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The multiplier event to disseminate the ideas and methods developed in the iMath project was embedded into an educational conference on electronics, which took place at the Universidad de Málaga 26-28 of June 2024.
We live in a time when Artificial Intelligence (AI) is almost everywhere, and almost everyone talks about it. The media is full of news and opinion articles, often written by people with weight in the field of communication, but without technical knowledge in the subject matter. These articles often repeat a narrative of potential dangers, biases, and deficiencies attributed to AI that could equally be attributed to humans. In the debate, we aim to analyze, in a reflective manner based on knowledge and experience, some key aspects of AI, such as its impact on our societal model and current teaching processes, or its way of learning and possible resources to reduce its errors and biases.
The iMath project organised a round table meeting to discuss about the developed methods, the online resources and the new recommender system for MathE. For the round table, we invited 4 experts to initiate the discussion and an experienced professor of the University of Málaga as discussant to lead the debate. In an afternoon session, the iMath project organised a demonstration session for electronic learning tools. When several parallel sessions finished, one plenary session in a laboratory exposed the value of an e-learning environment and demonstrate the contribution of AI in generating a recommender system.
The sixth partners' meeting of the iMath project took place in Braganca (PT). The meeting was organized in a hybrid modality and all partners participated in person or online. The main discussed topics were:
- Demonstration of the OptLearn Algorithm installed on the new version of the MathE Portal
- Presentation of the organized multiplier events
- Presentation of the strategies to guarantee the sustainability of the iMath project results
- Presentation of the target groups' assessment of the project results
The iMath Project Multiplier Event, hosted by the University of Peloponnese, successfully gathered over 50 math lecturers, researchers, and university-level students for a day of dynamic discussions and collaborations. The event began with a warm welcome from Professor Paris Kitsos, followed by Professor Spiros Sirmakessis providing an insightful overview of the iMath Project’s goals to integrate artificial intelligence into mathematical education. Participants also engaged with Professor Marios Katsis’s comprehensive presentation on optimization algorithms and explored the innovative OptLearn Algorithm presented by Professor Sirmakessis, sparking lively discussions and new perspectives.
As the event concluded, attendees participated in networking and discussions on the practical applications of the OptLearn Algorithm and the various resources offered by the iMath Project. This event not only inspired and energized participants but also laid the groundwork for future collaborations, driving forward the innovation and improvement of mathematical education. The success of the event underscored the importance of interdisciplinary collaboration and set the stage for ongoing exploration in the field.
Bragança host the XII National Meeting of Catholic Moral and Religious Education (ENES) for Secondary Education on April 12 and 13, gathering around 3,000 young people.
The event was an opportunity for students to engage with Bragança city and explore the city's heritage, art, culture, research, and hands-on experiences.
The open-air class will lead the students through two routes, marked by participation in workshops where each student will be a protagonist. One of these workshops is the iMath Project, where students will have the opportunity to explore the mathe portal equipped with the Optlearn algorithm.
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The fifth partners' meeting of the iMath project took place in Malaga (ES). All partners participated in the meeting and the main discussed topics were:
The applet has been created to allow the students to test and became more familiar with Machine Learning fundamentals and basic algorithms.In particular, you could study the error double descent phenomenon when approximating a function with a polynomial regressor: test error first decreases, then increases, and then decreases again, increasing model's polynomial degree. The phenomenon occurs under specific conditions, but the user will be able to modify regularization's parameter and polynomial degree and change the training dataset to play with the regressor and see what happens on the error’s curve.The applet has been realized using Dash and Plotly.
The partnership produced a paper on the iMath project. This paper presents the aims and activities of the iMath project and, as one specific activity, the OptLearn algorithm. The algorithm provides student activity recommendations with the aim of maximising their learning outcomes at a given student’s time effort. It is based on automatic concept map generation BFS graph walk. The paper is available at https://erk.fe.uni-lj.si/2023/papers/kosir(student_activity).pdf
A promotional event of the iMath project was held in conjunction with the 32nd International Electrotechnical and Computer Science Conference ERK 2023. The event served as a platform to raise awareness about the iMath project, with attention being drawn through a poster presented at the ERK conference, which attracted over 100 participants, and presentation within a dedicated section Didactics.
Within the bilingual section in Didactics which emphasised on several technology-related teaching aspects, a presentation of research results from the iMath project, further highlighting the project’s contributions to the field.
Following the sections’ oral presentations, a gathering of the interested public was organised. This interactive element of the event allowed for a deeper understanding of the iMath project and its implications, fostering a sense of community among the participants.
Overall, the event was successful in promoting the iMath project and in facilitating discussions on technology-related teaching aspects. The combination of presentations and discussions provided a comprehensive overview of the iMath project and its impact on the field of didactics. The event served not only as a promotional platform but also as a forum for exchange of ideas and knowledge.
The applet has been created to allow the students to test and became more familiar with Machine Learning fundamentals and basic algorithms.In particular, you could test Support Vector Machine (SVM) algorithm on a classification task. You can choose between three different datasets (Moons, Circles, linearly separable) and set noise, number of samples and distance between classes, and you can tune the main model’s hyperparameters: kernel type, kernel parameter γ, regularization parameter C and the approach to adopt in muti-class case (one-vs-one, one-vs-rest).The applet has been realized using Dash and Plotly.
The fourth partners' meeting of the iMath project took place in Hamburg (DE). All partners participated in the meeting and the main discussed topics were:
K-means is a clustering method widely recognized in the literature and used to subdivide a set of data into distinct groups called clusters. The purpose of this algorithm is to assign each element of the data set to clusters so that elements within the same cluster are more similar to each other than to elements in other clusters.
The K-means process can be summarized as follows:
This applet aims to provide a visual tool for examining different critical valuesand provide insights into the evaluation of a concept map’s quality and itsvisual representation. We focus on salience metrics to assess and help usersenhance the effectiveness of their concept maps with an evaluation of itsquality. The applet features an Interactive Graph Visualization by leveraging thePython library “dash-interactive-graphviz”, allowing the user to seamlesslyzoom in or out, to check in an easy manner the different graph layouts thatthe user can choose. It also allows the user to click on nodes to get specificmetrics and information of the node. Although two sample concept maps areprovided and the user can explore them, it also allows the user to upload aCSV file to the applet for working with its custom concept maps.Furthermore, the applet has multiple buttons with question marks that whenclicked, displays information about the usage and the shown metrics. By usingBootstrap, the applet has a responsive design and allows using it insmartphones.
The applet has been created to allow the students to test and became more familiar with Machine Learning fundamentals and basic algorithms.In particular, you could test Random Forest (RF) on a classification task. They can choose between three different datasets (Moons, Circles, linearly separable) and set noise, number of samples and distance between classes, but most of all they can tune the main model’s hyperparameters: number of trees in the forest and number of features to consider deciding the best split. The applet has been realized using Dash and Plotly.
The third partners' meeting of the iMath project took place in Florence (IT) . All partners participated in the meeting and the main discussed topics were:
The second partners' meeting of the iMath project took place in Patras (EL) . All partners participated in the meeting and the main discussed topics were:
The database of benchmarks related to learning and optimization algorithms. Join the iMath Community and submit your proposal!
The database of algorithms and terminology related to machine learning and optimization algorithms is available on the iMath Portal. Join them on the iMath Community and submit your proposal!
Math Lecturers and Researchers can now contribute to the iMath Library dedicated to scientific and academic publications onlearning and optimization algorithms. Join them on the iMath Community and submit your proposal!
The brochure of the iMath project is available on the project website in English and in all partners languages. The brochure, based on the visual identity of the project, describes the context, the aim, the activities, the target groups, and the expected results of the project.
Each national version also indicates the contact details of the national partner.
It is now possible to register to the iMath platform and contribute to the database of publications, algorithms, benchmarks and students' learning indicators. What are you waiting for? Share your results with your colleagues all around the world!
Register
The kick-off meeting of the iMath project took place online as a consequence of the COVID-19. All partners participated in the meeting and the main topics discussed were:
The iMath project is funded, by the European Commission through the Portuguese National Agency for the Erasmus+ Programme to develop a new AI-driven tool that supports higher education math students, providing them with a database of resources, hands-on activities, self-evaluation tests based on their previous performances.