The aim of the project “Toolbox Datenkompetenz” (Toolbox Data Literacy) is to develop a Germany-wide digital tool and training platform that is primarily dedicated to the nationwide development of data literacy skills and makes a sustainable contribution to the implementation of the Federal Government’s data strategy and digitisation project across society.
To realise this, the following sub-objectives were developed:
- Participatory development of platform-based teaching/learning scenarios and core requirements for key societal stakeholders from business, education and politics.
- Development and testing of a low-threshold and robust digital infrastructure (platform) as the basis for open toolboxes
- Development and testing of various learning and working tools for competence building in data literacy.
- Development and testing of a secure and intuitive digital learning world that maps the teaching/learning scenarios
- Development of target group-specific incentive systems and a long-term continuation strategy (open access strategy)
TBDK as a digital toolbox
Dealing with data, especially with large amounts of data, is not trivial and requires not only basic data competence but also the practical use of modern data tools. The TBDK platform will interlock digital learning content and online-based data tools to create a practice-oriented learning offer. The platform can be used independently by business, science, politics and all citizens of the Federal Republic of Germany to build up or further develop basic data skills. With the goal of achieving nationwide data literacy, the toolbox is implemented as an open, digital toolbox that enables every learner to use the data tools for their own learning, project or research scenarios. In addition to the comprehensive and highly available online learning offer, the Toolbox will also have its own expert network, which will enable the merging of understanding and requirements for data literacy from business and science with accompanying initiatives, research projects and meta-projects (e.g. INVITE) such as forums, digital panels and working groups. Within the framework of the expert network “Data Literacy”, a separate expert board from business and science is being created for the development of the required and interdisciplinary competence standards.
Key research questions
In order to achieve these goals, a Design Science Research approach has been chosen – it is an approach that is driven by practice, brings together scientific knowledge, gains new insights and at the same time initiates and implements developments in practice.
- What are the requirements for a low-threshold platform for teaching data literacy from the different areas of society (business, education, politics)?
- What incentive systems can increase the use of the platform?
- What teaching/learning scenarios are there for the individual target groups?
- Can the findings on incentive systems and scenarios be generalised?
- Which modules and function blocks are needed within the individual target groups?
- What are common intersections for high adaptation in the target groups?
- How must the feature sets be prioritised or balanced?
- Are there different system and hardware requirements?
- Which functionalities can be covered by freely available tools?
- Can open source-based data tools cover the needs of business and science in order to sustainably assert themselves in the course of the digital transformation and knowledge transfer?
- Do commercial data tools contribute to faster and sustainable competence transfer and acceptance?
- Which free data tools are already established on the market today and which incentive systems are used?
- How can existing data tools be transferred into a low-threshold and collaborative platform?
- The platform bridges the gap between teaching/learning systems (such as classic learning content management systems) and data tools, which raises the question of which standards and semi-standards of both areas are important for implementation?
- What does an architecture model for a systematic combination of the individual functional modules look like?
- How can data protection and data security be conceptually anchored in the sense of privacy-by-default and complete data sovereignty across the platform? (Communication protocols and data flow control)
- How can platform-supported teaching/learning scenarios for data literacy (in the individual target groups) be systematically developed?
- How must learning content and data tools on a platform be interlinked in a didactic concept?
- Which learning and media formats work for the sustainable teaching of data literacy?
- How can the platform content also be used or supplemented outside the digital platform as part of a blended learning approach?