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and Learning Study: Steps Followed in Machine Learning Methods for Predicting Dropouts (for RQc)

• Which factors affecting drop-out were highlighted by girls but had not been considered in the machine learning model?

We went out into the schools and did roll call to verify whether girls in our list (previously enrolled in that school) were back in school and how that matched our predictions. Alongside this, we picked approximately four girls to do in-depth qualitative interviews to identify missing factors in our models. We also conducted FGDs, teacher interviews, and community interviews.

For Kenya, EDT monitoring data was used for dropout predictions which included secondary school girls to assess whether they progress or drop-out of school. The monitoring data was collected between August 2018–March 2019, while the new post-Covid-19 roll-call data to verify predictions was collected between February–March 2021. As EDT decided to collect project data on girls at primary level, so as to not duplicate actions, we instead focus on validating our predictions of girls at secondary level.

To verify the Kenyan predictions, 52 schools were selected (see the main report for details – but to mimic the GEC midline data) of which we had monitoring data, and therefore predictions, for 208 girls. These girls were attending secondary grades (predominantly Forms 1 & 2) during the midline data collection in 2019 before the school closures due to the Covid-19 pandemic in 2020. If they were still enrolled, it was expected to find these girls one grade up from their midline grade – mainly in forms 2 & 3 if progressed successfully. Table 2 below summarises the number of girls shared to try and locate during the roll call.

Table 2: Sample size for roll call shared, Kenya

Of the 208 secondary school girls shared for roll calls, the research team received information on enrolment status of 203 girls. Of these, 138 were still enrolled in 2021, while the enrolment status of 30 girls could not be verified. This means that the roll call status was not verified in 35 cases (17% of the original shared secondary lists).

Table 3: Number of girls from roll call received, Kenya

Enrolled # girls

No 35

Unknown 30

Total 203

The 30 girls for whom the roll call could not be verified come predominantly from Form 1 in 2019. The main reason for not being able to verify girls’ status was no ability to speak with the caregiver due to offnet number or simply not picking up calls (90%). In three cases, there was a mismatch between the EDT monitoring data and what was shared by a primary caregiver when reached over the phone. Therefore, these girls could not be found in the expected secondary schools as they were in lower primary grades in 2021. This may in fact be a reason for some other of the unknown cases as the girls who were not found come from Form 1 of the EDT monitoring data in 80% of cases as shown in Table 4

Grade

Therefore, 173 girls are used in the analysis and their enrolment status is verified against predictions. For Nepal, Mercy Corps’ midline survey conducted in January 2019 was used to make predictions about girls’ future transition or drop-out. The newly collected post-Covid-19 roll-call data was collected in April 2021. To verify the Nepalese predictions, 45 sampling schools were selected which were attended by 574 girls in grades 8, 9, and 10 in 2019. Therefore, if still enrolled, it is expected to find these girls two grades up from their midline grade – in grades 10, 11, and 12. The predictions are checked against transition outcome for 317 girls who were in grades 9 and 10 in January 2019 and are therefore expected to be found in higher secondary levels. Furthermore, transition status is verified for 214 girls who are expected to have completed their secondary school education since they were in grades 9 and 10 in January 2019 which are the highest grades available in their schools, and for 43 grade 8 girls who are expected to transition into secondary schools.

II Access and Learning Study: Steps Followed in Machine Learning Methods for Predicting Dropouts (for RQc) girl transferred to a different school or dropped out (in 120 cases). In two cases, the girl was not known to the school, and the transition status of the 10 grade-8 girls who were meant to transition into a secondary school is unclear as shown in Table 6. 6 The girls for whom the enrolment status could not be verified come from various grades as shown in

Table 7

Full details of the results are in the main body of the text.

6 Data collection team mentioned that these girls could have got married in India, but no one has definitive information on their enrolment status in the school.

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