On November 16th, an event was held in the city of Spytków that brought together students and high school pupils, featuring game tournaments. During the event, our students presented their projects using artificial intelligence (AI). The materials from the FAAI project became indispensable and were showcased to a large group of over 60 participants.
On November 15th, an event was held that brought together students and high school pupils, focusing on computer games and lectures on game development. During the event, methods of creating games using artificial intelligence (AI) were presented. The materials from the FAAI project became indispensable and were showcased to a large group of over 100 participants.
We are delighted to inform you that our students are using FAAI work both in their Master’s theses and future progress. On the 2nd of July, the students defended their theses during the bachelor exam. The work was inspired by the FAAI project. The results of the students’ projects considered using applied AI in game development. Thanks to the project, the theses were defended successfully with the highest grade possible.
Now, we are proud to inform you that, based on their research, the scientific papers were accepted for the Engineer of the XXI Century Conference, which will take place in Bielsko-Biała, Poland.
There is a need to develop effective curricula based on real-life cases that can be used to broaden students’ participation and motivate them during their studies. Real-life case examples are crucial to justify the learning of the respective discipline. In our study, we explore the application of image processing using Python in the context of processing ancient manuscripts, particularly palimpsests. Palimpsests are invaluable historical manuscripts, often rewritten and reused over time. They pose challenges for researchers due to legibility and interpretation issues. Python and AI can help decipher them. This interdisciplinary study not only introduces students to applied AI techniques, but also enriches their practice with the use of various image preprocessing techniques to enhance the readability of palimpsests. Specific methods such as Gamma correction, Contrast Limited Adaptive Histogram Equalization (CLAHE) and Gaussian smoothing are detailed to demonstrate various preprocessing strategies. Current educational trends in Applied Artificial Intelligence (AAI) are discussed in this paper. Experimental techniques are elucidated through example code implementations showing the practical application of these technologies. The research contributes to the advancement of both educational and scientific applications by introducing learners to the history of their country through the analysis of ancient manuscripts. By engaging with these materials, students gain practical skills in AI while deepening their historical knowledge, fostering a holistic and interdisciplinary approach to learning.
The palimpsests represent unique historical sources that hold the potential for new insights in the field of human history. These manuscripts, rewritten and reused over time, pose challenges in the research related to their readability and interpretation. The present study aims to investigate the readability of palimpsests through the use of image preprocessing techniques. The article focuses on methods for the preprocessing of palimpsests that could lead to a significant improvement in the readability of the ‘hidden’ text. The challenges encountered during the processing of palimpsests are explored and various techniques applicable to improving the readability of these manuscripts are analyzed.
The primary goal of preprocessing in this context is to separate the ‘hidden’ text from the visible one, neutralizing material defects and aging. The article presents specific methods such as extracting specific color range from an palimsest image. The experimental techniques are highlighted with sample codes illustrating the application of the respective technology. The current research attempts to advance the development of methods for processing palimpsests and opens up new perspectives for extracting information from those historically valuable manuscripts.
Dates: July 11-12, 2024
Location: Nessebar, Bulgaria
The transnational meeting A5.2, a crucial event under Work Package 5 (WP5) of the FAAI project, was held on July 11-12, 2024, in the historic coastal town of Nessebar, Bulgaria. This meeting marked the final managerial gathering of the project, bringing together key representatives from five partner institutions to discuss the dissemination and exploitation of the training materials and thesaurus in artificial intelligence (AI) and machine learning (ML). The target audiences for these materials include students, teachers, mentors, and managers, emphasizing the project’s commitment to enhancing educational practices and professional development in AI.
Day 1: July 11, 2024
The meeting commenced at 9:30 AM with a welcome and introduction delivered by representatives from ULSIT. The opening remarks set the tone for collaboration and reflection on the project’s achievements, emphasizing the significance of this final meeting in consolidating the efforts of all partners.
Following the introduction, participants engaged in discussions regarding the local dissemination results as outlined in document A4.7. Each coordinator presented reports detailing their institution’s outreach strategies, engagement activities, and the impact of these initiatives on raising awareness of AI and ML training resources. This collaborative review provided valuable insights into best practices and lessons learned, fostering a sense of collective responsibility for the project’s success.
After a brief coffee break, participants reconvened for a session focused on task performance reports, where they reviewed the key performance indicators across various work packages:
Following a lunch break, the meeting resumed with an examination of the final local dissemination results (A5.7). Coordinators shared their reflections on the effectiveness of their dissemination strategies, discussing both quantitative and qualitative outcomes. This session aimed to synthesize findings to inform future dissemination efforts and enhance the visibility of the project’s outputs.
The afternoon included a financial management report presented by all coordinators, focusing on budget allocations, expenditures, and financial sustainability strategies. This discussion was pivotal for ensuring that all partners had a clear understanding of the financial health of the project and the implications for future activities.
The day concluded with an engaging session dedicated to discussing and shaping the final evaluations of project results. Participants collaboratively identified strengths, areas for improvement, and recommendations for future projects, ensuring a comprehensive assessment of the project’s impact.
An informal dinner was held in the evening, providing participants with an opportunity to network, share experiences, and reflect on the collaborative journey undertaken throughout the project.
Day 2: July 12, 2024
The second day began at 10:00 AM with a critical session focused on signing agreements for the sustainability of project outputs post-completion. This agreement signified a collective commitment from all partners to continue promoting and utilizing the training materials developed during the FAAI project. It emphasized the importance of ensuring that the resources remain available and beneficial to the targeted audiences long after the project’s conclusion.
Following this, the group engaged in a discussion and summary of the meeting, where coordinators shared their reflections on the meeting’s outcomes. This final session was instrumental in preparing a comprehensive “TO DO” list, outlining actionable steps to ensure that all remaining tasks were addressed before the project officially concludes.
The A5.2 meeting served as a vital culmination of the FAAI project’s efforts, providing a platform for partners to reflect on accomplishments, share valuable insights, and solidify plans for the future. The collaborative atmosphere fostered open dialogue and strengthened relationships among institutions, highlighting the shared commitment to advancing AI and ML education.
The signing of sustainability agreements marked a significant milestone, ensuring that the training materials and resources developed during the project will continue to serve as valuable tools for educators and professionals. This commitment to sustainability underscores the project’s long-term impact on enhancing educational practices and fostering innovation in the field of AI across Europe.
As the FAAI project moves toward completion, the collaborative spirit and shared goals of the partner institutions will undoubtedly continue to influence the landscape of AI education, ensuring that the benefits of this initiative are felt by students, teachers, and industry professionals alike.
Dates: May 15-19, 2024
Location: University of Ss. Cyril and Methodius in Trnava, Slovakia
The A5.4 Teacher Training event, held from May 15-19, 2024, in Trnava, Slovakia, brought together educators from five partner institutions to develop comprehensive teaching materials and guidelines for Artificial Intelligence (AI) and Machine Learning (ML) education. Organized by the University of Ss. Cyril and Methodius in Trnava, this training focused on equipping teachers with practical knowledge, resources, and frameworks to support and enhance AI education within various academic environments.
Across five days, participants worked collaboratively to establish practical resources, including guidelines and educational materials for AI instruction. This training not only focused on content development but also provided a forum for discussing and refining methodologies, curriculum design, and teaching strategies for AI-related courses.
The training commenced with a welcome address by UCMT, which introduced participants to each other and set the tone for the week’s collaborative work. ULSIT led the first session on Good Practice in Developing Guidelines, sharing methods for structuring effective teaching resources. This session offered practical insights into creating comprehensive yet adaptable teaching materials, critical for AI education across diverse institutional settings.
UBB led a focused session on the development of the AAI Teacher Guide, which provides educators with foundational AI concepts, teaching strategies, and adaptable resources for classroom use. Following this, teachers collaborated in team sessions to expand and refine the guide with input from UCMT, ensuring that it would be accessible and relevant across different educational contexts.
ULSIT took the lead on Day 3 to develop the AAI Student Guide. This guide aims to provide students with clear, foundational information on AI principles and practical skills, tailored to varying levels of AI knowledge. The guide also includes interactive activities and project-based learning recommendations, supporting a hands-on approach to AI education.
Day 4 shifted focus toward practical applications of AI in business, with UNI presenting the initial framework for the AAI Business Guide. This resource is designed to bridge the gap between academic AI education and industry applications, preparing students with the knowledge and skills they’ll need to understand and apply AI solutions in professional settings. UoM and UNI facilitated collaborative team sessions, encouraging participants to integrate business-relevant AI scenarios and case studies.
On the final day, all participants received certificates of completion as recognition for their involvement in developing these essential AI resources. This was followed by a round-table discussion on enhancing the AAI framework, including potential revisions to methodology, curriculum, and content to align with emerging trends and requirements in AI and ML. Institutional coordinators concluded with a summary of training outcomes and an outline of future project steps to ensure continued progress and support.
The A5.4 Teacher Training in Trnava served as a productive and impactful event, allowing educators to collaboratively build and refine resources that will enhance AI and ML education for students, teachers, and industry professionals alike. By developing these guides, the training has contributed to a stronger foundation for AI learning across participating institutions, ensuring that both educators and students are well-prepared for the demands of the AI field. As the FAAI project progresses, these resources will play a crucial role in supporting an informed, skilled generation of AI practitioners.
Dates: May 15-19, 2024
Location: University of Ss. Cyril and Methodius in Trnava, Slovakia
The A5.5 student training, held from May 15-19, 2024, in Trnava, Slovakia, brought together students from five partner institutions for an immersive experience in the practical applications of artificial intelligence (AI) and machine learning (ML). Organized by the University of Ss. Cyril and Methodius in Trnava, the training aimed to equip students with hands-on skills in AI across multiple domains, from industry and healthcare to ecology and smart cities.
Over five days, students delved into various AI modules, gaining practical skills and collaborating on projects designed to address real-world challenges through AI-driven solutions. Each session, led by expert representatives from partner institutions, introduced students to AI applications in science, industry, and business, with modules covering both foundational knowledge and specialized fields.
The training began with a welcome session by the host institution, UCMT, followed by introductions from participants. ULSIT presented an overview of the FAAI project, including its objectives and target audiences, to familiarize students with the broader context and goals of their work.
The day’s training sessions included:
Building on foundational knowledge, Day 2 introduced students to more technical aspects:
The day ended with collaborative team-working sessions where students worked on project ideas, guided by mentors from UBB and UCMT.
Day 3 showcased AI applications across diverse sectors:
In the afternoon, students continued with their team projects, mentored by ULSIT experts.
On Day 4, students delved into industrial and robotics applications:
Afternoon team-working sessions allowed students to finalize their project concepts, with guidance from UNI and UoM.
The training concluded with project presentations, where student teams showcased AI solutions they had developed, applying knowledge from each module to create innovative concepts targeting specific societal or industrial challenges. Projects ranged from AI-driven environmental monitoring systems to smart city applications and personalized healthcare tools. Each presentation was followed by a brief Q&A session, allowing teams to receive feedback and suggestions from trainers and peers.
Finally, all participants received certificates of completion, celebrating their dedication, hard work, and newly acquired expertise in AI and ML.
The A5.5 training in Trnava provided a comprehensive introduction to AI applications for the students, equipping them with valuable skills and practical knowledge that will benefit their academic and professional pursuits. This training was not only a stepping stone in AI education but also an inspiring experience for students, allowing them to collaborate with peers across countries and apply their skills in innovative ways. The FAAI project remains committed to supporting such experiences, fostering a skilled generation of AI practitioners ready to meet the challenges of tomorrow.
The work is fulfilled within the framework of Erasmus+ project “The Future is in Applied Artificial Intelligence” (FAAI) and devoted to the development the methodology for collecting and analyzing good practices in the field of applied artificial intelligence (AAI) regarding the competences, training, existing solutions and real cases, which can be used for developing training courses of competence based education. The empirical methods used in the research of good practice in AI include a group of methods associated with the study and generalization of competencies, advanced pedagogical experience, as well as with the study of AI solutions in the science and industry. The following groups were researched to improve the study:
The obtained data collection can be aquire here: