Hybrid learning models enable both breadth and depth of data science capacity building.
The two-part hybrid nature of the program was an effective model for jump-starting sustainable data science skills development and knowledge sharing in the public sector.
Through the virtual training phase, the program reached over 80 participants from Botswana, Ethiopia, Ghana, Guinea, Madagascar, Malawi, Mali, Mauritius, Nigeria, Senegal, Sierra Leone, Somalia, Somaliland, and Togo. Participants gained wide-ranging data science skills and knowledge and practical experience with tools applicable to their respective institutional contexts.
Remote delivery is cost-effective and enables people to join training opportunities across different geographies and contexts. Maintaining learner engagement and interaction is essential for high-impact virtual delivery, especially in data science. During the training, the availability and use of open platforms like Google Collab allowed participants to write and execute arbitrary code through their browsers without needing specialized software. However, there are always trade-offs with different modes of delivery, and virtual learning requires additional preparation and resourcing around languages, connectivity, and in-between session engagement.
After two months, every participant reported an increase in data science knowledge and skills. Beyond gaining knowledge, a third of them now felt equipped to practice these skills in their institutional contexts, a critical indicator of likely behavioral change as a result of the program. Working with their institutions’ leadership, the trainees were able to go on and apply the skills learnt through identifying a key problem related to the pandemic response, recovery, and resilience for data science application.
I will apply [this training] in my work. This will allow me to better process the data. I have also acquired knowledge on the visualization of the data and on how to make better predictions and limit the errors in the dissemination of results for better decision-making. –Ndeye Fatou Mboup, ICT and Innovation Project Manager, IPAR, Senegal
After the virtual training, the fellowship stage of the program provided national statistical offices (NSOs) and ministries with an opportunity for practical, hands-on learning in a hybrid format.
Partnerships are central to closing the knowledge and skills gap in data for development.
Through partnering with academic institutions to develop shorter-term online and blended learning programs led by local data scientists, NSOs and other government institutions enhance their internal capacities to develop tailored data-driven solutions to local challenges.
The program tapped into the wide AIMS data science network across Africa to facilitate the training, as well as source the pilot fellowship cohort. Training participants benefited from engaging with local data science experts and relevant use case scenarios. For example, in Malawi, the trainees were able to receive support from a fellow who designed a quality assurance and training plan for implementation across the project’s participating districts, using his knowledge of the local context, drivers, and barriers for change.
The exposure of members of staff to data science has been a big opportunity to be at pace with what is developing continentally and globally [in terms of] data exploration and data visualization; ease of analysis; identification of errors and ability to fix them. In particular, it has enabled us to improve our statistical bulletins on child protection indicators and increased our knowledge of Python programming. –Mercy Kanyuka, Commissioner of Statistics, National Statistical Office, Malawi
Building on the Global Partnership’s existing relationships with agencies like Ghana Statistical Service, the involvement of institutional leaders for their input and approval of projects from inception helped to enhance these provisions. In turn, these engagements boosted demand for improved technical skills and use of new technologies and products. Similarly, the fellows benefited from experience with real-life situations on sustainable development-related issues that will inspire their continued growth in the sector beyond this particular program.