+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +**********************************************************************
Zeit:
Dienstag, 30. Januar 2024, 14.00 Uhr
Ort:
9222, E3, Ahornstr. 55 und hybrid via Zoom (https://rwth.zoom-x.de/j/64937773189?pwd=eGttNUMzSElnQUVkc3FrYzBqK2F4UT09)
Referent:
Lubna Ali M.Sc. RWTH Lehr- und Forschungsgebiet Informatik 9 (Lerntechnologien)
Thema:
convOERter: A Technical Assistance Tool to Support Semi-Automatic Conversion of Images in Educational Materials as OER
Abstract:
Open Educational Resources (OER) are seen as an important element in the process of digitizing higher education teaching and as essential building blocks for openness in education. They can be defined as teaching, learning, and research materials that have been made openly available, shareable, and modifiable. OER include different types of resources such as full courses, textbooks, videos, presentations, tests, and images, which are usually published under the open Creative Commons licences. OER can play an important role in improving education by facilitating access to high quality digital educational materials. Accordingly, there is a steady increase among higher education institutions to participate in the so-called "open movement" in general and in utilizing OER in particular. Nevertheless, there are many challenges that still face the deployment of OER in the educational context. One of the main challenges is the production of new OER materials and converting already existing materials into OER, which could be viable by qualifying educators through training courses and/or supporting them with specific tools. There are many platforms and tools that support the creation of new OER content. However, to our knowledge, there are no tools that perform fully- or semi-automatic conversion of already existing educational materials. This identified gap was the basis for the design and implementation of the OER conversion tool (convOERter). The tool supports the user by semi-automatically converting educational materials containing images into OER-compliant materials. The main functionality of the tool is based on reading a file, extracting all images as well as all possible metadata, and substituting the extracted images with OER elements in a semi-automated way. The retrieved OER images are referenced and licenced properly according to the known TASLL rule. Finally, the entire file is automatically licenced under Creative Commons excluding specific elements from the entire licence such as logos. In order to evaluate the effectiveness of the tool in promoting the use of OER, a comprehensive user study was conducted with educators and OER enthusiastic at different universities. The study was accomplished by offering a series of OER evaluation workshops to compare the conversion efficiency of the tool with manual conversion. The results show that using the conversion tool improves the conversion process in terms of speed, license quality, and total efficiency. These results highlight that the tool can be a valuable addition to the community, especially for users less experienced with OER. As a future work, it is intended to further develop the tool and improve its functionality. Additionally, a long-term study can be conducted to assess the impact of the tool in facilitating and enhancing the production of OER on a larger scale.
Es laden ein: die Dozentinnen und Dozenten der Informatik
Dear colleagues,
during my past affiliation at TU Dortmund, I have organised workshops on music data analysis, as part of "SIGMA" cooperation (special interest group on music analysis).
Now, I'm happy to inform you that the series of workshops will be continued at the RWTH but also at TU Dortmund and other cooperating institutes.
The workshops will be organised in a hybrid way, so that both on-site and on-line participation are possible.
In case you are interested in future cooperations like research studies or supervision of bachelor and master theses, in particularly in the area of "AI for music analysis and music generation", please do not hesitate to contact me!
Further information about SIGMA is available on http://sig-ma.de
The program of the following 56th SIGMA meeting: 15.02.2024, 14:00-16:20 Chair for AI Methodology, RWTH Aachen, Theaterstr. 35-39, room 325 https://rwth.zoom-x.de/j/66894045629?pwd=M08rK1N3UVRHUXpRaXd0Qlp5MGQ2dz09
14:00-14:05 Welcome greetings
14:05-14:30 Conference study Fabian Ostermann: Adaptive video game music as a multi-objective benchmark for conditional autoregressive models
14:30-15:20 Research study Claus Weihs: Optimized decision trees – how to improve model quality in music data analysis
15:20-16:10 Research discussion Martin Ebeling: Is that what you hear? How ambiguities in hearing disturb the modelling of auditory perception
16:10-16:20 Conferences and calls, teaching activities, miscellaneous, next meeting
Kind regards, Igor Vatolkin
Dear colleagues,
you are cordially invited to participate in the 57th SIGMA workshop on music data analysis: 11.07.2024, 16:00-18:15, a hybrid event
Chair for AI Methodology, RWTH Aachen, Theaterstr. 35-39, room 325 https://rwth.zoom-x.de/j/65207808501?pwd=kbnDVGCRT5WvPI5RV4KbwLl0HJYp6J.1
16:00-16:05 Welcome greetings
16:05-16:35 Bachelor’s thesis (introduction) Philipp Springer: Using the Rank-N-Contrast Framework to Evaluate the Similarity of Polyphonic Audio Recordings
16:35-17:05 Conference study Leonard Fricke: Adaptation and Optimization of AugmentedNet for Roman Numeral Analysis Applied to Audio Signals
17:05-18:05 Master’s thesis (results) Johannes Mertens: Results of Empirical Studies on the Perception of Intervals and Triads with Historic Temperaments (with an introductory listening demo by Martin Ebeling)
18:05-18:15 Conferences and calls, teaching activities, miscellaneous, next meeting
Best regards, Igor Vatolkin
informatik-vortraege@lists.rwth-aachen.de