School Management : An Integrated Approach
August 2007

School Management : An Integrated Approach

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The quality of  learning that students experience at schools is of strategic importance for both their future and of the nation. To promote literacy, various schemes have been proposed by the Government of India such as Sarva Shiksha Abhiyaan, Mid-day meals, etc. Effective implementation of these schemes require concrete data periodically, based upon certain parameters, that enables authorities to assess the efficacy of the scheme in a transparent manner. Data management in schools is done primarily on paper. Monitoring of resource utilisation in schools is difficult as it is paper-based and has many bureaucratic hurdles. With growing number of students, data management is becoming laborious and error prone for both school as well as government authorities. It is arduous to gather, analyse and disseminate such vast amount of information through manual 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” 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An ICT based solution will drastically improve school administrative operations(management of students, teachers, funds, operations scheduling etc.) by reducing latency in data management and makes the operations less error prone.

The article proposes a model that will provide a common platform for school management, which also support interfaces in regional languages. This has profound implications for stakeholders at higher levels as they wish to manage schools using a common interface.

The school system in India is composed of primary, upper primary and high schools. A collection of schools forms a cluster, clusters form a block, blocks are under a district, districts form a state and states form the country. Such hierarchy is useful in decentralizing the management of schools. Operational information of a school flows from lower levels to higher levels. In the process the information can be analysed before being presented to higher level for appropriate decision-making.

Schools are the fundamental units of operation within this education system. Data is generated through operational activities in a school. This data needs to be managed and school operational activities need to be monitored. The School administration consists of number of components. They are

The model for management of school information and integration of schools across the country follows a layered approach. Each layer is dependent upon the layer below it. The lowermost layer defines a model which captures data to be managed and the uppermost layer provides interaction with the system.

It has the following three layers

1. Data Model
This model uses a classification based  n school types. Each school type has
its own operational requirements. The e  equirements can be modeled as a set of
attributes and a administration hierarchy. This model is itself multi-layered. Alayer is defined for each policy making bdy. This model defines the hierarchy  eeded for data entry and data management. Data providers at various levels provide data stamped with their signature. The data will be validated and again stamped by the signature of auditing authority as it moves from one level to another. This verified data will be made available to all stakeholders. This model also defines the security attributes for managing the data and provides support for feedback from various levels. The feedback and the actions taken upon are again visible to all the stakeholders ensuring transparency in the process. Data centers The data related to managed attributes from the data model is stored at data centers. A data center can be located  anywhere in the administration hierarchy where infrastructure is available. A level can manage its own data locally and this local data is not accessible to higher levels. But a lower level is required to furnish data as defined by the data  model to the upper level. Such a system allows a level to manage its local data  effectively & efficiently, yet maintain required relationship with  higher levels. Software Support The data model defines attributes for which values are stored in data centers. In current times, when the volume of information is large, paper based
processes are ineffectual. Software support is essential for speedy data recording, on-demand data retrieval, data analysis and report generation. The software should provide following facilities. 1.Data collection interfaces These interfaces are used to record data into the system related to school operations. They should be usable across wide array of devices  such as PCs, PDAs and kiosks, maximising the reach to a large section of the country. Data analysis tools These tools help decision makers at various levels in taking timely and effective decision that is based both on empirical data and current trends. These tools should provide facilities for identifying patterns, trends and relationships. Reporting Tools Reports are required by  administrative authorities from time-to-time and they can be  generated in different formats(tabular, graphs, charts, multiple document formats, etc.) based on  specified parameters. Also software should support the following characteristics: Support for diverse technologies  In a country, as large as India, there are many prejudices and tastes that  differ from region-to-region. They use different technologies for data management. All these different  usages must be combined under one umbrella such that they can interact with each other in standard manner. Localised user interfaces  India is a country with many official

Usage Scenario
The first step is the definition of datamodel. Existing classification of school types i.e., primary, upper primary and high school will be used in this data model. School policies are determined  t two levels. National policies for education such as fund allocation are made by national authorities. Further state bodies make various regulatory policies for schools under it. National  authorities require minimal information about every school in the country for tracking progress, fund utilisation, compliance with schemes, etc. The required information can be categorised into profile and operational information. Profile
information of a school consists of its identification information, location, primary contact, etc. Operational  nformation consists of admissions, drop-outs, compliance with center defined educational schemes, etc.  Each state has its own educational policies in addition to those defined by the center. Additional data needs to be managed at the state-level giving information about all the school operations under it. For e.g., a state might decide to maintain information about history, library facility, play grounds, number of toilets, laboratories, etc. as part of school profile. A state has requirement to manage operational information about schools as determined by state policies. These information include staff and student attendance, class schedules, exam records, fund management, etc. Schools, clusters and blocks are located largely in rural areas. Hence, it is impractical to have data centers 3. located at these nodes as there will be inadequate infrastructure and skilled human resources. Data centers can be located in each district, but this would give rise to multiple points at which, management of data extensions resulting due to new or updated policies, becomes difficult. Also data backups at so many locations is a point of concern. As schools follow policies made by state, the common data center can be hosted at state level. This does not have issues identified at district level above.  he required software will be installed at a state-level facility. This arrangement handles the issues of software maintenance which would be otherwise difficult if hosted at multitude of places. The server-side software will be Web Service based. Web Services is a  technology for developing distributed systems that provides interoperability using web-based standards. This is achieved through the means of standardised interfaces. These interfaces are used by clients to interact with web services. If different states support server-side web services having the same standardised interface across the country, it provides a common platform for uniform data recording format, data retrieval operations and data analysis. The other main advantage is that a given existing application can be exposed as a Web Service allowing different states to use different technologies for data management as per the available expertise and requirement and still be able to integrate with each other. Data regarding school operations is recorded using interfaces provided by this software application. Whenever data is recorded in the system, it is time-stamped and also carries data  rovider’s signature. This will ensure accountability at all levels for all operations. Further a data record, once entered into the system, cannot be modified by anyone. If required, erroneous data record can be corrected and a new version of the existing record will be added along with the reasons for the manipulation. This effectively maintains the complete log of any  instance of an operational activity. The complete history of any data  record is visible to anyone ensuring transparency in the operations. Data  records have a life cycle in this system. They are introduced in the system by a data provider. Next these records pass  through an audit process and the results are recorded which are again stamped with signature of auditing authority. Once a data record successfully passes through the audit, then only it becomes available for analysis. Data analysis which is based on verified datarecords results in accurate decision making.A streamlined process is required to achieve global data access, transparency and efficient operations. The model proposed above inherently provides these characteristics at all levels to all stakeholders within the education system. Usage of technologies such as Web Services for implementing this  model can help realise the goals and reap the fruits in the shortest span of  time. This model provides accurate data gathering and hence enables concerned authorities to take correct decisions. Transparency of the system reduces chances of malpractices and also conforms to the Right To  Information act.

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