Virtual capacity strengthening during COVID-19
The GRID3 Training Team has been working full speed to develop an online Learning Management System (LMS) that will make it possible to train hundreds of data experts during a time in which COVID-19 makes in-person interaction limited. Now the platform is ready and being implemented in various of the GRID3 countries. The LMS aims to complement and substitute face-to-face learning activities and will be an inherent part of the GRID3 programme even beyond COVID-19.
The GRID3 LMS, available at learn.grid3.org, hosts GRID3 courses and teaching materials, and allows to engage directly with enrolled participants in one application. GRID3 is now implementing distance learning activities, built around defined geospatial competencies, linked to the Geospatial Technology Competency Model (GTCM), and using the classification of learning activities. These two frameworks are widely-used methods and models that aim to harmonise competencies and statistics related to learning activities across countries.
The LMS will host courses around the following themes: Foundations of Geographic Information Systems (GIS) and Spatial Statistics; Support for Population Census and Microcensus; Gridded Population Survey; and Spatial Analysis, Statistics and Visualisation.
Selected participants are enrolled in the system and receive access to a learning plan based on the available courses supporting the desired geospatial competencies. Individual users are then able to interact with the GRID3 site primarily through their dashboard, which displays courses, modules, social hubs and learning plans. All the information needed is available in one central location.
While face-to-face learning remains GRID3’s first choice for capacity strengthening, the implementation of the GRID3 LMS at a wider scale allows training commitments to continue during COVID-19 and will supplement in-person engagement beyond the pandemic. The system is up and running for cohorts in the Democratic Republic of the Congo (DRC) and is due to go live in July for selected partners in Nigeria.
Implementation in GRID3 countries
In DRC, GRID3 is delivering a Trainer Support Programme to the Congo Basin Water Resources Research Center at the University of Kinshasa, the Census Bureau (Bureau Central de Recensement), and the National Agency for Clinical Information and Health Informatics (the Agence Nationale d’Ingénierie Clinique d’Information et d’Informatique de Santé, ANICiiS), as part of a collaborative engagement with the University of Kinshasa. The Trainer Support Programme is a means of reaching more people by enabling suitable trainers in-country to facilitate and lead their own future training courses, using GRID3 materials and LMS resources. To deliver this programme, GRID3 is using a blended approach of online and offline courses, with the LMS being supported by face-to-face sessions in Kinshasa at the end of June to a restricted number of participants and adhering to COVID-19 prevention standards. The course focuses on strengthening QGIS skills, a desktop geographic information system application, for population and health studies in DRC.
In Nigeria, GRID3 will deliver a foundational course in R for Bayesian Population Modelling to the National Population Commission. This course provides a digital practice-based overview of R coding as a required skill set, before a face-to-face advanced workshop on Bayesian Population Modelling is organised in the future. A Bayesian model is the modelling approach used by GRID3 to produce its gridded population estimates. The course features a live online webinar, recorded instructional videos and self-taught distance learning accessible to enrolled participants via the LMS.
Capacity strengthening is a strategic priority for GRID3 that ensures sustainable and positive ground-level impact on people’s lives. The LMS allows sustained knowledge management activities to continue through this uncertain time and beyond, supporting both online/distance learning and blended face-to-face support, with the overall aim to make basic georeferenced data available and useful for decision makers and strengthen countries’ capacity to produce and use those data.