ITS2025 Workshop: BBGI'25 Program
Tuesday, June 03rd – 15:00 – 18:00 – Workshop on Breaking Barriers with Generative Intelligence
The workshop will be held ONLINE
ATTENTION: **Workshop is free **Participants are not required to pay any fee
Tuesday, June 03
15:00
The Impact of AI-Driven Digital Human Resource Management on Organizational Efficiency: A Data-Driven Analysis
Ayman Al Armoti, Reema Al-Qaruty, Samer Abdel Hadi and Badriya Mohammed Mohammed
ABSTRACT: Digital Human Resource Management (DHRM) represents the transformation of traditional HR practices into a more efficient, technology-driven framework by leveraging mobile devices, data analytics, digital media, and IT solutions. Essen-tially, DHRM integrates AI, software, and internet-based technologies to stream-line and enhance HR functions. As organizations strive for long-term relevance and competitiveness, digital transformation in HR has become imperative. Failure to adopt digital change may result in inefficiencies and a competitive disadvantage.
This study reviews existing literature and explores various dimensions of DHRM, with a particular focus on AI-driven advancements. Primary and secondary data were collected through questionnaires and analyzed using quantitative methods. The findings underscore the significance of digital HRM in optimizing organizational performance, facilitating seamless implementation, and driving better business outcomes. Additionally, this research provides a foundation for scholars seeking to understand the impact of digital HR technologies on organizational effectiveness and workforce management. All in all, despite minor discrepancies, there is a positive correlation seen between the variables and the impact of digital technologies. It can be said that ARTIFICIAL INTELLIGENCE has a positive impact on the HR functions. And its support research questions
15:30
Leveraging Generative AI for Sustainable Laboratory Waste Management in Medical Education
Sura Al-Hiyali, Ashgan Ahmed and Azza Mohamed
ABSTRACT: Sustainable laboratory practices are vital for reducing environmental and health risks in medical education. This cross-sectional, questionnaire-based study was conducted between October and November 2024 at the College, UAE, aiming to evaluate sustainability awareness, waste management practices, and the role of digital technologies among medical laboratory students and staff. A total of 43 participants—including second-, third-year, and fourth-year students, as well as laboratory technologists—were selected based on their academic level and active involvement in laboratory work. First-year students were excluded due to limited lab exposure. Data were collected via a structured electronic questionnaire composed of multiple-choice questions addressing demographics, curriculum exposure, hazardous waste handling, and resource conservation practices. Descriptive statistical analysis was performed using GraphPad software, with key findings illustrated through bar charts and tables. Results revealed that toxic chemical reagents, disposable items, and biohazardous waste are the most commonly used materials, often disposed of on a weekly basis. Students highlighted the need for safer chemical alternatives, stronger recycling protocols, and training in proper handling techniques. Water and energy conservation emerged as significant concerns, with practical suggestions such as reuse systems, smart timers, and sustainable equipment. A majority of students (83%) rated sustainability as important to extremely important, while 79% supported curriculum revisions to include sustainability-focused content. Furthermore, 41% recognized the potential of artificial intelligence (AI) in enhancing both laboratory learning and eco-friendly practices.
Virtual laboratories were particularly valued, with 38% citing improved accessibility, 35% highlighting interactivity, and 33% noting flexibility and digital skill development. Importantly, 59.5% believed virtual labs significantly reduce environmental impact, underscoring their role in advancing sustainable medical laboratory education. The study adhered to ethical research guidelines, ensuring voluntary participation, anonymity, and compliance with institutional data protection protocols.
16:00
Securing School Communication: The Role of AI and Machine Learning in Spam Email Detection
Suha Assayed and Azza Mohamed
ABSTRACT: Emails play a vital role in facilitating communication between schools, students, and parents, enabling the sharing of knowledge, submission of assignments, and enhancing overall communication. The integration of generative AI (genAI) allows schools to automate responses, personalize communication, and improve student engagement and operational efficiency. However, the growing reliance on email systems brings security challenges, such as spam, phishing, and malware threats. Machine learning (ML) addresses these issues by using advanced techniques to detect and mitigate spam emails, ensuring secure and efficient communication. Together, genAI and ML streamline school operations and protect sensitive information, creating a safer and more productive environment for students and educators. In this study multiple machine learning algorithms are deployed to see how well they could detect spam emails during training and testing phases. The dataset is uploaded from Kaggle platform. The dataset includes 3,016 emails, all emails are collected from marketing and promotions domain. The models were developed and executed in Python language. The findings show that the Support Vector Machine (SVM) outperformed other classifiers, achieving 99.3% accuracy, 100% precision, 94.8% recall, and a 97.3% F1-Score.
16:30
“Future-Ready Learning: Exploring the Role of Generative Intelligence and Metaverse Technology in Education”
Faiza Qasmi
ABSTRACT: Generative Intelligence (GI) and Metaverse technology are at the front of this shift, which has brought forth new paradigms in education due to the quick development of emergent technologies. Generative Intelligence has enormous promise for customized and adaptive learning since it allows computers to produce human-like material, from text and images to simulations and interactive modules, thanks to the strength of big language models and generative neural networks. At the same time, the Metaverse—a communal virtual shared space that combines mixed reality (MR), augmented reality (AR), and virtual reality (VR)—offers immersive settings that support international cooperation in education and experiential learning. This research aims to describe how these two technologies are changing teaching strategies, improving student engagement, and making high-quality education more accessible to all. The study identifies important implications by combining recent advancements, real-world applications, and expert insights. These include the development of AI-powered virtual classrooms, intelligent tutoring systems, real-time content creation in immersive environments, and improved inclusivity through remote learning platforms. But it also draws attention to important issues, including the digital divide, data privacy, the psychological implications of virtual immersion, and ethical issues. According to the study’s findings, although generative intelligence and metaverse technologies have drawbacks, they can completely transform contemporary education and make it more inclusive, dynamic, and future-ready when carefully included.
17:00
BacPrep: An Experimental Platform for Evaluating LLM-Based Bacalaureat Assessment
Adrian Marius Dumitran and Radu Dita
ABSTRACT: Accessing quality preparation and feedback for the Romanian Bacalaureat exam is challenging, particularly for students in remote or underserved areas. This paper introduces BacPrep, an experimental online platform exploring Large Language Model (LLM) potential for automated assessment, aiming to offer a free, accessible resource. Using official exam questions from the last 5 years, BacPrep employs one of Google’s newest models, Gemini 2.0 Flash (released Feb 2025), guided by official grading schemes, to provide experimental feedback. Currently operational, its primary research function is collecting student solutions and LLM outputs. This focused dataset is vital for planned expert validation to rigorously evaluate the feasibility and accuracy of this cutting-edge LLM in the specific Bacalaureat context before reliable deployment. We detail the design, data strategy, status, validation plan, and ethics.
17:30
Developing a Mentoring System Based on Behavior Logging and Personalized Cognitive Modeling
Nilupul Heshan Randika Kodikara and Junya Morita
ABSTRACT: This research investigates the relationship between web semantics, goal relevance, and user interest in digital learning environments. We present an intelligent mentoring system that leverages foundation models and behavioral logging to evaluate the relevance of web materials to assigned tasks. Using Contrastive Language-Image Pre-training (CLIP), the system assesses semantic alignment between learning objectives and accessed resources. Our experimental study involved eight postgraduate students completing web-based research assignments on topics of varying interest levels while their browsing behaviors and semantic patterns were recorded. Statistical analyses revealed that resource relevance to task objectives significantly influenced information retrieval patterns, while user interest did not show a significant effect. These findings suggest that semantic alignment with task goals drives effective information retrieval in digital learning contexts. This work establishes a foundation for developing adaptive learning systems that can detect individual learning behaviors and provide tailored interventions based on real-time assessment of resource relevance.