In the previous project phases, ADSEE partners created innovative educational modules in data science for non-technical universities. Additionally, these modules were implemented in partners’ learning environments and tested by more than 200 students from Netherlands, Croatia, Slovenia and Germany. Evaluation of these project activities and gathering useful insights led partners to the final project phase – designing the guidelines for improvements in usage of data science methodologies in education.
As a culmination of the project, ADSEE partners created transferable guidelines on data science in different professional environments, with special emphasis on the non-technical ones. In order to create comprehensive guidelines, all previously finalized results of the project were thoroughly examined and the most important lessons-learned were set up in a form of transferable recommendations. Moreover, guidelines actually represent a model for higher educational institutions, which will help them in adopting efficient and innovative approaches when it comes to teaching about data science methods and approach.
Aim of the project partners was to create guidelines as a ready-to-use techniques for implementing data science approach. Guidelines encompass recommendations for HEIs on how to efficiently train individuals in data science and how to respond to current challenges and trends represented by data science in business environments.
Since preparing and conducting classes and lessons is a complex process, recommendations are designed as simple ready-to-implement steps/phases – a recipe for successful implementation of data science as a horizontal element in curricula.
HEIs can use prepared guidelines as a model which will help them in adopting efficient and innovative approaches when it comes to teaching about data science. Consequently, this could have a good impact on the labor market which is becoming more and more demanding when it comes to demand and supply of data workers.
You can find the guidelines here.
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