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emis_user_manual_data_warehouse [2020/09/04 02:19] – [Special Education] ghacheyemis_user_manual_data_warehouse [2023/12/13 20:52] (current) – [Teachers] ghachey
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 <note tip>The table warehouse.EdLevelERDistrict is essentially the same but with the added ability to disaggregate by districts.</note> <note tip>The table warehouse.EdLevelERDistrict is essentially the same but with the added ability to disaggregate by districts.</note>
 +
 +Details about the columns names in this table are included below:
 +
 +  * **SurveyYEar**: school year of survey to collect data
 +  * **ClassLevel**: the class level or grade
 +  * **YearOfEd**: the official year of education of the class level
 +  * **OfficialAge**: the official age of the class level
 +  * **enrolM**: males enrolled
 +  * **enrolF**: females enrolled
 +  * **enrol**: total enrolled
 +  * **repM**: male repeaters
 +  * **repF**: female repeaters
 +  * **rep**: total repeaters
 +  * **psaM**: male pre-school attenders
 +  * **psaF**: female pre-school attenders
 +  * **psa**: total pre-school attenders
 +  * **intakeM**: males intakes (new enrollments without repeaters)
 +  * **intakeF**: females intakes (new enrollments without repeaters)
 +  * **intake**: total intakes (new enrollments without repeaters)
 +  * **nEnrolM**: males enrolled of official age
 +  * **nEnrolF**: females enrolled of official age
 +  * **nEnrol**: total enrolled of official age
 +  * **nIntakeM**: males intakes of official age
 +  * **nIntakeF**: females intakes of official age
 +  * **nIntake**: total intakes of official age
 +  * **nRepM**: male repeaters of official age
 +  * **nRepF**: female repeaters of official age
 +  * **nRep**: total repeaters of official age
 +  * **popM**: male population as per most recent population projection in use
 +  * **popF**: female population as per most recent population projection in use
 +  * **pop**: total population as per most recent population projection in use
  
 The workbook below shows some sample analysis. This workbook does a bit more than simple pivot tables and charts on the data but also computes new data using formulas. The workbook below shows some sample analysis. This workbook does a bit more than simple pivot tables and charts on the data but also computes new data using formulas.
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 ==== Flows ==== ==== Flows ====
 +
 +
 +=== Views warehouse.CohortNation, warehouse.CohortDistrict and warehouse.CohortSchool ===
 +
 +The primary views to produce flow ratios indicators. 
 +
 +<note important>Flows are more advanced indicators with slightly more advanced mathematics behind them then other ratios seen so far.</note>
 +
 +Each of these views produce the same data but with different disaggregations (i.e. down to school level, district level and nation wide and by gender). Each record will have the following data which must be used in various formulas to produce the final indicators. There is a bold emphasis on the most important ones to produce most flow indicators with enough precision. These flows use the reconstructed cohort methods and must have consistent collection of enrolments and repeaters for two consecutive years. Details about the columns names in this view are included below:
 +
 +  * **Enrol**: the enrolments (e.g. Grade 5 enrolments for 2018-19)
 +  * **Rep**: the repeaters (e.g. Grade 5 repeaters for 2018-19)
 +  * **RepNY**: the repeaters for the next school year (e.g. Grade 5 repeaters for 2019-20)
 +  * TroutNY: the transfers out for the next school year (e.g. Grade 5 transfers out for 2019-20)
 +  * **EnrolNYNextLevel**: the enrolments for the next school year into the next class level/grade (e.g. Grade 6 enrolments for 2019-20)
 +  * **RepNYNextLevel**: the repeaters for the next school year into the next class level/grade (e.g. Grade 6 repeaters for 2019-20)
 +  * TrinNYNextLevel: the transfers in for the next school year (e.g. Grade 6 transfers in for 2019-20)
 +
 +The formulas are either identical or mathematical equivalent to the ones in the UNESCO UIS Education Indicators
 +Technical guidelines.
 +
 +  * Promotion Rate = (EnrolNYNextLevel - RepNYNextLevel) / Enrol
 +  * Repetition Rate = RepNY / Enrol
 +  * Survival Rate (year on year; not to a particular year) = Promotion Rate / ( 1 - Repetition Rate)
 +  * Dropout Rate = 1 - (Promotion Rate + Repetition Rate)
 +  * Transition Rate (year on year) = (EnrolNYNextLevel - RepNYNextLevel) / Enrol
 +
 +A sample workbook showing how these many flow indicators can be calculated including some analysis is included below.
 +
 +{{ :user-manual-data-warehouse:flows-ratios.xlsx |}}
 +
 +
 +
 +
  
  
  
 ==== Teachers ==== ==== Teachers ====
 +
 +
 +=== Table warehouse.TeacherLocation ===
 +
 +The table warehouse.TeacherLocation sits on the transition between:
 +
 +  * teacher reporting derived from the School Surveys (i.e. PDF annual surveys, Excel Workbook); and
 +  * teacher reporting derived from Appointments, and teacher training records from the web UI (i.e. manual entry of records in UI).
 +
 +<note important>The tables Establishment and Teacher Appointments define the structure of the teaching establishment: i.e. the collection of teaching positions, and the teachers that are appointed to those positions.  This is where we expect the teachers to be. The Establishment and Appointment framework is not currently in use by most users but data is simply gathered using the survey method.</note> 
 +
 +<note important>The TeacherSurvey table holds the records of where teachers are reported to be by the School Survey. This is where teachers are. Ideally, TeacherSurvey functions as a verification of TeacherAppointments. We could check that teachers are where they are supposed to be and report exceptions. In simpler setups (all of them currently) only the surveys are used and not the Establishment/Appointment teacher planning tool.</note>
 +
 +Regardless of the setup, this table brings these two sets of data together. There is a record for each teacher for each year they were active. It contains the gender, DoB, age group of teacher, the school, role, source (i.e. an appointment or reported through survey), whether the teacher is qualified and certified as determined by any possible means, the education sector, the max ISCED level taught, which grades taught, and some other details.
 +
 +=== Tables/Views warehouse.TeacherJob* ===
 +
 +Tables containing data about the number of staff and their job title, staff type (i.e. teaching and non-teaching) and teacher type (i.e. regular, special ed.). They come in various disaggregations:
 +
 +  * warehouse.TeacherJobTable
 +  * warehouse.TeacherJobSchool
 +  * warehouse.TeacherJobDistrict
 +  * warehouse.TeacherJobAuthority
 +  * warehouse.TeacherJobAuthorityGovt
 +  * warehouse.TeacherJobRegion
 +  * warehouse.TeacherJobIsland
 +  * warehouse.TeacherJobNation
 +  * warehouse.TeacherJobSchoolType
 +
 +
 +=== Tables/Views warehouse.TeacherActivity* ===
 +
 +Tables containing data about the number of staff teaching at specific grades. They come with various disaggregations support.
 +
 +  * warehouse.TeacherActivityTable
 +  * warehouse.TeacherActivitySchool
 +  * warehouse.TeacherActivityDistrict
 +  * warehouse.TeacherActivityAuthority
 +  * warehouse.TeacherActivityAuthorityGovt
 +  * warehouse.TeacherActivityRegion
 +  * warehouse.TeacherActivityIsland
 +  * warehouse.TeacherActivityNation
 +  * warehouse.TeacherActivitySchoolType
 +
 +They are generally used to produce Pupil-Teacher Ratios (PTR) with higher accuracy. The PTR = Enrol / Teachers. The warehouse tables provide the following columns:
 +
 +  * Enrol: enrolments for the grade (and whatever other disggregation)
 +  * Staff: total teachers teaching at that grade (regardless of how much time in a day they teach there)
 +  * StaffW: teachers full time equivalent teaching at that grade
 +  * GradePTR: the PTR calculated without regards for full time equivalent
 +  * GradePTRW: more precise PTR calculated with StaffW (i.e. full time equivalent)
 +
 +A sample workbook on teacher data analysis is included below. 
 +
 +{{ :user-manual-data-warehouse:teachers.xlsx |}}
 +
 +
 +
 +
 +
 +
 +
 +
 +
 +
  
  
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 {{ :user-manual-data-warehouse:special-education-analysis.xlsx |}} {{ :user-manual-data-warehouse:special-education-analysis.xlsx |}}
 +
 +{{ :user-manual-data-warehouse:special-education-in-depth-analysis.xlsx |}}
  
 ==== School Accreditation ==== ==== School Accreditation ====
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 Same of warehouse.enrol except this table aggregates this data up to District, Authority, SchoolTypeCode and is used as the basis for higher level aggregations of any of these enrolment data items. Same of warehouse.enrol except this table aggregates this data up to District, Authority, SchoolTypeCode and is used as the basis for higher level aggregations of any of these enrolment data items.
 +
 +==== Teachers ====
 +
 +=== Table warehouse.TeacherQual ===
 +
 +Intermediate table to assist in calculation of Certified / Qualified. This table shows, for each teacher, the qualifications reported, and the first year of that report. It is assembled from both the School Surveys, and any named qualifications reported in the web UI.
 +
 +<note warning>You do not need to use this table directly.</note>
  
  
-==== Flows ==== 
  
  
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 <note important>This table is geared towards advanced data people.</note> <note important>This table is geared towards advanced data people.</note>
  
-Consolidates the overall result of inspections. Filter on InspectionType to restrict to accreditations+Consolidates the overall result of inspections with all the typical school disaggregations. Filter on InspectionType to restrict to specific inspections (e.g. School Accreditation, WASH, etc.)
  
 <note important>This table is useful for pivot tables, and crossfilters, allowing multiple dimensions to be manipulated interactively</note> <note important>This table is useful for pivot tables, and crossfilters, allowing multiple dimensions to be manipulated interactively</note>
emis_user_manual_data_warehouse.1599185997.txt.gz · Last modified: 2021/02/02 02:10 (external edit)