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TA-ALB-10 project: Purpose and Methodology

TA-ALB-10 project: Purpose and Methodology . . OBJECTIVE/PURPOSE. Benefits. TA-ALB -10 delivers with this project…

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TA-ALB-10 project: Purpose and Methodology

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  1. TA-ALB-10 project: Purpose and Methodology .

  2. OBJECTIVE/PURPOSE

  3. Benefits • TA-ALB -10 delivers with this project… • a one-time snapshot picture (baseline) of the school infrastructure situation and conditions all over Albania in 2011 (unique exercise for Albania with high rate of data accuracy ) • supports the MoEs and related educational institutions to identify critical infrastructure needs, which can be strategically prioritized and invested in • provides the MoES with real time data/maps and situational analysis to negotiate and request for Government/donor funding • the future SIMS tool and current data can be updated and will enable the MOES thru to LGUs and REDs to undertake more informed educational and capital investment planning • enables MoES to monitor and report on real progress/changes in future • strengthens the educational structures and the shared responsibility with the LGUs

  4. Benefits Today: Presenting 2 new tools- 1) Geographical Information System Application (GIS): turning data into images to inform policy decisions; 2) School Infrastructure Management System (SIMS): a tool to support infrastructure management and capital investment planning; Based on: 3) The School Conditions’ Survey and Inventory: the first national audit of all pre-university schools in Albania

  5. METHODOLOGYBackground • A full census of pre-university school facilities in Albania • A total of 56 persons were involved in conducting the census • Main coordination office - 6 persons • Fieldwork coordinators - 12 persons • Auditors - 38 persons • Information collected through a pre-determined questionnaire/form by trained auditors: • Institutional form: Information on the type of school, number of students, teachers, staff, budget, etc. • Building form: Information on building structure, number & type classrooms, water & sanitation, electricity & lighting, heating & ventilation, sport areas, laboratories, history of natural hazards, etc.

  6. METHODOLOGY Nature of Data • Observation component • Data was recorded based on observations and actual measurements performed by the auditors during an on-site visit of the facilities. The type of data observed include: • Number classrooms & their measurement • Number of toilets • Building conditions and structure • Water & electricity • Sport areas • Laboratories • Furniture, etc. • Interview component • Some data was collected through the interview with the Director/Responsible Teacher during the on-site visit. The type of data collected through the interview include: • Type of school • Number of students & teachers • Transport issues • Internet issues • History of the school (natural disaster history, construction history, etc.) Over 410 data variables were collected for each school audit (1 school-1 building). And was much higher for the more complicated scenarios.

  7. METHODOLOGY Data Quality Assurance • Field supervision – provided multiple supervision visits to independently verify the information collected by the field auditors throughout the 3 phases of fieldwork (initial phase, mid phase, final phase). • Online Monitoring Platform – A fieldwork management tool was in place, designed to help monitor the fieldwork and efficiently respond to specific situations. As well, an online database containing personal accounts of all auditors served to: • Measure the progress of the census • Manage school assignments between the various auditors • Report any issues/specific information captured during the fieldwork • Upload the photos from every audit in an organized fashion • Audit Form Checking – Prior to data entry, audit forms arriving in the office were thoroughly checked by trained operators. Checking consisted of finding missing information, checking logical relations between the different sections, assuring the right scenarios and the proper number of audit forms, etc. • Data Entry Validation – a data entry program was designed with several validation rules embedded in it, which minimized the risk of data entry mistakes, as well as alerted the user to any missing information or wrong information as necessary. • Post Validation Process – Several validation rules were programmed for post data entry in order to find discrepancies and to clean the data. Multiple layers of quality assurance mechanisms

  8. METHODOLOGY Partnership with educational structures (MoES, REDs, Eos) • Design of School Inventory and Conditions survey form based on MoES aspirational building standards • REDs representatives participated in School auditor training • MoES facilitated contacts with RED and EO offices • REDs facilitated entry permission to Schools • Random participation in School surveys (MoEs and RED staff)

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