How does one make sense of new digital data, utilizing data science methods while adhering to rigorous evaluation protocols? This workshop provides a thorough grounding in developing a robust M&E approach for digital projects and revising existing workflows in response to the unique digital environment.
From the event website:
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 become familiar with the ‘building blocks’ of digital analytics, including Google Analytics, surveys and comment analysis
- Will be able to practice analysis using digital data
- Will be able to understand how digital data can be used for monitoring and evaluation purposes
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 Friday: 2:00 – 4:00pm CEST