Data-driven assessment of qualifications to Master's programmes – DDMV1
The project involves increasing the quality of the master's admissions process while reducing the workload for both PA and study administration, by automating data management to a large extent and also developing an accurate and validated model for assessment of qualifications.
Project context
KTH has many international applicants for its Master's programmes. The evaluation of these applicants currently takes considerable time for both KTH's administration and for Programme Directors (PA). The procedure requires that a number of documents are manually retrieved, opened and assessed in NyA. The efficiency of the process could be improved through automated data management. In addition, there is currently no validated method for how students' qualifications should be assessed to constitute a good indicator of their ability to succeed in their studies at KTH. The quality of the admissions process also has potential for improvement.
Ahead of the master's admissions at the SCI school in autumn 2023, a pilot project was therefore carried out during autumn 2022 with the overall goal of increasing the quality of the admissions process while reducing the workload for both PA and study administration. The pilot project succeeded in achieving both of these goals, while a number of new ideas were identified to continue towards the overall objective. There is therefore potential to further increase both the efficiency and quality of the process.
This project involves performing the work that the SCI school itself can do to move forward. Collaboration with other schools and with the university operational support (VS) has the potential to lead to further improvements.
Purpose (outcome)
The overall purpose of the project is to create better quality in the assessment for the master's admissions in autumn 2024, while reducing the time required for the work by automating all parts that can be automated. The impact targets are:
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Less work for both administration and PA, by automating all parts that can be automated (automated data management to quickly produce an easy-to-use decision support and a preliminary ranking of the students' qualifications). Follow-up via time comparisons.
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Better assessment for the international admissions in 2024, by creating a more accurate and validated assessment of qualifications model (using data from a larger number of former students at KTH than was the case in the pilot study). Follow-up via statistical analysis of the models developed.
Project results (output)
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New “Summary sheet” developed, tested and published for all participating 27 programmes at EECS and CBH (October 1, 2023).
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Validated admission model ready. Administrative support for PA ready (January 15, 2024)
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Excel programme to manage “Summary sheet” tested and ready (January 25, 2024).
Time plan
Start date: 2023-08-01
End date: 2025-01-31
Project documentation
If you have a KTH ID, you can read the latest project documents when logged in:
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Project initiation document: Projektdirektiv_FrU23_2322-SCI_Masterantagning-DDMV1.pdf (Swedish)
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Final report A3: A3_FrU24vt_2322-SCI_Masterantagning-DDMV1.pdf (Swedish)
Results
In October 2023, this SCI project Data-driven master's admission (DDMV1) was merged with the VS project Assessment of qulifications for Master's and collaboration with more schools began. The DDMV2 project (KTH-2407) now includes close to 30 master's programmes with Programme Directors (PAs) from SCI, EECS and ITM, the IT Department and central and school-based VS at the schools concerned. The work continues within the framework of DDMV2.