Please visit our Events page for upcoming training dates and bookings.

We also offer this training in-house for organisations and individuals, so you can access evaluation learning when you need it, with support to apply it to your own projects or programs. Contact us for details and a customised quote.

Practical training for meaningful conclusions

Combining insights from different data sources is essential for reaching robust conclusions in Monitoring, Evaluation and Learning. Our training provides practical guidance for synthesising findings, developing recommendations, and engaging stakeholders in meaningful reflection for ongoing improvement.

About this module

In this module you will learn the key skills needed to integrate and make sense of Monitoring, Evaluation and Learning (MEL) data from multiple sources. We will teach you rigorous yet realistic approaches for distilling lots of data down into a coherent ‘rich picture’ that informs evaluative judgments and addresses key evaluation questions. We will also help you to explore how to develop effective recommendations, and to engage key stakeholders in making sense of and refining MEL findings.

After completing this module, you will have practised summarising and integrating data from various sources into meaningful findings, developed draft recommendations, and used a rubric to make evaluative judgments. You will take away useful examples and resources to help you in future.

You will build your skills to:

  • Understand how synthesis and sense-making are used in MEL to develop a ‘rich picture’ that contributes to evaluative judgments
  • Use sense-making processes to identify insights from data, and understand how to involve stakeholders in these processes
  • Apply synthesis techniques to integrate information from various sources in ways that are practical and technically sound
  • Understand when and how to develop recommendations that are suitable for different audiences and contexts
  • Recognise and manage ethical issues related to synthesis and sense-making, including stakeholder voice, integrity, and research limitations

Who this module is for

This module is designed for people who have beginner to intermediate skills in Monitoring, Evaluation and Learning. It is highly relevant to those working in and with for-purpose organisations, whose roles relate to any of the following:

  • Research or evaluation
  • Planning, design and development of services and programs
  • Program or project management
  • Quality improvement or stakeholder engagement

Format of this module

  • Online or onsite: 1 x half day session

Our approach

Our down-to-earth training is specially designed for social purpose organisations across health, community services, education, international development and beyond. Participants in our interactive workshops use real projects as working examples, with a strong focus on ‘learning by doing’. Our facilitators draw on their extensive experience in Monitoring, Evaluation and Learning to explain complex concepts in plain language, and help you apply them to your own context.

Here's what a past training participant said about our MEL training:

Best aspects of this training: Very clear, use of diverse approaches, knowledgeable facilitators, warm encouragement of everyone, use of humour, well-paced and great handouts to support it all. Overall, it felt like a high level of value.

Our presenters

Our facilitators are Lirata staff with extensive real-world experience in designing and conducting Monitoring, Evaluation and Learning processes, as well as providing training and mentoring. Presenters vary depending on the session but often include Kate Randall, Alex Gruenewald, Katie Ronson and/or Mark Planigale.

Related training modules

Synthesis and sense-making are closely related to evaluation design. We encourage participants registering for this module to also register for our introductory module on Monitoring and Evaluation Frameworks (MEL-02), to gain a deeper understanding of how evaluation questions, indicators and data collection choices shape MEL findings.