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| start [2024/11/13 03:30] – [How to add a new student track to TDSM] tdsmdavid | start [2024/11/27 20:41] (current) – tdsmdianne |
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| ====== OVERVIEW ====== | ====== OVERVIEW ====== |
| The Teacher Demand and Supply Model (TDSM) supports Jordan's Ministries of Education (MoE) and Higher Education and Scientific Research (MoHESR) to make data-driven decisions and prepare multi-year supply and demand projections for grade K-12 teachers of Jordanian students in the Kingdom's public schools. The model uses data entered into the Open Education Management Information System (OpenEMIS((OpenEMIS (https://www.openemis.org) is an open-source education management information system initiated by UNESCO and used by the Kingdom of Jordan to track its students and teachers.))) to calculate teacher surpluses and shortages in each school from 2016 to five years in the future, allowing policymakers to recognize trends and shifts, and incorporate those into their considerations for policies and incentives impacting teacher recruitment and retention. TDSM will support stakeholders across the education sector in their efforts to plan strategically; it will inform the MoE, *Civil Service Bureau (CSB)*, and university partners about where teachers are going to be needed and for which subjects. The TDSM workflow is depicted in the illustration below.{{:tdsm.png?800|}} | The Teacher Demand and Supply Model (TDSM) supports Jordan's Ministries of Education (MoE) and Higher Education and Scientific Research (MoHESR) to make data-driven decisions and prepare multi-year supply and demand projections for grade K-12 teachers of Jordanian students in the Kingdom's public schools. The model uses data entered into the Open Education Management Information System (OpenEMIS((OpenEMIS (https://www.openemis.org) is an open-source education management information system initiated by UNESCO and used by the Kingdom of Jordan to track its students and teachers.))) to calculate teacher surpluses and shortages in each school from 2016 to five years in the future, allowing policymakers to recognize trends and shifts, and incorporate those into their considerations for policies and incentives impacting teacher recruitment and retention. TDSM will support stakeholders across the education sector in their efforts to plan strategically; it will inform the MoE and university partners about where teachers are going to be needed and for which subjects. The TDSM workflow is depicted in the illustration below.{{:tdsm.png?800|}} |
| ====== USER GUIDE ====== | ====== USER GUIDE ====== |
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| Navigate to the [[start#how to visualize the data|TDSM front end]] to view the updated forecasts. | Navigate to the [[start#how to visualize the data|TDSM front end]] to view the updated forecasts. |
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| ===== How to archive a version ===== *NEED STEP TO UPDATE VERSION # AND VERSION MONTH YEAR | ===== How to archive a version ===== |
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| Inside the project folder is file called "archive.sh", this script will archive the old data for the project create a record for the archive in archive list. | Inside the project folder is file called "archive.sh", this script will archive the old data for the project create a record for the archive in archive list. |
| The weekly hours of required instruction for each student track are contained [[start#lookup tables|weekly_classes_per_specialization lookup table]]. To adjusted the required hours of instruction for a given student track, modify the values in this file. Leave the cells blank for specializations where no instruction is required. | The weekly hours of required instruction for each student track are contained [[start#lookup tables|weekly_classes_per_specialization lookup table]]. To adjusted the required hours of instruction for a given student track, modify the values in this file. Leave the cells blank for specializations where no instruction is required. |
| ===== How to add new OpenEMIS locations to TDSM ===== | ===== How to add new OpenEMIS locations to TDSM ===== |
| Each directorate is uniquely identified in OpenEMIS by an area_id. A list of all OpenEMIS area_ids can be found in the [[start#stagins tables|areas.csv]] table, which is updated each time the TDSM data are refreshed. Additionally, each school in OpenEMIS is given a more granular administrative_area_id. Administrative_area_ids are nested within area_ids. Because OpenEMIS does not have unique identifiers for liwas, each known administrative_area_id+area_id pair has been mapped to a liwa in the [[start#lookup tables|administrative_area_crosswalk.csv]] file. If an administrative_area_id is not mapped in this table, any school with that administrative_area_id will not be included in TDSM. All unmaped schools are listed in the [[start#data files|unmapped_schoools.csv]] file. To add a new administrative_area_id+area_id pair to TDSM, add a new row the administrative_area_crosswalk.csv file, filling in a value for each column. The. next time the TDSM data are refreshed, the newly mapped administrative_area_ids will then be included. | Each directorate is uniquely identified in OpenEMIS by an area_id. A list of all OpenEMIS area_ids can be found in the [[start#staging tables|areas.csv]] table, which is updated each time the TDSM data are refreshed. Additionally, each school in OpenEMIS is given a more granular administrative_area_id. Administrative_area_ids are nested within area_ids. Because OpenEMIS does not have unique identifiers for liwas, each known administrative_area_id+area_id pair has been mapped to a liwa in the [[start#lookup tables|administrative_area_crosswalk.csv]] file. If an administrative_area_id is not mapped in this table, any school with that administrative_area_id will not be included in TDSM. All unmaped schools are listed in the [[start#data files|unmapped_schoools.csv]] file. To add a new administrative_area_id+area_id pair to TDSM, add a new row the administrative_area_crosswalk.csv file, filling in a value for each column. The next time the TDSM data are refreshed, the newly mapped administrative_area_ids will then be included. |
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| ===== How to refine the forecasting models ===== | ===== How to refine the forecasting models ===== |
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| =====Version history===== | =====Version history===== |
| TDSM version 1.0 was deployed February 2022. Version 2.0 is in final testing and scheduled to deploy on... | TDSM version 1.0 was deployed February 2022. Version 2.0 is scheduled to deploy in 2024. |
| | ^ TDSM 1.0 ^ TDSM 2.0 ^ | | ^ TDSM 1.0 ^ TDSM 2.0 ^ |
| ^ Data feed | Files manually generated from OpenEMIS and sent to TDSM | Automatically pulls from OpenEMIS via its API | | ^ Data feed | Files manually generated from OpenEMIS and sent to TDSM | Automatically pulls from OpenEMIS via its API | |
| The following tables are generated by TDSM each time it loads new data from OpenEMIS Jordan. These tables are persisted so that TDSM can be rerun without having to reload data from OpenEMIS. | The following tables are generated by TDSM each time it loads new data from OpenEMIS Jordan. These tables are persisted so that TDSM can be rerun without having to reload data from OpenEMIS. |
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| * **areas.csv**: List of all areas. | * **areas.csv**: List of all areas. [[https://drive.google.com/file/d/1E1ekGoBVmVX_zc6QIR1NaTVs6WPLn2u-/view?usp=drive_link|View file]] |
| * **institutions.csv**: List of all schools. | * **institutions.csv**: List of all schools. |
| * **subjects.csv**: List of all existing subjects and the teacher specialization they map to, Also includes the OpenEMIS ID of each subject and the OpenEMIS ID of the academic period during which the subject was first taught. [[https://drive.google.com/file/d/1aqtnm9tTF45D0RGscx_NGeYda7Oaiy9C/view?usp=drive_link|View file]] | * **subjects.csv**: List of all existing subjects and the teacher specialization they map to, Also includes the OpenEMIS ID of each subject and the OpenEMIS ID of the academic period during which the subject was first taught. [[https://drive.google.com/file/d/1aqtnm9tTF45D0RGscx_NGeYda7Oaiy9C/view?usp=drive_link|View file]] |
| * **lkp_specialization.txt**: Lookup table for specialization values. | * **lkp_specialization.txt**: Lookup table for specialization values. |
| * **lkp_school.txt**: Lookup table for school details. | * **lkp_school.txt**: Lookup table for school details. |
| * **unmapped_schools.csv**: Lists all schools from OpenEMIS that were not successfully mapped to a liwa. These schools are not included in the TDSM data or projections. To include these schools in TDSM, see [[start#How to add new OpenEMIS locations to TDSM | * **unmapped_schools.csv**: Lists all schools from OpenEMIS that were not successfully mapped to a liwa. [[https://drive.google.com/file/d/1l9HkEeOcJzrlDJ54blFjfNtZUZAxNxuy/view?usp=drive_link|View file]] These schools are not included in the TDSM data or projections. To include these schools in TDSM, see [[start#How to add new OpenEMIS locations to TDSM |
| |How to add new OpenEMIS locations to TDSM | |How to add new OpenEMIS locations to TDSM |
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