Watch the Interviews with the instructor Calum Handforth and the participants Camila Garroux and Ida Yamaswari!
Digital interventions offer exciting new possibilities for measurement, learning and evaluation. In contrast to offline programmes, digital interventions are ‘always on’ and often reach wider groups of users, resulting in large datasets with messy and multi-format data which require data science techniques to organise and analyse.
Digital interventions also often include multiple entry points, including ‘back end’ data, system data and user generated data. How does one make sense of this new digital data, utilising data science methods while adhering to rigorous evaluation protocols? This workshop will provide a thorough grounding in developing a robust monitoring and evaluation approach for digital projects and revising existing workflows in response to the unique digital environment.
The workshop facilitators will share a digital measurement framework that integrates digital as well as traditional methods and will present case studies for its use. Workshop participants will also practice data analysis for large digital datasets, including textual data and data linkages and will walk through exercises with discussion on how to incorporate these techniques in programmatic evaluations.
- Will have a strong and practical understanding of the role of digital analytics and digital data sources
- Will be able to explore how to apply RapidPro in their current or future work
- Will have practical knowledge of how R studio can be used to organize and analyse textual data
- Increase their understanding of the digital analytics landscape, including advancements and use-cases being led by key individuals and organizations
The workshop is recommended for evaluators and practitioners who are designing M&E for digital projects.
Introductory to mid-level.
Schedule of synchronous sessions
Monday to Wednesday: 1:00 – 5:00pm CEST
Thursday: 1:00 – 3:00pm CEST
Friday: 1:00 – 5:00pm CEST
All Details inclusive Schedules and Recommended Reading.