Influence of school accountability practices on academic achievement in secondary schools: A case of Nyabihu District, Rwanda (2023-2024)

Zephanie Habumugisha; Elizabeth Akinyi Owino

doi:10.51867/ajernet.7.2.63

Authors

Habumugisha Zephanie University of Kigali, Rwanda
Elizabeth Akinyi Owino University of Kigali, Rwanda

DOI:

https://doi.org/10.51867/ajernet.7.2.63

Keywords:

Academic Achievement, Accountability, Data-Driven Decision-Making, Performance Metrics, School Improvement Plans

Abstract

This study examined how school accountability practices influence academic achievement in secondary school in Nyabihu District, Rwanda. It focused on four main objectives: to examine the influence of performance metrics on academic achievement in secondary schools in Nyabihu District, to assess the influence of data-driven decision making, to evaluate the influence of teacher and staff evaluations, and to analyze the influence of school improvement plans on academic achievement in secondary schools in Nyabihu District. The research was based on Results-Based Accountability (RBA) Theory as the guiding theoretical framework. A descriptive and correlational research designs were used, with a total of 1125 participants surveyed and a sample of 295 selected, including 11 school leaders, 11 directors of studies, 31 teachers, and 242 students. The sample size was found using Yamane’s formula, along with stratified and purposive sampling techniques to choose participants. Data were collected using a structured questionnaire, and an interview guide. Qualitative data were analyzed through thematic analysis to find important themes, while quantitative data were examined using percentages, frequencies, means, standard deviation, and regression analysis with IBM SPSS Statistics version 27. The findings showed positive effect of different school accountability management policies on students' learning outcomes in secondary schools in Nyabihu District: Performance metrics explained 96.3% of the differences in students' learning outcomes (R² = 0.963, p = 0.000), indicating a strong positive effect on students’ success in learning. This means that performance metrics are sufficient to significantly improve academic achievement. Data-driven decision-making contributed to 56.4% of the differences in learning outcomes (R² = 0.564, p = 0.002), suggesting a moderate positive effect on student learning. However, this means that data-driven decision-making is not enough on its own to fully support student outcomes, showing that improvement should be established in these methods. Teacher and staff evaluations showed 25.3% of the differences in learning outcomes (R² = 0.253, p = 0.003), revealing a significant but relatively weak effect. This suggests that current teacher and staff evaluations are not sufficient to effectively boost student learning outcomes, indicating the need for changes and improvements. School improvement plans explained 37.0% of the differences in learning outcomes (R² = 0.450, p = 0.002), showing a significant but moderate relationship. This indicates that school improvement plans are unclear in effectively supporting and enhancing student learning outcomes in Nyabihu District, pointing out a key area for further development. In conclusion, the study recommended that school leaders should prioritize setting clear performance goals, strengthen school improvement plans, and provide ongoing teacher training in data use. The Ministry of Education should support these efforts through national guidelines and capacity-building programs. Future studies are encouraged to examine how long-term use of data-driven decisions impacts student achievement across various school environments.

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