patient journey to a machine learning friendly representation. The topology of the graph must be represented as a vector in a vector space suitable for machine learning. Challenges in data preparation and research opportunities using generative AI are explored. 

Sachin Moze

Real-time Heart Rate Analytics in Health Care Domain using AI

Abstract

In this research, we proposed an AI-based application to represent a solution for personalized health monitoring, leveraging wearable technology to provide real-time insights into individuals' heart rates. By seamlessly integrating with Google Fit, the application facilitates the immediate transfer of heart rate data to the cloud, ensuring accessibility and reliability. Through continuous monitoring of heart rate data, the system is equipped to detect abnormalities with precision and efficiency. Whether it's fluctuations in heart rate patterns or potential indicators of impending health issues, the application's algorithm swiftly identifies these signals. In response, emergency alerts along with their location are promptly send to family members via email and text messages, enabling timely intervention and support. In addition to its alerting functionality, the application offers features designed to enhance user experience and promote proactive health management. Users can effortlessly add multiple family members' details. Real-time tracking of heart rate progress provides valuable insights into individual health track, while historical data analysis offers a holistic view of long-term health trends. Furthermore, the application serves as a valuable resource for guiding users towards appropriate medical interventions when abnormalities are detected. By offering recommendations for medical consultation, the application empowers individuals to take proactive steps towards optimizing their health and well-being. To access these transformative features, users are required to create an account and authenticate it with their Google account read specific data permission's only, ensuring a secure and seamless user experience. This streamlined authentication process underscores the application's commitment to user privacy and data security, fostering trust and confidence among its users.

Dr Kelly Hunnings

Fostering Inclusivity in the Irish Literature Syllabus: A Thematic Approach

Abstract

This paper explores the necessity of diversifying the Irish literature syllabus in introductory Irish literature modules. While Irish literature is multifaceted, traditional syllabi often overlook the contributions of marginalized voices, including women, people of colour, LGBTQ+ community, and those from lower socio-economic backgrounds. By expanding the canon to include a broader range of authors and perspectives, we can offer students a more inclusive and representative understanding of Irish identity and culture. Indeed, in doing so, we can prepare students with the tools to interrogate notions of nationality, belonging, and cultural heritage in a global context. This paper offers practical strategies for educators, including a thematic approach and resource recommendations. By embracing diversity in Irish literature education, educators can cultivate a more equitable and enriching learning experience for all students, ultimately contributing to a more inclusive society.

James Fair

A Comparative Analysis of the Different Ways of Making Feature Films as Part of Higher Education Curricula

Abstract

Making feature films as part of higher education curricula is nothing new. Established filmmakers like Robert Altman and Brian De Palma made productions with student crews over forty years ago (Secret Honor in 1984 and Home Movies in 1979 respectively.) In recent years, UK and Irish institutions like Falmouth, Staffordshire, Bournemouth, UCLan and Filmbase in Dublin have all made features as part of courses. They primarily operate as a way of giving students a ‘real world’ experience on a large project rather than a short film. Existing academic literature addresses the extent to which each project is connected to industry (Mateer, 2018, Marshall, 2024 and Knowles, 2024) However, there is a lack of academic literature comparing the various ways in which these higher education institutions have structured the crews upon these productions. They vary in terms of level (undergraduate/postgraduate), student and staff responsibilities in the collaboration, and the ways that students are assessed. This presentation will provide a comparative analysis of these different approaches to understand the different ways in which the practice-based learning is structured. In a climate in which the UK and Irish film industries are predominantly service industries with a skills shortage in specialist areas, is it time to revisit these models, ask if they are meaningful and if yes, ask why they are not more prevalent?

Dr Barnaby Taylor

After Marker: Bow Lane Time Travel and the Apocalypse

Rory Glynn

The Death Of Sincerity In Blockbusters

Rebecca Sartor

Helping Hearts

Abstract

The short documentary ‘Helping Hearts’ offers a captivating glimpse into the vital work of the Austrian Crisis Intervention Team through the lens of a dedicated volunteer. Against the stunning backdrop of Austria's tranquil lakeside landscapes, delve into the team's essential role in supporting individuals coping with the aftermath of tragic deaths. Through poignant interviews and breathtaking visuals, gain insight into the team's methods, their unwavering dedication, and the profound impact of their assistance. Join us on this introspective journey as we explore not only the team's invaluable contributions but also the personal journey of one individual as he navigates the challenges of this compassionate calling.

Conor McCloskey

The Continuity Project: Relational Coherence and Building Motivation Through Language

Abstract

When exploring human language through a behavioural perspective, Relational Coherence refers to how well new information aligns with our prior beliefs. For example, a statement such as “dogs are friendly” would display high Coherence for a Labrador owner, but low Coherence for somebody with a fear of dogs. Coherence is essential for understanding how language and thought interact, and for understanding how people follow instructions. Most prior research on Coherence has focused on material that is spoken aloud to participants, with a limited number of studies exploring the impact of Coherence in written material. In this research project, Coherence will be explored as an influencing factor of behaviour, as well as a predictor of trust. Across two experiments, this ongoing research project is exploring the effect of Coherence on instruction-following tendencies as well as the impact of perceived Coherence on trust, specifically using news stories and perception towards the reliability of the outlets providing them. This research will further our functional understanding of human language with reference to a key aspect of human language, as well as helping to understand how Relational Coherence can be used to facilitate stronger outcomes across domains such as academia, media, and public health.

Cara Lefroy

Which Factors Impact Stress and Wellbeing in Neurodivergent Parents?

Abstract

Background: Despite its importance, few studies have explored parental stress and wellbeing among Autistic parents, parents with ADHD, and AuDHD (both Autistic and ADHD) parents. Addressing this gap, the present study examines stress, wellbeing, psychological flexibility, and social support among these neurodivergent parent groups. Key hypotheses are as follows: (i) parental stress will be predicted by psychological flexibility and social support, (ii) wellbeing will be predicted by psychological flexibility, social support and stress (iii) there will be no differences in these variables between the three neurodivergent parent groups.

Methods: The study employs an online cross-sectional survey design. Ethically approved by the DBS Ethics Committee, 345 neurodivergent parents completed standardized self-report measures of parental stress (Berry & Jones, 1995), wellbeing (Vanderweele, 2017), psychological flexibility (Golijani-Moghaddam et al., 2023), and social support (Zimet et al., 1988). Parents were asked to disclose whether they had an Autistic and/or ADHD neurotype.

Results: Among Autistic parents and parents with ADHD, multiple linear regressions revealed that parental stress was predicted by psychological flexibility and social support. Similarly, for these parents, wellbeing was predicted by stress, psychological flexibility, and social support. ANOVAs revealed that surveyed neurodivergent parents did not differ in terms of stress, wellbeing and social support across the three groups. Autistic parents reported higher psychological flexibility than parents with ADHD.

Discussion: These findings can be used to inform supports for these parent groups. Psychological flexibility and social support may be important modifiable targets which can facilitate improved stress levels and wellbeing in neurodivergent parents. The absence of differences in stress, support and wellbeing levels between the three neurodivergent parent groups highlight the similarities between these groups. This aligns with recent conceptualisations of Autism and ADHD, being less distinct than previously assumed, further supported by high rates of co-occurring ADHD and Autism reported in this study.

Dr Alison Stapleton & Conor McCloksey

The Limit Does Not Exist: Targeting Self-Limiting Beliefs with Acceptance and Commitment Therapy

Abstract

Among third-level students, becoming caught in self-limiting beliefs contributes to academic procrastination (Wang et al., 2017) and study-related burnout (Nina Katajavuori et al., 2023), in addition to diminished wellbeing and school engagement (Grégoire et al., 2018). One approach evidenced to reduce entanglement with self-limiting beliefs is acceptance and commitment therapy (ACT; Hayes et al., 2006). Through brief, easy-to-implement psychotherapeutic “defusion” exercises, ACT empowers people to take a metaphorical “step back” from their self-limiting beliefs, recognizing that thoughts are just thoughts and that we always have a choice about how we respond. To date, no studies have plotted participants’ degrees of attachment to their self-limiting beliefs before and after a defusion exercise. This is a substantial gap in the ACT literature (Assaz et al., 2022) that can be addressed by recent, cutting-edge techniques, specifically the relational density multidimensional scaling procedure (Belisle & Dixon, 2020). This project aims to empirically test students’ degrees of attachment to their self-limiting beliefs during a defusion exercise, further examining academic procrastination, burnout, and wellbeing pre- and postintervention. Findings will have implications for streamlining ACT interventions and conceptualizations of self-limiting beliefs, in addition to student engagement and wellbeing more broadly.

Bhuvan Israni

Examine the Efficacy of Spiritual Guidance and Healing in Ireland by adding Sermons by Chaplains in Dialectical Behaviour Therapy (DBT) for students with Suicidal Ideation, Self-Harm & Depression

Abstract

Research studies have clearly established that religion plays an important role in a majority of people’s lives (Lawrence et al., 2016). However, it is still very unclear if there is a relationship between suicide risk and religion. There are several research studies which have revealed that increased religiosity protects against suicide (Norko et al., 2017). However, there are few studies which suggest otherwise. A study suggested that suicide ideation was more severe among depressed patients who said religion is more important and among those who attend services more frequently (Lawrence, Oquendo & Stanley, 2015). The current study attempts to examine if following spiritual guidance can help reduce suicidal ideation, self-harm and depression among students in Ireland. Chaplains play an important role in spiritual guidance. This mixed method study compares outcomes for students at schools and universities in 14-week Dialectical Behaviour Therapy (DBT) followed by spiritual guidance and healing by a chaplain compared with those who would undergo only DBT. DBT is taught as a series of skills such as Mindfulness, Interpersonal Effectiveness, Emotional Regulation & Distress Tolerance. The aim of the study is to establish if DBT integrated with spiritual healing via a sermon by a chaplain helps reduce suicidal ideation, self-harm and depression among students. The objective is to offer compassionate spiritual care and emotional support, which can serve as resources for healing for those students who have suicidal ideation, self-harm and depression. A variety of statistical techniques and semi-structured interviews will be conducted with the participants to analyse the data. Further research in this area with a larger sample size will help in reiterating the findings of this research. Keywords- Dialectical Behaviour Therapy, Sermon, Chaplain, Suicidal Ideation, Self-Harm, Depression.

Shauna McNamara

Testing the Relationships between Teachers’ Knowledge of Autism, Experience of Systemic Stressors, and Attitudes towards the Inclusion of Autistic Learners

Abstract

This study explored the relationships between attitudes toward inclusion, knowledge of Autism, and stress (general, administrative [systemic], and competency-demand mismatch [systemic]) among teachers currently working with Autistic students in mainstream or Special Classes across primary, secondary, and Special schools. Key hypotheses were as follows: (i) lower stress will be predicted by a higher knowledge of Autism and more favourable attitude toward inclusion and (ii) there will be significant differences in stress between teachers who have a qualification in special education and teachers who do not. Ethically approved by the Dublin Business School Human Research Ethics Committee, this study employed an online cross-sectional survey design and the following measures: Perceived Stress Scale (Cohen et al., 1983), Adapted Autism Awareness Scale (Tipton & Blacher, 2014), Impact of Inclusion Questionnaire (Hasting & Oakford, 2003), and Teacher Stress and Coping (Forlin, 2001). 125 teachers practising an average of 17.4 years working in primary (n = 68), secondary (n = 50), and Special schools (n = 7) participated. At present, data analysis is underway with descriptive and inferential statistics (multiple regression model and independent sample t-test) being calculated. Preliminary results revealed that higher knowledge of autism and positive attitude to inclusion significantly predicted lower stress (administrative). Stress (competency-demand mismatch) differed significantly between teachers with a qualification in special education and those without. Qualitative comments from teachers highlight the need for additional supports and training in order to facilitate effective inclusion. Results are discussed with reference to neurodiversity-affirming approaches to supporting neurodivergent learners and pathways to better equipping teachers with necessary skills and tools. Overall, the present findings highlight existing gaps in Irish teacher training systems and inform the ongoing development of neurodiversity-affirming training systems.

André Büsgen & Nils Freyer

Assist.me!

Abstract

Small and medium enterprises (SMEs) often have unused process data that is unstructured or semi-structured, making it difficult to use for process optimization. The Assist.me! research project aims to help SMEs make use of their available data efficiently. To achieve this goal, we developed four objectives:

1. Anomaly-Detection: Not all unstructured data is suitable for process-mining and optimization. Our partners conduct many different measurements which are included in handwritten reports. Measurement errors are often overlooked, leading to more manual work. Anomaly-detection can identify anomalies in the measurement. We developed an autoencoder-based anomaly-detection architecture to detect anomalies in measurements which can be trained continuously without further efforts.

2. Information Retrieval: The amount and complexity of textual data constitutes a burden to its use. We explored the use of Large Language Models (LLMs) and cross-encoder models to effectively access knowledge bases and extract relevant information in a dialogue system. We adapted the Retrieval Augmented Generation (RAG) process to generate better search queries and trained models for better data selection, as default embedding and reranking models within the standard RAG process did not yield good results for our partners’ niche domains.

3. Process Model Extraction: Extracting formalized process models from text is time-consuming and requires trained staff. We developed GUIDO, a hybrid approach using a BERT-based sentence classifier to filter relevant sentences and dependency parsing to extract activities and orders. This allows SMEs to automate the process model extraction task with comparatively low annotation costs.

4. Process Mining & Compliance Checking: We used cross-encoders to map activities to equivalence classes and developed PALM to empirically evaluate the use of paraphrasing as a form of data augmentation for text classification. Our findings enable SMEs to apply process mining and process compliance checking to the textual data without requiring large amounts of annotated data.

Dr Vincent Hunt

Podcasting for Reading

Abstract 

My experience in the publishing industry, as a student, and as a lecturer suggests that students use rather than read material. Using material leads to the student becoming over reliant on technology. Reading material develops critical thinking skills, enhances research, and writing skills. To study reading as a student activity and to increase engagement with the written word, I propose to develop a series of podcasts around the paradigm of Read, Learn, Lead. Informal research, discussions with students has thus far informed my research and I now propose to formalise research in this area.

Nkosiphendule Ngcoza

Between Popularity and Tyranny: Wildlife Tourism and Workers’ Livelihoods in rural South Africa

Abstract

The popularity of wildlife tourism in South Africa has surged in recent years. Hence, this warrants a systematic investigation into the contribution of wildlife farming in the context of South Africa’s slow land reform and rising unemployment, poverty, and inequality. It is against this backdrop that this paper seeks to assess whether wildlife tourism, touted as a sustainable development approach, genuinely enhances the well-being of local communities, or exacerbates existing social and economic issues. Furthermore, it intends to analyse the shift from agricultural to game farming and its implications for land insecurity. Methodology This empirical research employed semi-structured interviews, heeding the guidance of McIntosh and Morse (2015). Interviews, conducted in English and IsiXhosa, honoured participants’ voices, with separate sessions for males (ootata) and females (oomama) to ensure anonymity and openness. Document analysis, complementing interviews, provided context for evaluation of documents and operational reports of the private game farm employing the farm workers. Thematic analysis distilled data into coherent narratives, with colours representing emergent sub-themes. This rigorous approach unveiled the complexities of rural livelihoods within the private game reserve, demonstrating the transformative power of qualitative research. Findings and Implications The paper argues that despite the promotion of wildlife tourism as a capable alternative to many forms of agrarian production and a catalyst for rural development, there seems to be limited empirical evidence to back up these claims, especially in the Eastern Cape where many livestock farms have been converted into game farms in recent years. We argue that while wildlife tourism may contribute to economic growth and employment creation, it fails to address the long-standing structural issues, including rural inequality. This research serves the purpose to inform existing rural development government policy. 

Ana Clara da Silva

Assessing the Impact of the Recruitment Process on the Attraction of Potential Candidates

Abstract

This research paper explores the dynamics of recruitment processes and their impact on candidate perceptions and behaviours, with a focus on Millennials in the Irish labour market. The study addresses two primary objectives: first, to understand candidates' opinions on recruitment processes, and second, to investigate the correlation between recruitment length and candidate dropouts among. The research methodology adopts a structured approach integrating literature review with descriptive survey analysis. The research tool selected was an online survey distributed through social media platforms. Qualitative and quantitative research approaches are implemented with open-ended questions and statistical analysis of the survey responses. The candidate profile primarily focuses on Millennials, those born between 1977 and 1997. Projections indicate they will occupy 75% of the global workforce by 2025. Finally, the data preparation involved the review and adjustment of the survey responses to facilitate analysis. The findings highlight the critical role recruitment processes play in shaping candidates' perceptions of organisations. While candidates express a preference for assessments comprising multiple stages, the research uncovers a challenge posed by prolonged recruitment processes. Nearly half of the respondents report abandoning recruitment processes due to their extended duration. However, while lengthy processes contribute to candidate dropout, no clear trend emerges regarding the number of stages and dropout rates. Other factors such as effort required at each stage and timely feedback emerge as significant influencers of candidate decisions to abandon the job application. Moving forward, organisations must prioritise candidate experience and retention by streamlining recruitment processes and fostering meaningful engagement. By aligning recruitment practices with candidate preferences, organisations can enhance their employer brand, attract top talent, and cultivate a positive workplace culture. This research underscores the importance of adapting recruitment strategies to meet the evolving needs of candidates in the modern labour market. 

Eleeshiya Roshell Warnakulasuriya

Impact of Integrating AI as a Project Management Skill in Project Management Education

Abstract

This research proposal investigates the impact of integrating Artificial Intelligence (AI) as a project management skill within project management education, aiming to prepare students for the evolving demands of the industry. The study encompasses various objectives, including evaluating the current status of AI integration in project management skills, analyzing the role of AI in project management, assessing the educational gap in project management curriculum to meet industry demands, and proposing strategies for integrating AI into project management education. Drawing on existing literature, the proposal underscores the increasing adoption of AI technologies across industries and emphasizes the significance of understanding AI's role in project management. The research aims to bridge existing gaps in literature by exploring the impact of AI integration on project management practices and workforce preparedness. Primary data collection involving interviews with three project management master's students and three experienced project managers will provide insights into the perspectives of both academia and industry professionals. The research methodology adopts a primary qualitative approach, utilizing face-to-face interviews with structured questions to gather authentic insights. Ultimately, this research seeks to contribute to the understanding of AI's impact on project management education and practice, offering valuable insights for educators, practitioners, and policymakers striving to equip the workforce with essential skills for the digital age.

Slate2 and RIPE23: Introduction and Overview 

Dr Barnaby Taylor and Dr Andrew Browne

DBS Research Grants 2024

Lori Johnston

DBS Applied Research and Theory Journal 

Dr Rita Day and Louise Cooke-Escapil