The Sustainable Development Goals (SDGs) Global Indicator Framework (GIF) has multiplied training needs due to the large number of new indicators to be monitored by countries, whereas COVID-19-related social distancing restrictions have provided an unexpected springboard for the proliferation of cutting-edge virtual training tools and modalities. This has exposed a panoply of new data-related skills needed by contemporary statisticians, and therefore the types of training that could be most appropriate for acquiring these skills. This paper analyses the changing context and nature of training, with particular reference to the experience of FAO as a custodian agency for a large share of SDG indicators. The combination of different learning modalities, appropriately blended into a coherent learning programme, is shown to have the greatest impact, with one modality reinforcing the strengths and dampening the limitations of another.
Related
Increasing user engagement around data and statistics
Course
Self-paced e-learning
Offered by:
SIAP, UNSD
SDG: 2030 Agenda, Breaking the silos, Leave no one behind
SDG: 2030 Agenda, Leave no one behind, SDG 2
Integrating surveys with geospatial data through small area estimation
Resource
Document
Offered by:
Khalil, Clara Aida; Di Candia, Stefano; Falorsi, Piero Demetrio; Gennari, Pietro
FAO
SDG: 2030 Agenda, Leave no one behind, SDG 2
Alternative methods for disaggregating SDG indicators
Resource
Document
Offered by:
Falorsi, Piero Demetrio, Donmez, Ayca, Khalil, Clara Aida, Di Candia, Stefano, Gennari, Pietro
FAO
SDG: 2030 Agenda, Leave no one behind, SDG 2
Tracking progress on food and agriculture-related SDG indicators 2021
Resource
Training material
Offered by:
FAO
SDG: 2030 Agenda, Leave no one behind, SDG 1, SDG 2, SDG 5, SDG 6, SDG 10, SDG 12, SDG 14, SDG 15
SDG: 2030 Agenda, Breaking the silos, Leave no one behind