MPAT Data Collection

As Gaby last wrote, we are well into carrying out the MPAT and only have about two weeks left of data collection.  Our data entry is also underway with the three MPAT-recommended steps of checking, scoring and coding – that can be better understood by reading the MPAT User’s Guide.  The three steps have been time consuming, but I feel our data is being entered in the MPAT Excel spreadsheet correctly and consistently (with some needed cleaning and scrubbing of course).

What does the MPAT consist of exactly?

  • First, we held a 2-week training to prepare – which included understanding the purpose of the MPAT, dissecting the guts of the survey itself, preparing for logistics day-to-day, etc.
  • Our survey sample consists of 480 households in 15 villages and in 2 different sublocations
  • Most of our surveys are being carried out in the local mother tongue – Kikurian – while just a few are being carried out in Kiswahili
  • Each morning at 8 a.m., the enumerator supervisors call on the village elders to help with random sampling of the village.  The elder literally pulls numbers out of a hat, indicating the households to visit on that specific day
  • Our field staff consists of one field manager who coordinates 18 daily contract staff –  2 enumerator supervisors, 12 enumerators and 4 data entry staff
  • The enumerators survey from 10 a.m. – 3 p.m., when farmers are usually home from their fields and when mothers tend to cook for their children who return from school in the afternoon
  • The data entry staff work every day at the Nuru offices to check, score and code the surveys for analysis

It was a great experience to work with Alasdair Cohen, the author of the MPAT. This was his first time working in Africa and also the first time he implemented the MPAT with an NGO. Usually working with IFAD-related staff, he set a high standard for work; but our enumerators and data entry staff rose to the occasion. Upon leaving, our staff said how they enjoyed his level of work and how they were excited to have learned so much.

We are eager to wrap up our work in the field and start to look at the final data over the next few weeks and months to come.

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