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https://www.um.edu.mt/library/oar/handle/123456789/138988| Title: | Extracting notional machines for databases |
| Authors: | Miedema, Daphne Fletcher, George Aivaloglou, Fenia Busuttil, Leonard Farinetti, Laura Goodfellow, Martin Guerrini, Giovanna Haldeman, Georgiana Pan, Yuhan Ramagoni, Sujeeth Goud Satyavolu, Chandrika Sooriamurthi, Raja Tu, Xiaoying Tudor, Liviana |
| Keywords: | Education -- Databases Computer science -- Data processing Machine learning Information visualization |
| Issue Date: | 2025 |
| Publisher: | Association for Computing Machinery |
| Citation: | Miedema, D., Fletcher, G., Aivaloglou, F., Busuttil, L., Farinetti, L., Goodfellow, M.,...Tudor, L. (2025, June). Extracting Notional Machines for Databases. Proceedings of the 30th ACM Conference on Innovation and Technology in Computer Science Education v. 2, Netherlands. 693-694. |
| Abstract: | Database education is a cornerstone under many of the more popular topics in computer science such as machine learning and visualization. Although, in recent years, more fundamental research into database education has come out, there are many more ways in which it can be extended. Research on the practice of teaching databases, namely on the educational materials and explanations of teachers, can help us create new building blocks for fundamental research. This working group aims to collect and present notional machines of different types, for a wide range of database subtopics. These materials offer and updated context for database educators to design their courses from, as well as open up pathways of further research into database education. |
| URI: | https://www.um.edu.mt/library/oar/handle/123456789/138988 |
| Appears in Collections: | Scholarly Works - FacEduTEE |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Extracting_notional_machines_for_databases_2025.pdf | 818.67 kB | Adobe PDF | View/Open |
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