Evaluation

The Improving Learning Outcomes for Asia (ILOA) regional project works closely with USAID’s Asia Bureau and Missions across the region to identify key questions and challenges Mission staff face in their day-to-day work. An advisory group of USAID Mission colleagues raised an important question: how best to wade through the array of education data available? What are the types, how are they used, when are different data useful, etc.? Indeed, the use of different data to effectively partner with governments to make evidence-based decisions is a top priority. As a result, ILOA produced a brief summarizing the different sources and uses of data for basic education, youth and workforce development, and higher education. The brief recognizes how data sources and uses have evolved over time, enabling ministries, their partners, and stakeholders to measure performance, inform policy and plan interventions, and manage limited resources. The brief is designed to succinctly assist USAID staff and their partners in navigating the world of education data.

Presentation at CIES in March 2024.

A classroom observation tool for a kindergarten teacher in distance education.

Classroom Observation Tool for Kindergarten Class (kG2).

A tool for evaluating teacher performance for grades 1-3 mathematics education in Arabic language in distance education.

Classroom observation tool for grades 1-3 mathematics education in Arabic.

Lot Quality Assurance Sampling (LQAS) is a methodology to measure the quality of a product. It was first used in the early 1920s of the last century in car factories to ensure their products quality. A sample of the cars manufactured by the production lines is tested to ensure its quality. Thus, the test result is mainstreamed to all cars. Through this methodology, poor quality products or “defects” can be quickly and accurately identified so that they can be disposed or repaired. As it would be a very expensive and time-consuming process if manufacturers checked the quality of each individual product they produce. Therefore, LQAS methodology provided sampling that allowed the classification of an entire production unit by testing a small number of randomly selected products of that unit. If the selected products meet the minimum quality standards, the producers are satisfied that the entire unit has met the minimum quality standards, and if a sufficient number of those selected products do not meet the minimum quality standards, then the entire unit is rejected. This methodology was first used in the humanities, including education, about 20 years ago. Using such a methodology in the education sector enables the Ministry of Education and field directorates to control the quality of the teaching and learning process, and to classify schools as “Achieving” or “Not achieving” the minimum standards of performance quality. Likewise, the MOE’s officials can categorize field directorates as “Achieving” and “Not achieving” the minimum performance standards.

The current study sought to test the stability of the new classroom observation tool that was developed by the initiative, and to reveal the extent of consistency among educational supervisors in their understanding of this tool. The study sample consisted of 80 male and female teachers who taught early grades in 10 schools in five education directorates in the three regions during the first semester of the 2019/2020 academic year.

The Early Grade Reading and Mathematics Initiative (RAMP) has a great interest in the quality of the data related to the initiative’s activities, whether in term of the trainees’ data (teachers, school principals, educational supervisors, or senior teachers), classroom observation data, community of practice data, and other data. To ensure data quality, it was necessary to develop clear and specific Standard Operating Procedures (SOPs) to be used by the Monitoring & Evaluation (M&E) team in data audits and quality control.

RAMP initiative – pupil questionnaire 1.