Baseline Survey in Monitoring and Evaluation and Performance of Education Projects in Refugee Camps in Turkana County, Kenya
Bibliographic record
Abstract
Baseline surveys serve as a foundational instrument in monitoring and evaluation, significantly enhancing the performance and impact of education projects in refugee camps by providing critical benchmarks for planning, implementation, and assessment. This study examined the influence of baseline surveys in monitoring and evaluation (M&E) on the performance of education projects in refugee camps in Turkana County, Kenya. Guided by international frameworks such as the Convention on the Rights of the Child, Sustainable Development Goal 4, and the 2018 Global Compact on Refugees, the research focused on education initiatives implemented by Windle International Kenya in partnership with the United Nations High Commissioner for Refugees (UNHCR). A census approach was employed, targeting a study population of 141 education stakeholders: 7 principals, 5 head teachers, 72 Board of Management members, 5 M&E officers, 1 County Quality Assurance and Standards Officer (QASO), 1 Sub-County QASO, 15 education officers, 15 project coordinators, 15 finance officers, and 5 program managers. These education stakeholders were selected due to their central roles in the planning, execution, and oversight of education projects, ensuring that the study captured informed perspectives on the influence of baseline surveys within the project context. Data were collected through structured questionnaires and key informant interviews and analysed using descriptive and inferential statistics, including correlation and regression analysis. Qualitative findings from interviews further contextualised the quantitative results. The results indicate a positive and statistically significant relationship between the use of baseline surveys in M&E and the performance of education projects in refugee camps (r = 0.680, p < 0.05; β = 0.172, p = 0.020). Respondents reported that comprehensive baseline surveys contribute to setting project targets, tracking progress, guiding resource allocation, and enhancing stakeholder engagement. Thematic analysis of qualitative responses highlighted the importance of financial support, community sensitisation, and improved security as key factors for project success and teacher retention. The study concludes that baseline surveys are integral to effective M&E, serving as benchmarks for planning, resource allocation, and project evaluation, ultimately improving educational outcomes for refugees. This research recommends that education project implementers prioritise baseline survey practices, ensure stakeholder involvement, invest in staff training, and integrate baseline surveys within standard M&E frameworks to enhance the project's success and performance in refugee settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".