Real-time monitoring

Our relationship with learning data is proactive and purposeful. With contextual use of real-time data, we have pioneered a course corrective approach to MEL.

For program managers

As students interact with our tutoring platform, it automatically collects and synthesises key insights into their learning as it occurs. Our implementations are centred on the ability to adapt all facets of product and programme design on an ongoing basis, informed by the continuous supply of data-driven insights. The availability of learning data across multiple implementations, which has accumulated over fifteen years, enables us to identify global best practices and apply them within local contexts.

Continuous course correction

We know that numbers alone only tell part of the story, which is why our data is tightly coupled with in-field observations that provide context and deeper insight. The virtuous interplay between live learning data and contextual observations informs a wide range of course corrections throughout the life cycle of a project, ensuring we reach the intended destination of quality learning outcomes.

Formative and summative evaluation

Our international mechanisms for monitoring, evaluation and learning are combined with external frameworks to provide a comprehensive view on the impact of our projects. We work with independent researchers to evaluate project outcomes that are then reported back to ministries and funding partners.

From Data to Insight to Action

Read our white paper, which demonstrates how Whizz’s continuous course correction model led to a doubling of learning rates in rural Kenya

See how a holistic approach to EdTech has helped to:

  • Double learning rates in rural Kenya
  • Increase learning opportunities through capacity building
  • Provide long-term efficacy and ongoing learning gains