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218. Based on the outcomes and consensus at the workshop, data collection
instruments should be revised. Schedule and approach of collection should be
reconciled to avoid unnecessary duplication efforts.

Usage of appropriate and standardised definitions and terminologies in education
statistics
Findings

219. Some terminologies for education statistical indicators are different from
international standards. Different terms and terminologies are used in collection and
interpretation of data; at the same time, in some cases the same generic term is used to
describe the two different sets of data. This causes misunderstanding and confusion
and sometimes ushers in unnecessary debate. For example, defining repeaters,
comparing school attendance rates and enrolment rates, comparing different enrolment
rates from different sources without taking into account the nature and coverage of data.

220. During the diagnostic mission, it was found out that most of the staff were not
aware and have little knowledge about ISCED which is critical for the international
comparison statistics on education. It may be due to lack of documentation and the
previous staff who was in charge of this subject did not inform or explain well to the
others.

Recommendations

221. Both ministries should develop a guideline for standard definitions and
methods of calculation for education indicators which should be agreeable to all
concerned partners at the national level. These standard definitions and methodologies
should be used for all occasions of data collection and analysis concerning education
statistics in Bangladesh.

222. With the support of UNESCO, MOET should develop an ISCED mapping for
Bangladesh Education System which covers all types and forms of institutions from all
education sub-sectors.

Computerised EMIS

Findings
223. Currently, MIS unit of DPE under MOPME and MIS unit of BANBEIS under
MOE have the computerised EMIS systems to gather and produce the statistics for all
levels of education except for some portion of tertiary education and professional
education.

224. Data processing programmes have only rudimentary functions and do not
optimally take advantage of most useful functions of computerised data processing.
There are only a few or no built-in data validation functions in the programmes to check
the consistency and reliability of the data.

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