Foundational Learning Data in MICS: FLS and FLM 2.0

This upcoming one-week residential course, co-taught with UNICEF, introduces participants to the foundational learning data collected through UNICEF’s Multiple Indicator Cluster Surveys (MICS). The course is made possible through generous funding from the Gates Foundation.

Overview of the course

The one-week residential course will be held at the University of Cape Town, from 15-19 February 2027. This five-day course equips participants to prepare, analyse and communicate foundational learning data from the MICS Foundational Learning Skills (FLS) module and the updated Foundational Learning Module (FLM 2.0). Household surveys such as MICS assess children in sampled households, including those who are out of school, and link their learning to rich information on their families, health and schooling. Participants will learn what these data can and cannot tell us, and how to turn careful descriptive analysis into clear, policy-relevant data stories.

Who this course is for

This course is ideal for postgraduate students and researchers based in universities, NGOs, education ministries, assessment units and statistics offices who work with, or plan to work with, foundational learning data. The course will benefit those who wish to:

Use MICS foundational learning data correctly and confidently in their own analysis.
Understand how the FLS module and FLM 2.0 measure reading and numeracy, and how they relate to SDG 4.1.1(a).
Go beyond headline indicators to understand which children are learning, which are not, and why it matters for policy.
Communicate findings through clear charts and short data stories for policy audiences.

What you will learn

This five-day course combines lectures by AFLEARN and UNICEF specialists with hands-on labs in R. Key focus areas include:

MICS and the foundational learning modules: How MICS is designed, how the FLS module and FLM 2.0 assess reading and numeracy, and how benchmarks are defined.
Preparing the data: Downloading, merging, and harmonising MICS files; reading questionnaires alongside the data; scoring the assessments; and documenting how variables are constructed.
Survey design and representativeness: Using weights, strata, and clusters to produce national and subnational estimates with correct standard errors, and examining who is, and is not, represented in the data.
Beyond the headline indicator: Score distributions; using the rich data to explore learning by age, grade, other child characteristics, and household circumstances.
Valid comparisons: How assessment timing, age eligibility, and language affect comparisons across countries, groups, and survey rounds.
Telling the story: Building on UNICEF’s foundational learning digital stories to produce clear charts and short, well-caveated data stories.

Building a community of practice

One of the goals of AFLEARN is to strengthen the community of researchers working with data across Africa. Networking opportunities will be provided through group exercises, social events during the week, and ongoing support in the months following the course, with online sessions designed to help you continue applying your new skills to your research.

Prerequisites

The course is designed for participants with a reasonable level of data literacy and some experience of analysing survey data. Basic familiarity with R will be assumed; a short online R primer will be provided before the course. The lab is equipped with computers, but participants are welcome to use their own laptop, provided that R and RStudio are installed prior to the course. The course will be conducted in English.

Two courses, one application. This course is one of two back-to-back, one-week courses on African learning data. Course 1, Foundational Learning Data in MICS: FLS and FLM 2.0 15-19 February 2027, is co-taught with UNICEF and focuses on analysing and communicating MICS foundational learning data. Course 2, From Learning Data to Policy Evidence 22-26 February 2027, focuses on research design and on whether data are adequate to answer a research question. Participants may take either course or both.

How to apply

Please complete the course application form.

We encourage you to complete the form as soon as possible. The deadline is 8 November. Spaces are limited, and you will be notified if your application is successful. For inquiries or further assistance, please email us.