Partners' Institution:
Universidad de Màlaga
Project's period (from/to):
01 January 2022 - 31 December 2023
Activity concerned:
PM - Project Management
Objectives of activities carried out:
Up to 30 June: Contacting the international office of Málaga, setting up a Teams area for filing material. Contacting researchers and teachers in the department, who might be stakeholders in the project. Execution of first part of the project related to embedding in literature and knowledge of algorithms and benchmarks. Dissemination of the project.
Up to 23 of December
Contacting the international office of Málaga, work on time sheets.
Contacting researchers and teachers in the department, who might be stakeholders in the project. Discussing the results of the first part of the project.
Discuss approaches about development of a recommender system using mathE.
Up to 22 of June 2023
Gather students to do experiments
Develop the python implementation of the recommender system
Discuss with local stakeholders and analyse results
Objectives were:
-Contacting project management within the university
-Meetings with potential stakeholders
-Discussing and developing the learning approach
-Implementation of a system
-Analysis of results
Up to 22 of December 2023
-carry out dissemination
-develop the recomender system in cooperation with other partners
-develop the applet
-upload reports and applet documentation into iMath platforms
-update time sheets
Up to 23 of December
Contacting the international office of Málaga, work on time sheets.
Contacting researchers and teachers in the department, who might be stakeholders in the project. Discussing the results of the first part of the project.
Discuss approaches about development of a recommender system using mathE.
Up to 22 of June 2023
Gather students to do experiments
Develop the python implementation of the recommender system
Discuss with local stakeholders and analyse results
Objectives were:
-Contacting project management within the university
-Meetings with potential stakeholders
-Discussing and developing the learning approach
-Implementation of a system
-Analysis of results
Up to 22 of December 2023
-carry out dissemination
-develop the recomender system in cooperation with other partners
-develop the applet
-upload reports and applet documentation into iMath platforms
-update time sheets
Description of activities carried out:
-Composing a list of researchers and teachers within our group. We had several meetings as described in the dissemination section. We plan now to involve students by using Mathe in the start of the semester on 13 of September, but we did not prepare that part yet.
-We placed links on several websites of the university and research group in order to disseminate the project.
- Translation of the project brochure in Spanish.
-We selected 5 algorithms for an extensive description, that we thing that are very relevant to the project. Specifically, we have experience with all of them in our former investigation.
-We looked for benchmarks which we have been using in our investigation before and described 5 of them
-We describe 10 books and/or articles that have inspired us before and that we think that are of interest to the iMath project.
-For the learning indicators, we mainly discussed them with the experts within the department that have been working on them.
Up to 23 of December 2022
-Reporting on carried out activities for PR1 about embedding in literature and knowledge of algorithms and benchmarks. We created a list of findings and a presentation for the consortium meeting in Patras.
-We discussed the results and the challenges for PR2 in Patras.
-We included 2 teachers and a (technician) researcher to the Project to discuss possible approaches and perform testing with students.
-We worked on further dissemination of the Project mainly in international conferences and also in the school. We reported 8 more of these dissemination events in the Project portal.
-It appeared that ideas about the objectives were not that clear among Project partners and from September we have had several discussion meetings.
-Actually, we started to study more literature on recommender systems and added summaries to the literature overview in the portal.
-We focused on keywords to be added to specific MathE questions.
-We contacted students for testing the system. However, due to not being directly involved in the corresponding classes, we failed a bit in attracting the necessary critical mass.
-Installing Python and its libraries in computers to get the code of Giulia running. Solving problems in this respect.
Up to 22 of June 2023
-contracting a collaboator to help implementing the python system
-work on dissemination of the project ideas
-discuss approaches mainly with he partners from Hamburg and Slovenia. We had many online discussions about the approach
-Studing various recommender ideas from a book we added o the literature review
-We were successful in obtaining Málaga students to help in the experiments
-reporting on our findings for the meeting in Hamburg
Up to 22 of December 2023
This period was more productive. Not only due to the availability of the technician Alejandro, but also because we had inspiring discussions in Hamburg with partners Andrej and Ivo. Moreover, we investigated the research question on how to visualise concept maps
-Meeting with Braganca partners in braga to update the recommender system, such that it selects from a subgroup of questions
-We actually added quite some material to the iMath library as we studied far more the literature on recommenders
-we also scanned the resources and added comments to the material that inspired us
-we developed a python script for participation of students
-development of the applet
-lots of discussion on literature on graph visualization
-development of reports
-study tips and write about them
-We placed links on several websites of the university and research group in order to disseminate the project.
- Translation of the project brochure in Spanish.
-We selected 5 algorithms for an extensive description, that we thing that are very relevant to the project. Specifically, we have experience with all of them in our former investigation.
-We looked for benchmarks which we have been using in our investigation before and described 5 of them
-We describe 10 books and/or articles that have inspired us before and that we think that are of interest to the iMath project.
-For the learning indicators, we mainly discussed them with the experts within the department that have been working on them.
Up to 23 of December 2022
-Reporting on carried out activities for PR1 about embedding in literature and knowledge of algorithms and benchmarks. We created a list of findings and a presentation for the consortium meeting in Patras.
-We discussed the results and the challenges for PR2 in Patras.
-We included 2 teachers and a (technician) researcher to the Project to discuss possible approaches and perform testing with students.
-We worked on further dissemination of the Project mainly in international conferences and also in the school. We reported 8 more of these dissemination events in the Project portal.
-It appeared that ideas about the objectives were not that clear among Project partners and from September we have had several discussion meetings.
-Actually, we started to study more literature on recommender systems and added summaries to the literature overview in the portal.
-We focused on keywords to be added to specific MathE questions.
-We contacted students for testing the system. However, due to not being directly involved in the corresponding classes, we failed a bit in attracting the necessary critical mass.
-Installing Python and its libraries in computers to get the code of Giulia running. Solving problems in this respect.
Up to 22 of June 2023
-contracting a collaboator to help implementing the python system
-work on dissemination of the project ideas
-discuss approaches mainly with he partners from Hamburg and Slovenia. We had many online discussions about the approach
-Studing various recommender ideas from a book we added o the literature review
-We were successful in obtaining Málaga students to help in the experiments
-reporting on our findings for the meeting in Hamburg
Up to 22 of December 2023
This period was more productive. Not only due to the availability of the technician Alejandro, but also because we had inspiring discussions in Hamburg with partners Andrej and Ivo. Moreover, we investigated the research question on how to visualise concept maps
-Meeting with Braganca partners in braga to update the recommender system, such that it selects from a subgroup of questions
-We actually added quite some material to the iMath library as we studied far more the literature on recommenders
-we also scanned the resources and added comments to the material that inspired us
-we developed a python script for participation of students
-development of the applet
-lots of discussion on literature on graph visualization
-development of reports
-study tips and write about them
Results Achieved:
Plan of project activities including dissemination
- List of stakeholder researchers, lecturers and students that will be contacted to be involved
- Number of links placed on websites with the iMath information
- Project brochure in Spanish
- 10 literature papers/books reviewed
- Description of 5 optimisation algorithms
- Description of 5 benchmarks
- Description of 3 student indicators
- Dissemination in terms presenting the project to teachers and researchers at our department. Presentation of iMath to our project partners
Added up to 23 of December 2022
Dissemination activities carried out and reported
- Added reviews of works related to recommender systems to the project library mainly handbooks related to Python oriented recommender systems specifically for learning
-Contribution to discussing the possible approaches with Ana Pereira and with the complete consortium
-Management activities for time sheets and adding co-workers to the project
-Advertising for attracting students within 4 linear algebra courses
-Started administrative procedure to hire a technician with other funding for the project elaboration
-Test environment set up
-Keyword structure for knowledge graph approach set up
Added up to 22 of June 2023
-Implementaions added to github
-obtaining experimental results
-Management activities for the financial report
-Intention to create a repot on the idea of adding concept maps to the recommender
-We implemented two different recommenders based on collaborative filtering and experiemented with randomly assigning them to students to measure their impact.
Added up to 22 of December 2023
-Implementation of an RMSE measurement in dash
-Integration of software with Braganca
-Developed applet on concept map visualisation
-Technical reports
-upload the tips and a presentation to discuss them
- List of stakeholder researchers, lecturers and students that will be contacted to be involved
- Number of links placed on websites with the iMath information
- Project brochure in Spanish
- 10 literature papers/books reviewed
- Description of 5 optimisation algorithms
- Description of 5 benchmarks
- Description of 3 student indicators
- Dissemination in terms presenting the project to teachers and researchers at our department. Presentation of iMath to our project partners
Added up to 23 of December 2022
Dissemination activities carried out and reported
- Added reviews of works related to recommender systems to the project library mainly handbooks related to Python oriented recommender systems specifically for learning
-Contribution to discussing the possible approaches with Ana Pereira and with the complete consortium
-Management activities for time sheets and adding co-workers to the project
-Advertising for attracting students within 4 linear algebra courses
-Started administrative procedure to hire a technician with other funding for the project elaboration
-Test environment set up
-Keyword structure for knowledge graph approach set up
Added up to 22 of June 2023
-Implementaions added to github
-obtaining experimental results
-Management activities for the financial report
-Intention to create a repot on the idea of adding concept maps to the recommender
-We implemented two different recommenders based on collaborative filtering and experiemented with randomly assigning them to students to measure their impact.
Added up to 22 of December 2023
-Implementation of an RMSE measurement in dash
-Integration of software with Braganca
-Developed applet on concept map visualisation
-Technical reports
-upload the tips and a presentation to discuss them