Swedish educational data - Data-driven innovation for world-leading education
| Reference number | |
| Coordinator | KUNGLIGA TEKNISKA HÖGSKOLAN - Avdelningen nätverk och systemteknik |
| Funding from Vinnova | SEK 2 184 196 |
| Project duration | August 2017 - August 2019 |
| Status | Completed |
| Venture | Data-driven innovation |
| Call | Data-driven labs |
Purpose and goal
The project aims to increase the digitization of the Swedish education sector and to find new ways of working on data-driven improvements. To achieve this goal, we have provided examples of what can be done with data, what expected results one can get and what is needed to achieve this. The results are presented below. An important conclusion, which is also the reason why we did not meet all the expectations we had in the project, is the unwillingness to share data for fear of handling personal data and for possible competition between schools and educational companies.
Expected results and effects
We have produced a research overview for the use of data in education. Academy has reported a data analysis (done by Sana Labs) that shows concrete results (change of admission test). Furthermore, RISE SICS has done a text analysis of over 59,000 degree projects that show the possibility of advanced natural language processing. We have come to the conclusion of the need of establishing quality registers for the education sector, according to the healthcare sector´s model. We also learnt that structured professional work is needed to prepare data for analysis (data readiness).
Planned approach and implementation
We have held meetings both within the project and with external stakeholders. We had two workingshops around the GDPR, one within the project and one with educational companies within Almega. Furthermore, Almega has arranged meetings regarding the need for data standards. We have met the companies Unikum, Learnster and Lexplore and are now working with Unikum on a continuation project. Further results are reported on the project web. Our conclusion is that work is needed to raise the level of data-driven work in the education sector in general, but that the potential benefits are great.