The starting point for the creation of an event-history database is the source registers for official statistics. Within education the three files mentioned above (enrolments, graduates and attainment) are arranged for the purpose of making them comparable over time. New data are merged with old data and classification variables are compared one by one. All changes for each classification variable is assigned with dates and coded as gains or loss records by a set of predefined rules. Only new information is interesting in the database. Each course, discipline or education that a person starts is registered with start and end dates.
Several predefined variables are integrated in NUDB to better extract indicators on the throughput of students. Two types of variables exist: Variables to be set once, and unable to change over time (e.g. Year when first time registered in upper secondary and tertiary education, year when first time graduate from compulsory, upper secondary and different stages of tertiary education and number of semesters in education before a first-time completion of a level) and variables based on gains, changes and losses (=event-history variables) in the individual's period of education (e.g. Number of semesters in education at any level and number of semesters within a specific program, to determine whether the completed degree is within a normal timeframe. Some educational programs are very modular and cannot be defined as beyond or within a normal timeframe).
The National Education Data Model is a conceptual but detailed representation of the education information domain. The Education Data Model strives to be a shared understanding among all education stakeholders as to what information needs to be collected and managed at the local level in order to enable effective instruction of students and superior leadership of schools.
The Education Data Model can be used by educators, vendors, and researchers to understand the information required for teaching, learning, and administrative systems. The Education Data Model answers questions such as:
What data do schools need to collect and manage in order to meet the educational needs of their students?
What information is needed to effectively manage education organizations such that teaching and learning is successful?
it consist of different files. Some are defined as course files where educational activities are organized by start and ending dates – others are not. Variable names (labels) and definitions are available in Norwegian only.
– Joint demographic and educational attainment file, annual updates
– All courses and subjects, monthly updates
– Student's main course of study, monthly updates
– Fixed personal variables
– Grades from completing compulsory education
– Diplomas and certificates from upper secondary education
Grades by field of education in upper secondary education
Low Literacy Rate
The absence of adequate school infrastructure like improper facilities and inefficient teaching staff is one of the main factors affecting literacy in India. There is a shortage of 6lakh classrooms to accommodate all the students in 2006-2007. In addition, there is no proper sanitation in most schools. The study of 188 government-run primary schools in central and northern India revealed that 59% of the schools had no drinking water facility and 89% no toilets. A Public Report On Basic Education (PROBE) team did surveys and reported that India had very poor infrastructure in 1999 and a 25% rate of teachers being absent from school on any particular day in 2005. In 600,000 villages and multiplying urban slum habitats, ‘free and compulsory education’ is the basic literacy instruction dispensed by barely qualified ‘Para...