Handbook with guidelines for educators, which will be produced during WP7, Guidelines for usage of DS methodologies in education (FIŠ), will respond to 2 necessities: how to efficiently educate and train individuals in DS and how to respond to current challenges and trends represented by DS in business environments.
The project will culminate with transferable guidelines on data science in different professional environment, with special emphasis on the non-technical ones. Since one of the project goals is to develop a pilot model for higher education in data science, helping thus HEIs in adopting efficient and innovative approaches in this area, the handbook with guidelines will primarily respond to two necessities: how to efficiently train individuals in data science and how to respond to current challenges and trends represented by DS in business environments. It is becoming increasingly apparent that data scientists need to demonstrate skills necessary to convert data-based scientific inference into accessible, actionable insights for business and upper level management. Today’s data scientists need to both straddle the worlds of business boardrooms and IT as well as become a hybrid of them. Guidelines will therefore be developed for data science studies (DS already vertically implemented in curricula) and for a non-data science studies (studies that have implemented DS as horizontal element in curricula and studies that haven’t implemented DS in curricula at all) including tailoring recommendations in relation to institutions specificities. Due to fact that DS projects are lucrative and are made of various aspects (technical, business, security, data) it is not easy for regular person to understand how DS concepts can unlock value. By using the platform, the focus is to create end-to-end project description, to use simulation (prototyping) where applicable, to increase engagement level of participants and to ease up DS use-cases integration into education.
Guidelines will thus represent a clear framework and materials to support the implementation of data science in HEIs and in different business/industry sectors containing: a short reflection on data science within higher education; a proposed methodology for the implementation results within HEIs studies; set of guidelines for independent user that want to apply developed approach in data science in their daily work; guidance notes and tools to support the piloting process and evaluation procedure. From the practical point of view, it will include important instructions such as how to choose the participants, how to prepare the programme with sample schedules, which pitfalls to avoid, as well as links to useful sites, additional learning material, a link-collection with useful programmes etc. The material produced during this IO aims to strengthen HEIs through capacity and know-how building of both teaching and technical staff and to increase visibility of their activities (especially of Croatian and Slovenian partners).
The guidelines and relative materials will be updated annually, also after the project ends, and will be available in digital form (structured in textual, video and graphical form), free of charge, to the general public and all interested HEIs. The intention is to implement at least one platform use-case in at least one improved education/training course preferably of the partnering organisations, representing a standard according to published guidelines.
WP7 will produce the following deliverables:
- 1 guidelines
- 4th multiplier event