UDISE Registration

NIEPA professionals with the involvement of other experts designed and developed the core data capture formats. Accordingly, NIEPA designed software for implementation at the district level and provided the required technical and professional support to DPEP districts. a primary version of the software named as District data system for Education (DISE) was released during the center of 1995. The district-level professionals were assisted within the establishment of EMIS units, trained within the data collection, computerization and analysis using DISE. a serious emphasis was on user orientation within the use of educational and allied data for planning, management, monitoring and feedback on the DPEP interventions.

In addition to the DISE, many additional mechanisms for data validation and internal control of faculty statistics were also introduced. First, a 5-10% validation check is undertaken altogether districts immediately after data collection. Second, the software provides for several consistency and validation checks. Third, a national survey is conducted every 2-3 years to determine the standard and reliability of DISE data. The second post enumeration validation survey is ongoing now. Fourth, the reverse flow of knowledge has been strengthened to make sure transparency and dissemination of knowledge up to the varsity level. These sorts of validation measures and transparency of knowledge have resulted in considerable improvement within the quality of knowledge collection and reporting.

The DISE has also an inbuilt provision for normal feedback. Besides the annual review workshops, the primary major review of the DISE was undertaken during 1997-98 and was further followed by an in-depth review during 2000-01 leading to DISE2001. The capacity building program for implementing the new data capture formats and therefore the software (DISE2001) is undergoing since the last one year. the continual improvisation is important to scale back data redundancy and fine-tune the info collection formats and therefore the corresponding software with the emerging needs. Therefore major reviews with a 3-4 year gap haven’t only provided the required inputs for updating the EMIS approach but also ensured continuous involvement of the states and stakeholders in monitoring and evaluation.

• Presently the EMIS is confined to elementary stage covering eight years of education.
• The varsity and village level data is updated annually with 30th September because of the reference date.
• The concepts and definitions of educational variables are standardized at the national level. All states/districts follow equivalent definitions.
• The software provides facilities for college code generation which is exclusive and according to various administrative levels.
• The software captures two sorts of information base: at the village and therefore the school level.
• Village-level data comprises variables associated with the access to educational facilities of varied types, identification of habitation without access to primary and upper primary schools supported distance norms, inventory of all kinds of educational institutions including recognized and unrecognized schools within the village, selected data on the amount, enrolment and teachers/instructors in NFE/EGS and alternative schools, pre-primary education including Anganwadis and Balwadis. Data on age-specific population and out of faculty children generated through household surveys form a part of the village data.
• The DCF defines core data on school location, management, rural-urban, enrolment, buildings, equipment, teachers, incentives, medium of instruction, age-grade matrix, children with disabilities, examination results and student flows.
• An outsized number of standardized reports on school-related variables and performance indicators aggregated at the cluster, block and district level are generated by the software.
• The school summary report for every school is generated for sharing with the school/VEC. the varsity summary report contains key data on school and a summary of indicators that are compared with the cluster, block and therefore the district averages. The transparency and sharing of knowledge at school/village level have led to considerable improvement within the quality of reporting and also provides an opportunity for the stakeholder to understand the status of their school.
• Detailed database on individual teachers, Para-teachers and community teachers and their profile including data on in-service training received would be available under DISE2001.
• Eliminates the probabilities of knowledge manipulation at various levels. the varsity remains liable for the correctness of the info supplied. The software provides for internal consistency and exceptional cases listing.
• The states/districts have the flexibility of adding supplementary variables depending upon their specific requirements on year to year basis. No additional software for computerization and analysis of state/district-specific data is required.
• The state/districts can develop their own large databases using ‘designer’ module and integrate a spread of school/cluster/block-level data with DISE2001. The software handles multiple databases at various levels and includes many tools of knowledge analysis and presentation.
• Simple to use dynamic graphics facility to reinforce the presentation of varied sorts of graphs and data. This feature is out there for the data also like the generated variables.
• Multi-user and modular system of software design for better management and security of databases. The software uses ‘Oracle’ because of the backend tool for management. The software works on both personal Oracle also as Oracle for Workgroups.
• Predefined queries on standard aspects like school list, list of villages without primary and upper primary schools, single teacher schools, schools without buildings, schools with high PTR, etc., Users can define and save other queries.
• User-defined dynamic query on many variables to facilitate day-to-day management.
• Facilities for basic statistical analysis including generation of latent variables and their analysis.
• The ‘report viewer’ module provides the facilities for sharing of ordinary reports with multiple users without full software installation. This provides for the sharing of electronic reports on performance and other indicators.
• Data are often exported to several other formats for further analysis.
• The info from the district to state level is transferred following multiple modes including the transfer through the Internet.
• Online support built into the software. the web site provides considerable scope for sharing and dissemination of project related information. Regular chat/counseling sessions are held using electronic media. Efforts are being made to develop a network of districts and state-level EMIS and supply interactivity using teleconferencing and other modern technologies. The work on this aspect is ongoing.