DEVELOPMENT AND HARMONIZATION OF EFFECTIVE … · very difficult to get comprehensive and exhaustive statistics. The development of an effective Higher Education Management Information

DEVELOPMENT AND HARMONIZATION OF EFFECTIVE STATISTICAL NORMS AND STANDARDS FOR AFRICAN REGION

Higher Education Management Information Systems Norms

and Standards Benchmarking Framework for African Region

HEMIS Norms & Standards Benchmarking Framework for African Region

1

Table of Contents ABBREVIATIONS & ACRONYMS ............................................................................................................... 3

ACKNOWLEDGEMENTS ............................................................................................................................ 4

PREFACE ..................................................................................................................................................... 5

DEFINITION OF STATISTICAL TERMS .......................................................................................................... 7

1. INTRODUCTION ...................................................................................................................................... 9

METHODOLOGY .................................................................................................................................... 9

Remit for the review ............................................................................................................................ 10

Scope and approach to review ....................................................................................................... 10

INSTITUTIONS’ EXPERIENCES, INTERESTS AND NEEDS ........................................................................ 11

Findings of available Benchmarking Framework ........................................................................... 11

Overview of available benchmarking resources - Market data sources ................................... 11

A STRATEGY-CONTINGENT APPROACH TO HEMIS BENCHMARKING ............................................ 14

PROPOSAL HIGHER EDUCATION MANAGEMENT INFORMATION SYSTEMS BENCHMARKING

FRAMEWORK ........................................................................................................................................ 16

2. PURPOSE OF THE NORMS AND STANDARDS .................................................................................... 16

3. QUALITY OF STATISTICS ....................................................................................................................... 17

4. USING THE ASSESSMENT FRAMEWORK. ............................................................................................. 18

Steps to follow in scoring country performance: ........................................................................... 18

The Process of Engagement ............................................................................................................. 19

5. LIMITATIONS OF THE ASSESSMENT FRAMEWORK .............................................................................. 20

6. THE HEMIS NORMS AND STANDARDS ASSESSMENT FRAMEWORK ................................................. 20

A. Policy and Legal Framework ........................................................................................................ 20

NORM 1. MANDATE FOR DATA COLLECTION FOR THE EDUCATION SECTOR ............................. 20

NORM 2: QUALITY COMMITMENT ..................................................................................................... 25

NORM 3: STATISTICAL CONFIDENTIALITY .......................................................................................... 27

NORM 4: ACCOUNTABILITY TERMS OF THE PRODUCTION AND PUBLICATION OF STATISTICAL

REPORTS ................................................................................................................................................ 29

NORM 5: IMPARTIALITY AND OBJECTIVITY ........................................................................................ 31

NORM 6: REGISTRATION OF INSTITUTIONS ........................................................................................ 34

NORM 7: REGISTRATION OF LEARNERS ............................................................................................ 36

B. Resources Availability and Utilisation ........................................................................................... 38

NORM 8: ADEQUATE RESOURCES ..................................................................................................... 38


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NORM 9: COST EFFECTIVENESS .......................................................................................................... 42

C. Statistical Processes ....................................................................................................................... 44

NORM 10: SOUND METHODOLOGY AND APPROPRIATE STATISTICAL PROCEDURES ................. 44

NORM 11: NON-EXCESSIVE BURDEN ON RESPONDENTS ............................................................... 48

D. Education Information Reporting ................................................................................................ 50

NORM 12: RELEVANCE ....................................................................................................................... 50

NORM 13: ACCURACY AND RELIABILITY .......................................................................................... 54

NORM 14: TIMELINESS AND PUNCTUALITY ....................................................................................... 57

NORM 15: COHERENCE, CONSISTENCY, COMPARABILITY AND INTERPRETABILITY .................... 59

NORM 16: ACCESSIBILITY AND CLARITY ........................................................................................... 62

NORM 17: COMPREHENSIVENESS ..................................................................................................... 65

CONCLUSION .......................................................................................................................................... 67

ANNEXURE A: SCORING MATRIX ........................................................................................................... 68

ANNEXURE B: EXTERNAL PEER RATING TEAM AND COUNTRY SCORING MATRIX ............................ 70

REFERENCES ............................................................................................................................................. 72


3

ABBREVIATIONS & ACRONYMS AAU Association of African Universities

AfDB African Development Bank

ADEA Association for the Development of Education in Africa

AU African Union

CIEFFA African Union International Centre for Girls’ and Women’s Education

in Africa

CSO Central Statistics Office

DQAF Diagnostic Quality Assessment Framework

ENSAT

ECOWAS

EMIS Norms and Standards Assessment Team

Economic Community of West African States

GIS Geographic Information Systems

HEMIS Higher Education Management Information Systems

ICT Information and Communication Technology

ISCED International Standard Classification system of Education

MDGs United Nations Millennium Development Goals

MoE Ministry of Education

MoU Memorandum of Understanding

NCTE National Council for Tertiary Education

NESIS National Education Statistical Information Systems

NFE Non Formal Education

NSO National Statistics Office

OECD Organization for Economic Cooperation and Development

REC Regional Economic Community

Stats SA Statistics South Africa

TVET Technical and Vocational Education and Training

UIS UNESCO Institute for Statistics

UN United Nations

WGEMPS ADEA Working Group in Education Management and Policy Support

WGNFE ADEA Working Group on Non Formal Education


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ACKNOWLEDGEMENTS

This Framework adopted from the lessons learned in the Norms and Standard Assessment

Framework for EMIS at the basic and secondary education sub-sector was produced on behalf

of the African Region by a Restricted Technical Committee (RTC) made up of experts in Higher

Education Management Information Systems (HEMIS). Expert from Burkina Faso, Ghana,

Senegal, Mauritius, and from Universities in Ghana and Chad, a team from the ADEA Working

Group on Education Management and Policy Support (WGEMPS) and Working Group on Higher

Education, Association of African Universities (AAU) under the supervision of Makha

NDAO(Coordinator ADEA-WGEMPS) and Nodumo DHLAMINI( AAU-Director - ICT Services &

Knowledge Management) in collaboration with Youssouf Ario Maiga(ADEA-WGEMPS Program

Manager), Kwesi Acquah Sam(AAU&ADEA-WGHE) and Alpha Bah(ADEA-WGEMPS resource

person). We would like to recognize the valuable contributions of experts from partner

organizations and Universities, notably, Dr. Yohannes Woldetensae, Senior Education Expert from

African Union Commission, Mrs Rachel Ogbe, Principal Programme Officer Education, ECOWAS

Commission and Dr. David Blaise OSSENE, Expert Education et Culture, ECCAS Commissions and

Prof. Mohammed Salifu, Executive Secretary of Ghana National Council for Tertiary Education,

Ghana . In addition we would like to express our gratitude to the HEMIS Technical Team from

Universities led by Dr. Regina Gyampoh-Vidogah, Director, ICT Services, University of Cape

Coast, Ghana and Jacob Akunor, Head, ICT, National Council for Tertiary Education for their

value contributions in preparation of this framework.

We would also like to thank the following “HEMIS experts” for their contributions

Mr. Vedanand Bhurosah, Assistant Director, Ministry of Education and Human Resources,

Tertiary Education and Scientific Research, Mauritius

Pr. Babacar GUEYE, Directeur général de l'Enseignement supérieur, Sénégal

Léonard SAWADOGO, Expert international en SIGE, Burkina Faso

Koulnodji Marcellin Ngombaye, Point Focal de la Direction des Études de la Statistique et

de Système d'Information(DESSI) du ministère de l'enseignement supérieur à l'université

de Moundou, Tchad

Edward Dogbey, Statistician, Ministry of Education, Ghana

Patrick Sammy Nkum, Data Officer, National Council for Tertiary Education, Ghana

Nii Adotei Abrahams, Head, Corporate Affairs, National Council for Tertiary Education

Emmanuel Afful, Head, Software Development, Kwame Nkrumah University of Science

and Technology, Ghana

Dr. Ibrahim Mohammed, Director of Research, University for Professional Studies, Accra,

Ghana

Mr. Thomas Bright, University of Mines and Technology, Ghana

Dr. John Effah, Head, Institutional Research, University of Ghana

Ruth Bunmi Odufala, Business Development Officer, AAU

Makha Ndao

ADEA-WGEMPS Coordinator


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PREFACE

The availability of a comprehensive and relevant data and statistics on Higher Education is

central to the effective delivery of the higher education sub sector in African. Quality data is

critical for planning, monitoring, to ensure accountability which is an essential element in

strengthening governance, leadership and management of higher education institutions and

the education sector as a whole.

Most countries in Africa are faced with numerous challenges in the collection, compilation and

analysis of statistical data. Higher education is one of education sub sectors in Africa where it’s

very difficult to get comprehensive and exhaustive statistics.

The development of an effective Higher Education Management Information Systems (HEMIS)

is still at the infancy stage in many countries. As a result, there is a huge data gap and

information to monitor and report progress of African Higher Education. According to UIS report

in 2016, only 2 countries in Sub-Saharan Africa submitted the HE questionnaire in 2015.

In some instances, the challenge is inadequate institutional capacity in relation to sustainable

infrastructure and human resources for an effective HEMIS. Consequently data coverage for the

list of all higher education institutions (both public and private) continues to be challenge. In

other instances, the concern is the structural arrangements for the management of education

characterized by the absence of a benchmarking tool such as the Norms and Standards

Assessment Framework (NSAF) for the management of education information in the higher

education sub sector Experience has shown that when the NSAF is utilize at the basic and

secondary education sub sector – EMIS coverage increased exponentially and the data gap

has reduced significantly.

At the institutional level, most tertiary and universities do not possess sound data collection

processes and the structure to support the components of a comprehensive information

management system which comply with international standards and guidelines. There barely

exist EMIS structure at the institutional level, no comparable indicators each has their own

specific tool and data collection and processing instruments as well as standards of practice.

Timeliness and punctuality in annual statistics has been a challenge no guidelines on frequency

and release dates of statistics are set. The issue of coding should be sorted out for easy

comparability of data as Universities in Africa have their codes for Universities etc., while other

institutions have their own codes.

The main purpose of this Norms and standards is to have a set of criteria and measures for

advocating best practice and benchmarking Universities in the African capable of being able

to produce relevant, accurate, timely and comprehensive education statistics and information.

This will assist Universities in sustaining a comprehensive and appropriate Education

Management information systems in harmony with international and regional systems and

practices. There are four thematic areas, namely: Policy and Legal Frameworks; Resource

Availability and Utilization; Statistical Processes; and Education Information Reporting.


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The goal is to strengthen African Higher Education systems by changing the role African

universities in the area of Higher Education Management Information Systems (HEMIS). The sub

sector will be revived using appropriate HEMIS Norms and Standards Assessment Framework to

ascertain status quo om around the four thematic areas above and identify recommendations

for the way forward including effective partnership with WGHE and AAU to reduce the ‘data

blanks’ in the sub sector.

Fundamental to this is to reposition universities in each country to drive HEMIS by addressing the

perennial challenges i.e.; a) low capacity for HEMIS skills, b) production and sustaining the

necessary infrastructure (databases & Apps) and c) reduce staff turnover by student-internship

or apprenticeship schemes to create employment.

Professor Etienne Ehouan EHILE

Secretary General AAU


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DEFINITION OF STATISTICAL TERMS

1. Administrative Data- The set of units and data derived from an administrative source.

2. Administrative sources – The organizational units within a country that are responsible

for implementing an administrative regulation (or group of regulations), for which the

corresponding register of units and the transactions are viewed as a certified source of

information and statistical data.

3. Aggregated data – The result of transforming unit level data into quantitative measures

for a set of characteristics of a population.

4. Benchmark- A recognized standard, or a reference point, that forms the basis for

assessment or comparison.

5. Data Dictionary – Refers to centralized repository of information about data such as

meaning, relationships to other data, origin, usage, and format standardized concepts,

definitions and classifications used by Ministries in the production of their data.

6. Data providers – Refers to all bodies and agencies that produce statistics. These include

education and training institutions, households, enterprises, administrations and other

respondents.

7. Coherence - The degree of validity, accuracy, usability and integrity of data,

successfully brought together with other data within a broad analytical framework and

over time.

8. Education and training institutions – Refers to schools, colleges, universities, centres or

any formal and non-formal education and training provider that occupies an institution

and provides a recognized education programme.

9. EMIS – Refers to a System for collection, processing, analysis, publication, dissemination,

and rendering of Information services for the Management of Educational resources

and services.

10. Guidelines – Directions or principles used in the development, maintenance and

application of rules. They may or may not be mandatory, but are provided as an aid to

interpretation and use of rules.

11. Imputation – Refers to the process of identifying missing data, generally used for the

correction of partial non-response from a census or a survey, to adjust or modify the

data accordingly.

12. Individuality – A single person or institution.

13. Learner – Refers to any pupil or student or person enrolled in an education and training

programme.

14. Metadata – Information on the underlying concepts, definitions, and classifications used,

the methodology of data collection and processing, and indicators or measures of

accuracy of the statistical information.


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15. Ministry of Education - The singular term “Ministry of Education” is used synonymously

with its plural form “Ministries of Education” to include all those government Ministries

responsible for the various levels of education and training in a country.

16. Protocols - A set of guidelines or rules.

17. Preliminary data - Results that have not been verified sufficiently to be published.

18. Scope- Coverage or sphere of what is to be observed. It is the total membership or

population of a defined set of people objects or events.

19. Statistical authority – Shall mean, at national level, the national or central statistical office

(CSO, NSDS, or Statistical authority) and other statistical bodies in charge of producing

and disseminating African statistics according to a statistical law.

20. Statistical Value Chain – Refers to the statistical process from the source of data to the

final statistical output. For example, it concerns the collection of information in school

records, the compilation of an annual census survey, the collection and verification at

lower levels of governance (circuit, district, regional, provincial), the inputting of the

data, the data cleaning and imputation and the generation of statistical tables and

reports.

21. Secondary data – Refers to data collected by someone other than the user. Examples

are data obtained from research, studies and surveys produced outside of the Ministry

of Education.

22. Special needs – Refers to learners under difficult conditions that are vulnerable,

marginalized and/or with disability.

23. Structures – Refers to various sub-units of the Ministry responsible for education

administration by area of specialization and geographic distribution.

24. Sub-Sectors - Pre-primary education, primary education, secondary education,

Technical and Vocational Education, Teachers’ training education, Non-formal

education, Higher and tertiary education.

25. Validity - Correctness and reasonableness of data - findings truly represent the

phenomenon you are claiming to measure.

26. Verification - The process whereby data accuracy and inconsistencies are checked.

http://en.wikipedia.org/wiki/Guideline


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1. INTRODUCTION

A key challenge facing institutions in the African Region’s is inability to report on its human

resource development achievements and challenges is information gaps .This is a problem of

inadequate data coverage of all education institutions (both public and private) and all sub-

sectors in the education system. In other cases, it is the structural arrangements for the

management of education in the absence of a policy and norms and standards for the

management of education information. Some countries have more than one Ministry

responsible for the delivery and management of education and therefore each Ministry

collects its own data and information. Issues of duplication, varying definitions and poor

coordination of sector wide data arise and thereby affect the quality and availability of

education statistics. These issues are compounded when comparisons are made across

countries. As a result few Member States are reporting comprehensively on all the required

global education indicators. This tends to lead to a number of problems in monitoring and

evaluating the performance of an education and training sector in countries and across the

region.

This report presents benchmarking in the African Region Education sector, commissioned from

Technical Consulting Group of Education Management Information System (EMIS) and

Statistical as part of "Benchmarking to improve efficiency". The report presents a snapshot of

current benchmarking activities and experiences in the Region Higher Education sectors and

offers a benchmarking proposals to meeting educational institutions' needs in the Region,

Africa and beyond.

The purpose of this benchmarking is to develop institutions' understanding of the conditions

and standards for international competitive success in their chosen business missions, and to

enable them to take informed decisions about the activities needed to further their strategic

goals. The insights gained through this process must then be translated into effective

management actions and change programmes, designed to move the institution forward in

terms of the maturity framework described earlier.

This benchmarking framework is structured as follows:

The key messages arising from the teams’ consultations with selected institutions

on their needs and experiences in international benchmarking.

Summary of findings of available benchmarking sources.

Proposals Framework for Higher Education management information systems

benchmarking

Conclusions and recommendations.

METHODOLOGY

The peer review methodology used involved the following:

User consultation through face to face interviews and focused discussions;

Questionnaire administration;

Presentations;

Review of documentation, instruments, policies, and reports;


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Remit for the review An initial Educational Management Information Systems (EMIS) Status manual on

benchmarking activities and resources focused on individual member countries in improving

production of education statistics within institutional operations for planning, financing and

developments of education framework.

Particular areas of interest for the review were:

The uses of international benchmarking in relation to academic performance

and non-academic activities

Approaches taken by policy and mission groups, and known activities by

government bodies and agencies

Examples of international benchmarking best practice in a small sample of

universities with an assessment of impacts and benefits

Review of available resources, including international university league tables

Assessment of quality, accuracy and timeliness of the data

Based on this analysis this benchmarking framework propose a possible model or models for

international benchmarking by the African Region’s institutions - An assessment of the feasibility

of implementing the proposed model and the possible restrictions and constraints –

Recommendations for Higher Education and the Statistical Agencies sector more broadly, for

developments that might optimize the use of international benchmarking to improve

institutional performance.

Scope and approach to review

This benchmarking for Higher Education institutions can be interpreted in various widely differing

ways:

Comparisons of the overall international standing or ranking of institutions against data

compilations in various international 'league tables'

Data-based comparisons of international institutions operations and performance,

including data collected by international of universities

Process-based comparisons of institutional management approaches, intended to

identify and share good practices with regard to recruitment and other aspects of

internationalization

Environmental and other issues-based comparisons of developments and approaches

in different countries

Market intelligence on patterns of demand and competitor information from different

countries

Each of these interpretations of benchmarking are very different in kind, and in their potential

relevance and usefulness for institutions. Benchmarking is not an end in itself, and is useful

inasmuch as it can inform better strategic or managerial plans and decisions. It’s was therefore

felt it important to start the review with an understanding of the institutional planning needs that

would potentially be served through benchmarking, and then to assess the available resources

and their value in that context. The approach thus proceeded through:


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Needs assessment: based on consultation with a selection of institutions, identification of the

critical needs and uses of international benchmark information among Higher Education

Statistics Agency (HESA)‘s member institutions

Review of available resources

Desk research was conducted to identify and assess the available resources for benchmarking

and assessment of gaps and unmet needs. The output of this stage is a conspectus of available

international benchmarking resources.

INSTITUTIONS’ EXPERIENCES, INTERESTS AND NEEDS

While almost all Universities and institutions have declared strategic commitments to growing

internationalization, the scope of this commitment and the progress of related plans and

performance vary greatly across the African Regional Sectors. While some institutions are

focused simply on growing their student recruitment numbers, others are well advanced

towards becoming fully international in all area of their operations. This impression was

confirmed in our workshop held in Accra form 29-30 June 2017 with a number of institutions.

Universities recognize that they are increasingly competing with both domestic and

international rivals on all of these criteria, but appear to use comparisons with their competitors

mainly as a basis for calibrating their own targets. We interviewed staff from a sample of

Universities, representing a cross-section of institutional types, to understand their current

priorities, activities and experiences of Management information systems benchmarking. We

also held less structured discussions with a wider group of institutions who attended HEMIS

benchmarking workshops.

Findings of available Benchmarking Framework

Overall, It is found that while most institutions collect and review comparative data on their

institutional performance, few use them systematically in their planning or management

processes, and those that do, do so in very specific areas, either detailed analyses of research

performance or to assess the perceptions of their students. All the institutions that attended the

workshop were keen to stress that, while benchmarking and statistics can be important, there

has to be purpose to them. Thus ‘changing the mindset’ was the phrase used by one institution

to make this point.

Overview of available benchmarking resources - Market data sources

There is a wealth of published data and analyses of comparisons across the Educational

Management Information system, most of it published in the public domain along with some

proprietary commercial products. This section presents a summary overview and commentary

on the major sources, including some still in development.


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TITLE/COVERAGE/COMPARISON DESCRIPTION

AU&ADEA Outlook on

Education report for COMEDAF

ADEA produced on behalf of AUC Department of Human Resources,

Science and Technology (HRST) the Outlook on Education report for

each REC for COMEDAF. These report cover the indicators for

Gender and culture, EMIS, Teacher development, Higher and tertiary

education, TVET, Curriculum development, teaching and learning

materials, Quality management, Early childhood development and

Cross cutting agendas-HIV and AIDS, Quality Assurance and

Qualification Frameworks

UNESCO Institute for Statistics

Indicators Coverage: Global

(Country-wide)

Comparison: Market data

UNESCO releases education statistics on a country-wide basis.

Indicators include gross enrolment rate, distribution of students,

percentage of female students, gross completion rate, Inbound and

outbound mobility rate, Number of students in tertiary education per

10,000 inhabitants, and Percentage of tertiary graduates in

education.

Global Higher Education

Rankings Affordability &

Accessibility in Comparative

Perspective Coverage: 17

countries (Countrywide)

Comparison: Market data

Global Higher Education Rankings report studies the affordability and

accessibility of higher education across the participating nations.

Six indicators of affordability are reported on and these: - Education

Costs as a % of Ability to Pay (ATP) - Total Costs as a % of ATP - Net

Costs as a % of ATP - Net Cost After Tax Expenditure as a % of ATP -

Out-of-Pocket Costs as a % of ATP - Out-of-pocket Costs After Tax

Expenditures as a % of ATP Median income levels per country are

used as a metric of ATP.

The study uses four indicators of accessibility: - Participation rates -

Attainment rates - The Educational Equity Index (EEI) - Gender Parity

index

Overview of available benchmarking resources - Market Intelligence Sources

British Council Education

Market Intelligence (EMI)

Coverage:

Global Comparison: Market

intelligence

The British Council's Education Market Intelligence provides higher

education statistics, information on universities, market profiling,

country profiling, international student data, quarterly updates on

developments, and other education market intelligence insights.

Higher Education International

Unit Coverage: Global

Comparison: Market

Intelligence

The UK International Unit (IEU) formed on 1 August 2010 by merging

the UK HE International Unit and the UK HE Europe Unit is a central

observatory of international and European issues and inform all

higher education institutions and other stakeholders through its

research, publications and websites and coordinates strategic

engagement between UK and international stakeholders.

In representing the sector as a whole, the IEU works closely with

higher education institutions and organizations, including the British

Council, UK Department for Business, Innovation and Skills, UK Joint

International Unit, UKTI, Universities Scotland, the Scottish

Government, Higher Education Wales and the Welsh Government.

Academic Analytics business

intelligence reports Coverage:

US institutions

Comparison: Market

intelligence

Academic Analytics created the Faculty Scholarly Productivity Index

which ranks doctoral programmes in the US. The index measures the

scholarly productivity of faculties based on: - Publications - Citations

- Financial - Honorary awards. Academic Analytics is now focusing

on business intelligence for university administrators apart from the

Faculty Scholarly Productivity Index.


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Institutional Process Comparisons

Association of Common wealth

universities (ACU)

Benchmarking Programme

Coverage: 16 universities from

Australia, Canada, Hong Kong,

New Zealand, the African

continent, the United Kingdom

and other parts of the

Commonwealth Comparison:

Institutional process

comparisons

The Association of Commonwealth Universities maintains a higher

education benchmarking programme through a series of

collaborative reviews of selected business processes, through an

annual round of focused reviews. Universities share information on

their activities in the selected themes, regarding: - Approach -

Application - Outcome

Through these benchmarking exchanges, information about good

practices are also identified and shared, using the structure and

criteria of the European Quality Excellence Framework.

Whole University Rankings

QS World Universities Ranking

Coverage: Global (University

rankings)

Comparison: Whole university

ranking

QS World university rankings is one of the leading global university

rankings. It ranks universities on the basis of parameters such as: -

Academic reputation - Citations - International students -

International faculty - Employer review

Academic Ranking of World

Universities (ARWU) Coverage:

Global (University rankings)


ranking

ARWU ranks worldwide universities using objective indicators such as:

- Number of alumni that won Nobel prizes and Field, Number of highly

cited researchers selected by Thomson Scientific, Number of articles

published in journals of Nature and Science - Number of articles

indexed in Science Citation Index - Expanded and Social Sciences

Citation Index - Per capita performance with respect to the size of

an institution. It is considered as one of the most influential ranking of

world universities.

CHE Excellence Rankings

Coverage: European

Institutions (University rankings)


ranking.

The Centre of Higher Education ranks a selected group of European

institution in subjects such as biology, chemistry, mathematics,

physics, political science, psychology and economics.

The center also publishes 'CHE University Ranking' (for higher

education institutions in German speaking countries) and 'CHE

Research Ranking' (higher education institutions are analyzed using

a range of metrics from which users can extract the comparisons

most relevant to their own interests

Webometrics Ranking of World

Universities Coverage: Global

(University rankings)


ranking

The Webometrics ranking measures the overall volume, visibility and

impact of web pages published by universities such as referred

papers, conference contributions, thesis, reports, digital libraries,

databases as well as general information on the institution.

Indicators used for the ranking methodology include: - Size or the

number of pages recovered from search engines like Google,

yahoo, Live Search and Exalead. - Visibility - Rich Files - Scholars

2016 World University Ranking

Coverage: Global (University

rankings)


ranking

The World Universities Ranking by High Impact Universities ranks the

top 500 universities worldwide on the basis of the research impact of

the universities measured by: - Research publications - Citations


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SIR World Report Coverage:



ranking

SIR World Ranking identifies best research focused universities across

the globe. The rankings are based on the research work carried out

by universities and involves evaluation criteria such as: - Research

performance - Publications in high quality journals - Citations

RatER Global University Ranking

of World Universities Coverage:



ranking

The Global University Ranking is the first international study for RatER

and ranks more than 400 well-known global universities. These

universities are analyzed on the basis of attributes such as: -

Academic performance - Research performance - Expertise of

faculty - Availability of resources of the universities - Level of socially

significant activities of the graduates of universities - Level of

international activities of the universities.

The Performance Ranking of

Scientific Papers for World

Universities Coverage: Global

(University rankings)


ranking

This annual report from Higher Education Evaluation and

Accreditation Council of Taiwan (HEEACT) ranks universities across

the globe as per: - Research productivity (number of articles) -

Research impact (number of citations) - Research excellence

(number of highly cited papers, number of articles in high impact

journals)

Times Higher Education

Ranking Coverage: Global

(University rankings 2016/2017)


ranking

Times Higher Education rankings are based on a selected set of

parameters. Weight is given to each parameter and universities are

scored on respective performance in each attribute. Overall

weighted score is calculated to arrive at the final score for each

university. It is one of the largest global surveys for higher education

universities. Parameters used for the evaluation process are: -

Learning environment - Research - Citations - Industry Income -

International mix

A STRATEGY-CONTINGENT APPROACH TO HEMIS BENCHMARKING

The strong thrust of this report, backed by the experiences of institutions is that benchmarking,

whether based on domestic or international comparisons, is useful only inasmuch as it informs

the relevant business decisions for improving strategic performance. It follows from this view that

institutional approaches to benchmarking should be contingent on the current objectives,

status and priorities of individual institutions. This suggests a four-stage, strategy-contingent

benchmarking model, on the lines illustrated here and discussed below:

Where are we now?

What do we need to know?

What can we learn?

What information is available?

i. Where are we now?

Using the framework described above, institutions should undertake an honest assessment of

the current status of their strategies and determine their priorities for moving to the next levels.

ii. What do we need to collect?

This analysis will identify any gaps in the information or sector intelligence available to the

institution that might be addressed through a benchmarking exercise. For example, an institution

with aspirations to improve its standing in international research rankings might wish to


15

understand the particular metrics and levels of performance in them that differentiate the

institutions currently above them in the relevant tables.

iii. What information is available?

Having identified specific information needs through the first two stages, institutions should

identify the most appropriate available resources. In many cases the relevant data will be more

specific and more granular than that provided in general benchmarking resources or data

comparisons, which is the reason that the more sophisticated users of benchmarking resources

found greatest value in specialized proprietary sources such as i-graduate's international

student barometer or Academic Analytics and similar research performance databases. It may

well be that data being developed through national source data will be more useful than

'processed' cross-country comparisons. Subject to this comparison, identification and analysis

of comparative data in institutions' particular areas of interest should serve to indicate their

relative strengths and weaknesses against chosen comparators.

iv. Learning from other Benchmarking

In most instances, apparent differences and pointers towards differential performance do little

more than highlight areas for further investigation. Differences in reported data or approaches

between peer institutions may simply reflect differences in their respective contexts or history,

which are not helpful in taking practical lessons from the comparisons. Nonetheless, even such

constrained comparisons can be valuable in helping institutions to adopt an external

perspective on their performance, as it may be seen by potential students, staff recruits or

research funders. And a structured and results-oriented approach will usually give institutions a

better understanding of their competitive position and the conditions for success, even if their

routes to improvement will always be bespoke to their own history and ambitions.

This standard approach to institutional benchmarking should adopt approaches that identify

the comparative information most relevant to their particular needs, internationalization

strategies and the maturity of their operations. HE institutions in African Region should consider

what competitor information and market intelligence is most relevant to their particular

institutionalization goals and their next stages of international corporate developments.

Institutions should then select the most appropriate benchmark components for their particular

needs, and incorporate these into their planning and performance management systems.

v. Benefits of collaboration

While many institutions are understandably cautious about collaborative benchmarking

activities, which they fear might require them to share sensitive proprietary information, they

should perhaps consider making an exception for Africa engagement with some of the richer

international initiatives being developed to provide more reliable and granular comparative

information. While it would be prohibitively expensive and time-consuming for individual

institutions to engage in the design and development of these initiatives, there may be benefits

from a collaborative approach channeled through a single African representative, such as

ADEA and AAU.

We recommend that detailed consideration should be given to the scope and potential

benefits from collaborative sector engagement in new benchmarking resources, possibly

channeled through ADEA or another national sector body.


16

PROPOSAL HIGHER EDUCATION MANAGEMENT INFORMATION SYSTEMS

BENCHMARKING FRAMEWORK

The HEMIS Norms and Standards Code of Good Practice has four areas of focus:

Policy and Legal Frameworks;

Resource Availability and Utilization;

Statistical Processes; and

Education Information Reporting

The first two areas of focus – Policy and Legal frameworks, and Resource Availability and

Utilization – are the prerequisites or fundamental conditions that impact on the environment in

which HEMIS operates. It’s important to ensure that the institutional and legal environment, the

availability and use of human, financial and technological resources support a well-functioning

HEMIS. The following two focus areas target the methodology and processes that need to be in

place to produce quality statistics and information, in order to verify the appropriateness and

timeliness of the products and outputs produced by the process. Each area has a set of Norms

that Universities should commit to abide throughout the entire process of the production of

education statistics. A set of Standards of Good Practice for each of the Norms provides a

reference for reviewing the implementation of the code.

2. PURPOSE OF THE NORMS AND STANDARDS

The main purpose of the HEMIS Norms and Standards is to have a set of criteria and measures

for advocating best practice and benchmarking countries capabilities in being able to

produce relevant, accurate, timely and comprehensive education statistics and information.

Adopting these Norms and Standards ensures universities will have sustainable, comprehensive

and appropriate education management information systems in harmony with international

and regional systems and practices.

This Norms and Standards Assessment Framework can be used for:

Self-assessment by producers of education statistics.

Advocacy tool in debates for ensuring that the necessary HEMIS resources and

infrastructure are available to Universities responsible for HEMIS education and

training.

Reviews performed by AUC in assessing regional capacity in the development and

coordination of education policies and their consistent reinforcement of/by HEMIS,

as well as country compliance with the framework.

AUC and REC accreditation for quality and acceptable statistics.


17

3. QUALITY OF STATISTICS

Underpinning the Norms and standards is a principle of the Quality of Statistics which is defined

as ‘fitness for use’. The Quality of Statistics has eight dimensions; namely, relevance, accuracy,

timeliness, accessibility, interpretability, coherence, methodological soundness and integrity.

Five of these eight quality dimensions are also covered in the Data Quality Assessment

Framework of the International Monetary Fund (IMF) and the UNESCO Institute of Statistics (UIS).

The relevance of statistical information reflects the degree to which it meets the real needs of

users. It is concerned with whether the available information sheds light on the issues of most

importance to users.

The accuracy of statistical information is the degree to which the output correctly describes

the phenomena it was designed to measure.

The timeliness of statistical information refers to the delay between the point to which the

information pertains, and the date on which the information becomes available. It considers

the regularity and punctuality of the release of information.

The accessibility of statistical information refers to the ease with which it can be obtained. The

cost of the information may also be an aspect of accessibility for some users.

The interpretability of statistical information refers to the ease with which users can understand

statistical information through the provision of metadata. This information normally includes the

underlying concepts, definitions and classifications used the methodology of data collection

and processing, and indicators or measures of the accuracy of the statistical information.

The coherence of statistical information reflects the degree to which it can be successfully

brought together with other statistical information within a broad analytical framework and

over time. The use of standard concepts, classifications and target populations promotes

coherence, as does the use of common methodology across surveys.

Methodological soundness refers to the application of international, national or peer-agreed

standards, guidelines, and practices to produce statistical outputs. Application of such

standards fosters national and international comparability.

The integrity of statistical information refers to the values and related practices that maintain

users’ confidence in the Ministry producing statistics and ultimately in the statistical product.

These dimensions of “statistical quality” are overlapping and interrelated. Failure to comply

with any one dimension will impair the usefulness of the information.


18

4. USING THE ASSESSMENT FRAMEWORK.

A key strategy in modern education management is the measuring that includes relevant and

targeted planning to support decision-making and efficient investment in programmes. This

also acts as an early warning measure of system dysfunction as well as benchmarks against

which progress is assessed.

The assessment framework was developed in a manner that makes it possible for Universities self-

assessment and peer ranking. Each of the 17 Norms includes a number of components.

Components are high-level descriptors of a number of Standards. The degree of

implementation of a Standard associated with a Norm is measured on a 4 point assessment

scale. The ideal Standard is embedded in “Quality Statistics” (Level 4).

Steps to follow in scoring country performance:

- Review the Norm and the associated Standard; and then assess which level (Level 4 to

1) closely approximates the Standard characterized by your EMIS systems.

- In the associated column, score a 4 for a system whose implementation of a standard

is characterized by Level 4, similarly score a 3 for Level 3 etc.

- List evidence or provide justification for the scoring. Collect evidence if there is any for

later review by the external Norms and Standards Assessment Team.

- The Standards are independent of each other making it possible for an EMIS system to

be assessed as Quality Level 1 for one standard and to have Quality Level 3 for the next

standard.

- An average score can be calculated for each Norm so as to give an indication of which

areas need further improvement. Insert the average score on the Table in Annexure A

(see page 31) - Average the score for each of the following focus areas:

A. Policy and Legal Framework.

B. Resource Availability and Utilization

C. Statistical Process

D. Education Information Reporting

The overall ranking of an EMIS system is obtained by averaging all the scores for all of the100

standards. The overall country ranking of the EMIS system will be based as indicated on the

table below. An overall assessment of greater than 3.3 indicates that this country has an

HEMIS system which produces quality statistics. Similarly, an overall average score of

between 2.6 and 3.3 classifies the country as having acceptable statistics. An average score

below 2.6 indicates the country has questionable or poor statistics.


19

Assessment Range

Quality Statistics 3.4 to 4.0

Acceptable Statistics 2.6 to 3.3

Questionable Statistics 1.8 to 2.5

Poor Statistics 1 to 1.7

The Process of Engagement

The steps of engaging in this process are as follows:

1. The University writes a formal application to AAU and ADEA expressing their wish

to benchmark this EMIS based on Norms and Standards Assessment framework.

AAU and ADEA will formally respond outlining the steps and conditions for an

assessment

2. The University creates an internal national Review Team which will undertake the

assessments and produce an Assessment Report. This should not take more than

two weeks.

3. The University make it self-assessment and share the report with AAU and ADEA

4. AAU and ADEA appoints an EMIS Norms and Standards Assessment Team (ENSAT).

They will selected experts mainly from the universities supported with AAU, ADEA

and Representative from REC and AUC to conduct the benchmarking exercise.

5. The ENSA Team independently assesses the EMIS system with the evidence

provided by the national team.

6. The university's Team and the external Team engage in joint discussions and reach

a consensus on the scoring of standards. In cases where the country assessment

and the peer assessment differ significantly and no consensus on scoring is

reached the two scores shall be averaged with the country score constituting 40%

and the ENSA Team 60%.

7. The Peer Team develop the final assessment report with scores, findings and

recommendations.

8. This is shared with the senior officials of the Ministry for their concurrence on

measures for improved data quality.

9. The university's Team and the external Team will develop an Action Plan for the

recommendations implementation. The proposed activities should be budgeted

with operational time lines.

10. The publication of the assessment findings is subject to confidentiality agreements

11. A date for the next assessment is agreed upon.

12. The HEMIS system will have an overall ranking of Quality Level 4 or Quality Level 3.

ADEA and AAU in collaboration with the Universities and with budget by

Universities should support this exercise

13. A date for the next assessment is agreed upon.

14. The publication of the assessment findings is subject to confidentiality agreements.


20

5. LIMITATIONS OF THE ASSESSMENT FRAMEWORK

The information provided in this report can be used in analyzing national status of HE as well as

institutional status of Universities, campuses in different colleges, schools and faculties. The data

can also be helpful in analyzing the universities in terms of the numbers and the sizes of colleges,

campuses, faculties, gender; student teacher ratio. Also correlation between different courses,

enrolment, faculty, distribution of institutions and student-teacher enrolment ratio etc. can be

checked. Data availability on time remained a limiting factor. Technology is another factor.

Inability to follow academic calendar on the part of major Universities, inability to comply with

schedules for admissions. Conducting examination and bringing out results has immense

implications on many aspects including data availability on time. This limitation is low because

with innovate technologies being deployed across the African Continent, a one stop shop for

all students, finance and staff information need to be digitize instead of the manual statistical

data books. That will mean a robust state of the art constant internet supply that will drive this

digital agenda

6. THE HEMIS NORMS AND STANDARDS ASSESSMENT FRAMEWORK

In these Norms and Standards, the singular term “Ministry of Education” is used synonymously

with its plural form “Ministries of Education” to include all those government Ministries responsible

for the Higher and Tertiary levels of education and training in a country. To recap, These Norms

and Standards apply to all levels of Higher and Tertiary education including Universities,

Polytechnics and Colleges that offers degrees with the recognition that the Ministry managing

the Higher and Tertiary Education level has the primary responsibility for coordinating education

and training statistics for the sector. These norms and standards must be read and understood

taking account of the definitions proposed in Section 5.

A. Policy and Legal Framework Policy and legal frameworks governing higher and tertiary education statistics have a significant

influence on the effectiveness and credibility of Ministries of Education to produce and

disseminate education statistics. The relevant issues concern a mandate for data collection

from all education and training of Higher and Tertiary institutions and bodies, clarity on roles

and responsibilities, registration of students and institutions, commitment to quality, reporting

accountability, statistical confidentiality, impartiality and objectivity. All University education

statistical policy frameworks come under the umbrella of national statistical policy.

NORM 1. MANDATE FOR DATA COLLECTION FOR THE EDUCATION SECTOR

Ministries of Education/Universities/institutions must have a clear legal mandate to collect

information from all education and training institutions and bodies, both public and private, for

educational statistical purposes.


21

Ass

ess

me

nt

Lev

els

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the

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ality

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tist

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mm

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In 1

985,

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aw

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).

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.

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ap

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of

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le

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1.1

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Co

mp

on

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Leg

al m

an

da

te

1 STATISTICAL SERVICE LAW - 1985 (PNDCL 135) http://laws.ghanalegal.com/acts/id/560/statistical-service-law. Assessed 13/10/17

European Statistics Code of Practice - revised edition 2011ISBN: 978-92-79-21679-4

http://laws.ghanalegal.com/acts/id/560/statistical-service-law.%20Assessed%2013/10/17


22

Info

rma

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rin

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sho

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atic

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d

mo

ve

ac

ross

su

b-s

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va

rio

us

dire

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rie

s (H

R,

Fin

an

ce

), f

low

rig

ht

ba

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to t

he

sc

ho

ols

as

we

ll a

s

info

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tio

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ha

rin

g w

ith

oth

er

Min

istr

ies,

ag

en

cie

s

an

d d

ep

art

me

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re is

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pla

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ative

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for

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la

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ot

stip

ula

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dis

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for

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n-

co

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d t

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rate

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en

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str

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to c

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ss a

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on

ly f

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diffe

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b-

sec

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of

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nd

tra

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g

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na

tio

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l

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n a

llow

s

the

Min

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f

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n t

o f

ully

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ce

ss b

asi

c

ad

min

istr

ative

da

ta f

or

sta

tist

ica

l

pu

rpo

ses.

.

The

la

w p

rovid

es

dis

cip

lina

ry

ac

tio

ns

in t

he

ca

se o

f

no

nc

om

plia

nc

e

an

d a

lwa

ys

ap

plie

d

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Min

istr

y o

f

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uc

atio

n/U

niv

er

sitie

s/In

stitu

tio

n

ha

d a

str

ate

gy

for

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llec

tin

g,

pro

ce

ssin

g a

nd

inte

gra

tin

g d

ata

fro

m s

ub

-se

cto

rs

of

ed

uc

atio

n a

nd

tra

inin

g a

nd

fro

m

rele

va

nt

inst

itu

tio

ns

an

d

bo

die

s u

nd

er

oth

er

min

istr

ies

an

d t

he

civ

il

soc

iety

.

Leg

isla

tio

n o

n

the

ac

ce

ssib

ility

of

ba

sic

ad

min

istr

ative

da

ta f

or

sta

tist

ica

l

pu

rpo

ses

Exis

ten

ce

of

dis

cip

lina

ry

me

asu

res

in

inst

an

ce

s o

f

vio

latio

ns

of

the

la

w a

nd

ap

plic

atio

n o

f

dis

cip

lina

ry

me

asu

res

in

ca

ses

of

no

nc

om

plia

n

ce

Str

ate

gy f

or

co

llec

tin

g,

pro

ce

ssin

g,

dis

sem

ina

tin

g

an

d

inte

gra

tin

g

da

ta.

1.1

.4

1.1

.5

1.2

.1

2 Institutions view the process as voluntary and response rates are low as there are no consequences for noncompliance.


23

(Mo

U b

etw

ee

n t

he

sta

tist

ics

de

pa

rtm

en

t o

f th

e

Min

istr

y o

f

Ed

uc

atio

n a

nd

Tra

inin

g a

nd

th

e

Na

tio

na

l Sta

tist

ica

l

Off

ice

)

The

sh

arin

g o

f

info

rma

tio

n a

cro

ss

ed

uc

atio

n a

nd

tra

inin

g s

ub

-

sec

tors

,

go

ve

rnm

en

t

ag

en

cie

s a

nd

th

e

civ

il so

cie

ty d

oe

s

no

t m

ee

t

de

ad

line

s.

The

re is

no

co

llab

ora

tio

n

be

twe

en

th

e

Min

istr

y o

f

Ed

uc

atio

n a

nd

th

e

Na

tio

na

l Sta

tist

ica

l

Off

ice

.

EM

IS m

issi

on

s a

nd

att

rib

utio

ns

are

no

t

de

fin

ed

in

th

e

org

an

ic la

w o

f th

e

Min

istr

y o

f

Ed

uc

atio

n a

nd

Tra

inin

g.

The

Pro

ce

du

re

Ma

nu

al d

oe

s n

ot

exis

t.

So

me

little

info

rma

tio

n

sha

rin

g a

cro

ss

ed

uc

atio

n a

nd

tra

inin

g s

ub

-

sec

tors

,

go

ve

rnm

en

t

ag

en

cie

s a

nd

the

civ

il so

cie

ty.

The

re is

sim

ple

co

llab

ora

tio

n

be

twe

en

th

e

Min

istr

y o

f

Ed

uc

atio

n a

nd

the

Na

tio

na

l

Sta

tist

ica

l O

ffic

e

tha

t h

as

no

t

be

en

fo

rma

lize

d

by a

n o

ffic

ial

do

cu

me

nt.

EM

IS m

issi

on

s a

nd

att

rib

utio

ns

are

va

gu

ely

de

fin

ed

(im

pre

cis

e)

in t

he

org

an

ic la

w o

f

the

Min

istr

y o

f

Ed

uc

atio

n a

nd

Tra

inin

g.

The

Pro

ce

du

re

Ma

nu

al e

xis

ts.

Tim

ely

sh

arin

g o

f

info

rma

tio

n

ac

ross

ed

uc

atio

n a

nd

tra

inin

g s

ub

-

sec

tors

,

go

ve

rnm

en

t

ag

en

cie

s a

nd

the

civ

il so

cie

ty.

The

re is

a s

em

i-

fun

ctio

na

l M

oU

be

twe

en

th

e

Na

tio

na

l

Sta

tist

ica

l O

ffic

e

an

d t

he

Min

istr

y

of

Ed

uc

atio

n.

EM

IS m

issi

on

s

an

d a

ttrib

utio

ns

are

pa

rtia

lly

de

fin

ed

in

th

e

org

an

ic la

w o

f

the

Min

istr

y o

f

Ed

uc

atio

n a

nd

Tra

inin

g.

Pro

ce

du

re

Ma

nu

al Exis

t th

at

cle

arly d

efin

es

role

s a

nd

resp

on

sib

ilitie

s

Tim

ely

sh

arin

g o

f

info

rma

tio

n

ac

ross

ed

uc

atio

n

an

d t

rain

ing

sub

sec

tors

,

go

ve

rnm

en

t

ag

en

cie

s a

nd

the

civ

il so

cie

ty.

The

re is

a

fun

ctio

na

l M

oU

be

twe

en

th

e

sta

tist

ica

l se

rvic

es

of

the

Min

istr

y o

f

Ed

uc

atio

n a

nd

the

Na

tio

na

l

Sta

tist

ica

l O

ffic

e

on

all

sta

tist

ica

l

ne

ed

s3.

EM

IS m

issi

on

s a

nd

att

rib

utio

ns

are

cle

arly d

efin

ed

in

the

org

an

ic la

w

of

the

Min

istr

y o

f

Ed

uc

atio

n a

nd

Tra

inin

g.

Pro

ce

du

re

Ma

nu

al Exis

t th

at

cle

arly d

efin

es

role

s a

nd

resp

on

sib

ilitie

s o

f

ed

uc

atio

n a

nd

tra

inin

g

inst

itu

tio

ns

an

d s

tru

ctu

res

in

the

sta

tist

ica

l

va

lue

ch

ain

(co

nc

ep

tio

n

of

inst

rum

en

ts,

co

llec

tio

n,

co

mp

ilatio

n,

dis

trib

utio

n a

nd

sha

rin

g o

f

ed

uc

atio

na

l

info

rma

tio

n)

Tim

elin

ess

of

info

rma

tio

n

sha

rin

g a

cro

ss

ed

uc

atio

n

an

d t

rain

ing

sub

sec

tors

,

go

ve

rnm

en

t

ag

en

cie

s a

nd

the

civ

il

soc

iety

.

Mo

U b

etw

ee

n

Min

istr

y o

f

Ed

uc

atio

n

an

d t

he

Na

tio

na

l

Sta

tist

ics

Off

ice

.

Ma

nd

ate

of

the

EM

IS u

nit

with

in t

he

Min

istr

y o

f

Ed

uc

atio

n

an

d T

rain

ing

.

Exis

ten

ce

of

a

Pro

ce

du

re

Ma

nu

al w

ith

in

EM

IS

stru

ctu

res

1.2

.2

1.2

.3

1.2

.4

1.2

.5

3 The MoU can be with the Central Statistics Office or any other National Statistical Authority


24

To b

e m

erg

ed

with

1.2

.9

The

ma

nu

al is

no

t

use

d in

pra

ctic

e.

NO

RM

AV

ER

AG

E

The

ma

nu

al is

rare

ly u

sed

in

pra

ctic

e.

The

ma

nu

al is

oft

en

use

d in

pra

ctic

e.

The

ma

nu

al is

wid

ely

use

d in

pra

ctic

e.

Use

of

the

Pro

ce

du

re

Ma

nu

al.

1.2

.6


25

NORM 2: QUALITY COMMITMENT

The Ministries of Education/Universities/Institution commit themselves to work and cooperate

according to the norms fixed in the quality declaration of its national statistical systems and in

other international statistical frameworks.


26

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

The

re is

no

fra

me

wo

rk t

o

gu

ide

th

e M

inis

try

/Un

ive

rsitie

s/In

stitu

ti

on

on

ho

w t

o

pro

mo

te a

nd

en

sure

qu

alit

y.

The

re is

no

ou

tlin

ed

pro

ce

ss

(ve

rific

atio

n,

va

lida

tio

n, e

tc.)

to

mo

nito

r q

ua

lity o

f

da

ta c

olle

ctio

n,

pro

ce

ssin

g, a

nd

dis

sem

ina

tio

n o

f

sta

tist

ics.

Th

ere

is

no

qu

alit

y c

on

tro

l

at

all.

NO

RM

AV

ER

AG

E

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

Exis

ten

ce

of

a

fra

me

wo

rk b

ut

do

no

t c

lea

rly

spe

cify t

he

pro

ce

du

res

to b

e

un

de

rta

ke

n b

y

the

Min

istr

y o

f

Ed

uc

atio

n/U

niv

er

sitie

s/In

stitu

tio

n

The

re a

re n

o

pro

ce

sse

s

(Ve

rific

atio

n,

va

lida

tio

n, e

tc.)

To m

on

ito

r a

nd

en

sure

th

e

qu

alit

y o

f d

ata

co

llec

tio

n,

pro

ce

ssin

g, a

nd

dis

sem

ina

tio

n o

f

sta

tist

ics.

Th

ou

gh

ran

do

m c

he

cks

co

uld

be

ma

de

fro

m t

ime

to

tim

e.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

Exis

ten

ce

of

a

fra

me

wo

rk

cle

arly

spe

cifyin

g t

he

pro

ce

du

res

to

be

un

de

rta

ke

n

by t

he

Min

istr

y o

f

Ed

uc

atio

n

/Un

ive

rsitie

s/In

stit

utio

n t

o p

rom

ote

an

d e

nsu

re

qu

alit

y in

sta

tist

ica

l va

lue

ch

ain

, h

ow

eve

r

no

t ta

kin

g in

to

ac

co

un

t

na

tio

na

l a

nd

inte

rna

tio

na

l

qu

alit

y

sta

nd

ard

s.

Pro

ce

sse

s a

re in

pla

ce

(ve

rific

atio

n,

Va

lida

tio

n, e

tc.)

To m

on

ito

r a

nd

en

sure

th

e

qu

alit

y o

f d

ata

co

llec

tio

n,

pro

ce

ssin

g, a

nd

dis

sem

ina

tio

n o

f

sta

tist

ics.

Th

ese

pro

ce

sse

s a

re

oft

en

ad

he

red

.

Qu

ality

Sta

tist

ics

Lev

el 4

Exis

ten

ce

of

a

po

licy f

ram

ew

ork

cle

arly s

pe

cifyin

g

the

pro

ce

du

res

to b

e u

nd

ert

ake

n

by t

he

Min

istr

y o

f

Ed

uc

atio

n/U

niv

er

sitie

s/In

stitu

tio

n t

o

pro

mo

te a

nd

en

sure

qu

alit

y in

the

sta

tist

ica

l

va

lue

ch

ain

,

takin

g in

to

ac

co

un

t n

atio

na

l

an

d in

tern

atio

na

l

qu

alit

y s

tan

da

rds.

Pro

ce

sse

s a

re in

pla

ce

(ve

rific

atio

n,

va

lida

tio

n, e

tc.)

to m

on

ito

r a

nd

en

sure

th

e

qu

alit

y o

f th

e

da

ta c

olle

ctio

n,

pro

ce

ssin

g, a

nd

dis

sem

ina

tio

n o

f

sta

tist

ics.

Th

ese

pro

ce

sse

s a

re

fully

ad

he

red

to

.4

Sta

nd

ard

s

Po

licy a

nd

pro

ce

du

res

to

en

sure

qu

alit

y.

Pro

ce

sse

s to

mo

nito

r a

nd

en

sure

da

ta

qu

alit

y.

2.1

.1

2.1

.2

Co

mp

on

en

ts

Po

lic

y a

nd

Pro

ce

du

res

to

en

sure

qu

ality

sta

tist

ics.

4 Results are compared to those from other surveys and there are checks to ensure statistical data is consistent over time.


27

NORM 3: STATISTICAL CONFIDENTIALITY

The Ministry of Education/Universities/Institutions guarantees the privacy of data providers’

identification, the confidentiality of the information they provide and its use for statistical

purposes only.


28

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

Ind

ivid

ua

l d

ata

co

nfid

en

tia

lity is

no

t

Me

ntio

ne

d

an

yw

he

re in

th

e

po

licy d

oc

um

en

t.

No

pro

toc

ols

in

pla

ce

th

at

ap

ply

to

exte

rna

l u

sers

ac

ce

ssin

g

sta

tist

ica

l d

ata

.

No

eff

ort

s a

re

ma

de

to

sa

feg

ua

rd

the

co

nfid

en

tia

lity

of

ind

ivid

ua

l d

ata

.

NO

RM

AV

ER

AG

E

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

Exis

ten

ce

of

a

po

licy d

oc

um

en

t

tha

t e

nsu

res

tha

t

ind

ivid

ua

l d

ata

co

nfid

en

tia

lity

an

d u

sag

e f

or

sta

tist

ica

l

pu

rpo

ses

on

ly

Co

ntr

ol c

he

cks

ve

rify

ing

co

nfid

en

tia

lity

are

ve

ry lim

ite

d.

No

pro

toc

ols

in

pla

ce

th

at

ap

ply

to e

xte

rna

l u

sers

ac

ce

ssin

g

sta

tist

ica

l d

ata

.

Tho

ug

h s

om

e

eff

ort

s a

re m

ad

e

to s

afe

gu

ard

ind

ivid

ua

l d

ata

co

nfid

en

tia

lity.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

Exis

ten

ce

of

a

po

licy d

oc

um

en

t

tha

t e

nsu

res

tha

t

ind

ivid

ua

l d

ata

co

nfid

en

tia

lity

an

d u

sag

e f

or

sta

tist

ica

l

pu

rpo

ses

on

ly,

Sta

tist

ica

l

Co

nfid

en

tia

lity is

oft

en

ad

he

red

to t

hro

ug

h

ch

ec

ks

to e

nsu

re

on

ly a

gg

reg

ate

d

da

ta is

ma

de

pu

blic

ly

ava

ilab

le.

Exis

ten

ce

of

ne

ce

ssa

ry

pro

toc

ols

wh

ich

ap

ply

oft

en

to

exte

rna

l u

sers

ac

ce

ssin

g

sta

tist

ica

l d

ata

for

sta

tist

ica

l

pu

rpo

ses.

Qu

ality

Sta

tist

ics

Lev

el 4

Exis

ten

ce

of

a

po

licy d

oc

um

en

t

tha

t e

nsu

res

tha

t

ind

ivid

ua

l d

ata

co

nfid

en

tia

lity

an

d u

sag

e f

or

sta

tist

ica

l

Pu

rpo

ses

on

ly.5

Sta

tist

ica

l

co

nfid

en

tia

lity is

stric

tly a

dh

ere

d

to b

y a

de

qu

ate

me

asu

res

pu

t in

Exis

ten

ce

of

ne

ce

ssa

ry

pro

toc

ols

wh

ich

ap

ply

all

the

tim

e

to e

xte

rna

l u

sers

ac

ce

ssin

g

sta

tist

ica

l d

ata

for

sta

tist

ica

l

pu

rpo

ses.

Sta

nd

ard

s

Po

licy

ou

tlin

ing

me

asu

res

to

safe

gu

ard

ind

ivid

ua

l

da

ta

co

nfid

en

tia

lity

an

d u

sag

e,

exc

lusi

ve

ly f

or

sta

tist

ica

l

pu

rpo

ses.

Pro

toc

ols

fo

r

exte

rna

l u

sers

ac

ce

ssin

g

da

ta.

3.1

.1

3.1

.2

Co

mp

on

en

ts

Sta

tist

ica

l

Co

nfid

en

tia

lity

5 Among these measures should be clear procedures on how to archive records, a policy on how long records are kept and a strategy to safely dispose or destroy the records.


29

NORM 4: ACCOUNTABILITY TERMS OF THE PRODUCTION AND PUBLICATION

OF STATISTICAL REPORTS

The Ministries of Education/Universities/Institution adhere to a policy of timely and accurate

production and publication, to the statistical information requirements of national, regional,

continental and international education frameworks.


30

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

The

Min

istr

y/U

niv

ers

itie

s

/In

stitu

tio

n is

no

t

ob

lige

d t

o

pro

du

ce

or

pu

blis

h

an

aly

tic

al re

po

rts.

Sta

tist

ica

l re

po

rts

are

no

t p

rod

uc

ed

.

NO

RM

AV

ER

AG

E

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

The

Min

istr

y’s

/Un

ive

rsitie

s/In

stit

utio

n o

blig

atio

n

to p

rod

uc

e a

nd

pu

blis

h r

ep

ort

s is

ind

ica

ted

in

an

ad

min

istr

ative

do

cu

me

nt.

Sta

tist

ica

l re

po

rts

are

pro

du

ce

d

bu

t n

ot

pu

blis

he

d.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

The

Min

istr

y’s

/Un

ive

rsitie

s/In

stit

utio

n o

blig

atio

n

to p

rod

uc

e a

nd

pu

blis

h r

ep

ort

s is

ind

ica

ted

in

th

e

do

cu

me

nt

on

EM

IS t

he

No

rms

an

d S

tan

da

rds.

Sta

tist

ica

l re

po

rts

are

pro

du

ce

d

an

d p

ub

lish

ed

reg

ula

rly.

Ho

we

ve

r, t

he

rep

ort

s a

re n

ot

pu

blis

he

d w

ith

in

12 m

on

ths

of

the

sta

rt o

f d

ata

co

llec

tio

n.

Qu

ality

Sta

tist

ics

Lev

el 4

The

Min

istr

y’

/Un

ive

rsity’s

/In

stit

utio

n’s

ha

s a

n

ob

liga

tio

n t

o

pro

du

ce

re

po

rts

on

th

e s

itu

atio

n

of

the

ed

uc

atio

n

an

d t

rain

ing

sec

tor

in

ac

co

rda

nc

e w

ith

the

ed

uc

atio

n

law

or

po

licy.

Pro

du

ctio

n a

nd

pu

blic

atio

n o

f

Sta

tist

ica

l re

po

rts

with

in a

ma

xim

um

12

mo

nth

s fr

om

th

e

sta

rt o

f d

ata

co

llec

tio

n.

Sta

nd

ard

s

Ob

liga

tio

n t

o

pro

du

ce

an

d

pu

blis

h

an

aly

tic

al

rep

ort

s o

n t

he

pe

rfo

rma

nc

e

of

the

ed

uc

atio

n

an

d t

rain

ing

sec

tor

an

nu

ally

.

Tim

ely

pro

du

ctio

n

an

d

pu

blic

atio

n o

f

sta

tist

ica

l

rep

ort

s.

4.1

.1

4.1

.2

Co

mp

on

en

ts

Sta

tist

ica

l

rep

ort

s


31

NORM 5: IMPARTIALITY AND OBJECTIVITY

The Ministries of Education/Universities/Institution must produce and disseminate education

statistics respecting scientific independence and in an objective, professional and transparent

manner in which all users are treated equitably.


32

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

The

co

mp

ilatio

n o

f

sta

tist

ics

is la

rge

ly

influ

en

ce

d b

y

oth

er

exte

rna

l

forc

es

an

d

dis

reg

ard

s

sta

tist

ica

l a

nd

scie

ntific

co

nsi

de

ratio

ns.

Re

sults

are

eith

er

sup

pre

sse

d o

r/a

nd

ma

nip

ula

ted

.

Err

ors

in

sta

tist

ics

are

no

t c

orr

ec

ted

an

d r

evis

ion

s

an

d/o

r u

pd

ate

s o

f

da

ta a

re n

ot

pu

blis

he

d.

Info

rma

tio

n o

n

me

tho

ds

an

d

pro

ce

du

res

use

d

by t

he

Min

istr

y is

no

t a

va

ilab

le t

o

the

pu

blic

.

Sta

tist

ica

l re

lea

ses

an

d s

tate

me

nts

ma

de

in

th

e m

ed

ia

ten

d t

o b

e b

iase

d

an

d p

art

isa

n.

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

The

co

mp

ilatio

n

of

sta

tist

ics

is

larg

ely

ba

sed

on

sta

tist

ica

l

co

nsi

de

ratio

n b

ut

the

re is

co

nsi

de

rab

le

de

gre

e o

f

exte

rna

l

inte

rfe

ren

ce

.

Err

ors

dis

co

ve

red

in p

ub

lish

ed

sta

tist

ics

are

co

rre

cte

d b

ut

the

co

rre

ctio

ns

an

d r

evis

ion

s a

re

rare

ly o

r n

ot

pu

blic

ize

d.

Info

rma

tio

n o

n

the

me

tho

ds

an

d

pro

ce

du

res

use

d

by t

he

Min

istr

y is

on

ly m

ad

e

ava

ilab

le t

o t

he

pu

blic

up

on

req

ue

st.

Sta

tist

ics

are

ma

de

in

an

imp

art

ial a

nd

ob

jec

tive

ma

nn

er.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

The

co

mp

ilatio

n

of

sta

tist

ics

is

larg

ely

ba

sed

on

sta

tist

ica

l

co

nsi

de

ratio

n

bu

t th

ere

is

a

min

ima

l d

eg

ree

of

exte

rna

l

inte

rfe

ren

ce

.

In m

ost

in

sta

nc

es

err

ors

dis

co

ve

red

in p

ub

lish

ed

sta

tist

ics

are

co

rre

cte

d a

nd

pu

blic

ize

d w

ith

in

a r

ea

son

ab

le

tim

efr

am

e.

Info

rma

tio

n o

n

the

me

tho

ds

an

d p

roc

ed

ure

s

use

d b

y t

he

Min

istr

y is

oft

en

dis

sem

ina

ted

.

All

sta

tist

ica

l

rele

ase

s a

nd

sta

tem

en

ts a

re

ma

de

in

th

e

me

dia

Qu

ality

Sta

tist

ics

Lev

el 4

Sta

tist

ics

are

co

mp

iled

on

a

scie

ntific

ba

sis

gu

ide

d b

y

sta

tist

ica

l

co

nsi

de

ratio

ns.

Err

ors

dis

co

ve

red

in p

ub

lish

ed

sta

tist

ics

are

co

rre

cte

d a

nd

pu

blic

ize

d a

t th

e

ea

rlie

st p

oss

ible

da

te u

sin

g

diffe

ren

t fo

rms

of

ap

pro

pria

te

me

dia

with

ou

t

err

ors

Info

rma

tio

n o

n

the

me

tho

ds

an

d

pro

ce

du

res

use

d

by t

he

Min

istr

y is

pu

blic

ize

d a

nd

rou

tin

ely

dis

sem

ina

ted

.

All

sta

tist

ica

l

rele

ase

s a

nd

sta

tem

en

ts m

ad

e

in t

he

me

dia

are

ob

jec

tive

an

d

no

np

art

isa

n.

Sta

nd

ard

s

The

co

mp

ilatio

n

of

ed

uc

atio

n

sta

tist

ics

is

ba

sed

on

scie

ntific

an

d

sta

tist

ica

l

co

nsi

de

ratio

n

s o

nly

.

Co

rre

ctio

ns

of

err

ors

Da

ta

revis

ion

s

an

d/o

r

up

da

tes

are

pu

blis

he

d.

Info

rma

tio

n

on

th

e

me

tho

ds

an

d

pro

ce

du

res

for

sta

tist

ica

l

pro

du

ctio

n

use

d b

y t

he

Min

istr

y is

pu

blic

ly

ava

ilab

le.

The

re

lea

se o

f

sta

tist

ics

is

ma

de

in

an

imp

art

ial a

nd

ob

jec

tive

ma

nn

er.

5.1

.1

5.1

.2

5.1

.3

5.1

.4

Co

mp

on

en

ts

Imp

art

iality

an

d o

bje

ctiv

ity


33

The

re a

re n

o

syst

em

s in

pla

ce

to

gu

ide

sta

ff o

n

ac

ce

pta

ble

eth

ica

l

an

d p

rofe

ssio

na

l

co

nd

uc

t. S

taff

is

invo

lve

d in

irr

eg

ula

r

pra

ctic

es.

The

re a

re n

o p

olic

y

me

asu

res

pre

ve

ntin

g p

olic

y

ma

ke

rs’

ac

ce

ss t

o

da

ta b

efo

re its

rele

ase

an

d

pu

blic

atio

n.

NO

RM

AV

ER

AG

E

The

re a

re n

o

syst

em

s in

pla

ce

to g

uid

e s

taff

on

ac

ce

pta

ble

eth

ica

l a

nd

pro

fess

ion

al

co

nd

uc

t. S

taff

do

es

no

t e

ng

ag

e

in irr

eg

ula

r

pra

ctic

es.

Po

licy m

ake

rs

ha

ve

un

co

ntr

olle

d

ac

ce

ss t

o d

ata

,

the

co

nd

itio

ns

alo

ng

with

th

eir

rea

son

s fo

r th

eir

ac

ce

ss, a

re n

ot

pu

blis

he

d.

Pro

fess

ion

al a

nd

eth

ica

l

gu

ide

line

s e

xis

t

bu

t la

ck c

larity

or/

an

d a

re n

ot

ad

eq

ua

tely

imp

art

ed

to

all

sta

ff.

Po

licy m

ake

rs

ha

ve

ac

ce

ss t

o

the

da

ta. Th

e

co

nd

itio

ns,

alo

ng

with

th

e r

ea

son

s

for

the

ir a

cc

ess

,

are

pu

blis

he

d

an

d n

ot

ad

he

red

to

.

The

re a

re

gu

ide

line

s in

pla

ce

to

en

sure

pro

fess

ion

al

ind

ep

en

de

nc

e

an

d e

thic

al

be

ha

vio

r b

y s

taff

.

A c

lea

r st

rate

gy

6

to e

nsu

re s

taff

is

co

nsc

iou

s o

f

ac

ce

pta

ble

co

nd

uc

t is

in

pla

ce

.

Co

nd

itio

ns

un

de

r

wh

ich

po

licym

ake

rs,

spe

cific

ally

go

ve

rnm

en

t,

ma

y h

ave

ac

ce

ss t

o d

ata

tha

t is

th

at

is

pu

blis

he

d,

ad

he

red

to

an

d

ava

ilab

le f

or

pu

blic

sc

rutin

y

be

fore

its

re

lea

se.

Sta

ff is

aw

are

of

pro

fess

ion

al

an

d e

thic

al

co

nd

uc

t.

Co

nd

itio

ns

un

de

r w

hic

h

po

licy m

ake

rs

ca

n a

cc

ess

da

ta b

efo

re

its

rele

ase

are

ou

tlin

ed

in

th

e

dis

sem

ina

tio

n

po

licy.

5.1

.5

5.1

.6

6 Such a strategy may include induction and orientation of new staff, circulating professional guidelines and codes or constantly training staff on managing professional and ethical questions that

may arise.


34

NORM 6: REGISTRATION OF INSTITUTIONS

All higher education and training institutions must be compelled to register with appropriate

education Ministries if they are to operate as an education and training institution.


35

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

Less

th

an

50%

of

inst

itu

tio

ns

are

reg

iste

red

/u

nd

er

a

un

iqu

e n

um

be

r.

The

ap

pro

pria

te

Min

istr

y h

as

a

dire

cto

ry o

f h

igh

er

ed

uc

atio

n a

nd

tra

inin

g in

stitu

tio

ns

(pu

blic

as

we

ll a

s

priva

te),

bu

t it is

no

t u

pd

ate

d

an

nu

ally

.

NO

RM

AV

ER

AG

E

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

Be

twe

en

50%

an

d 8

0%

of

inst

itu

tio

ns

are

reg

iste

red

un

de

r

a u

niq

ue

nu

mb

er.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

Be

twe

en

80%

an

d 9

0%

of

inst

itu

tio

ns

are

reg

iste

red

un

de

r

a u

niq

ue

nu

mb

er.

The

ap

pro

pria

te

ed

uc

atio

n

Min

istr

y h

as

a

dire

cto

ry o

f

hig

he

r

ed

uc

atio

n a

nd

tra

inin

g

inst

itu

tio

ns

(pu

blic

as

we

ll a

s

priva

te),

bu

t it is

on

ly p

art

ially

up

da

ted

eve

ry

ye

ar.

Qu

ality

Sta

tist

ics

Lev

el 4

Mo

re t

ha

n 9

0%

of

inst

itu

tio

ns

are

reg

iste

red

with

a

un

iqu

e n

um

be

r

The

ap

pro

pria

te

ed

uc

atio

n

Min

istr

y h

as

a

dire

cto

ry o

f a

ll

Hig

he

r e

du

ca

tio

n

an

d t

rain

ing

inst

itu

tio

ns

(pu

blic

an

d p

riva

te)

wh

ich

is

tho

rou

gh

ly

up

da

ted

on

a

ye

arly b

asi

s.

Sta

nd

ard

s

All

pu

blic

an

d

priva

te H

igh

er

ed

uc

atio

n

inst

itu

tio

ns

are

reg

iste

red

with

Min

istr

ies

of

Ed

uc

atio

n

or

rele

va

nt

go

ve

rnm

en

t

au

tho

rity

.

Min

istr

ies

of

Ed

uc

atio

n

ha

ve

an

up

to

da

te

dire

cto

ry,

up

da

ted

ye

arly, o

f a

ll

hig

he

r

ed

uc

atio

n

an

d t

rain

ing

inst

itu

tio

ns.

6.1

.1

6.1

.2

Co

mp

on

en

ts

Re

gis

tra

tio

n o

f

Inst

itu

tio

ns.


36

NORM 7: REGISTRATION OF LEARNERS

All learners are required to present their birth certificate/records in any given year at any higher

education and training institution.


37

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

The

Min

istr

y d

oe

s

no

t c

olle

ct

ag

e b

y

gra

de

ed

uc

atio

n

sta

tist

ics

for

inst

itu

tio

ns.

NO

RM

AV

ER

AG

E

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

The

Min

istr

y

rep

ort

s a

ge

by

gra

de

ed

uc

atio

n

sta

tist

ics

for

mo

st

inst

itu

tio

ns,

so

me

of

wh

ich

ma

y b

e

est

ima

tes.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

The

Min

istr

y

co

llec

ts

co

mp

reh

en

sive

ag

e b

y

Gra

de

ed

uc

atio

n

sta

tist

ics

for

all

inst

itu

tio

ns

bu

t

the

se in

clu

de

som

e e

stim

ate

s

on

ag

e d

ata

.

Qu

ality

Sta

tist

ics

Lev

el 4

The

Min

istr

y

co

llec

ts a

cc

ura

te

an

d

co

mp

reh

en

sive

ag

e b

y g

rad

e

ed

uc

atio

n

sta

tist

ics

for

all

inst

itu

tio

ns.

7

Sta

nd

ard

s

Lea

rne

rs o

f a

ll

hig

he

r

ed

uc

atio

n

an

d t

rain

ing

inst

itu

tio

ns

gro

up

lea

rne

rs

ac

co

rdin

g t

o

ag

e, w

ith

info

rma

tio

n

pro

vid

ed

by

birth

ce

rtific

ate

s

7.1

.1

Co

mp

on

en

ts

Av

aila

bility

of

da

ta b

y a

ge

7 Enrolment by age is collected and published.


38

B. Resources Availability and Utilisation

Adequate resources and their effective use in managing an education management

information system has a major impact on the quality of education statistics.

NORM 8: ADEQUATE RESOURCES

Ministries of Education/universities/institutions ensure that material, human and financial

resources (both in terms of quantity and quality\are commensurate with the statistical

programmes.


39

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Da

ta c

olle

ctio

n m

eth

od

s

de

term

ine

co

sts.

Wh

at

is

the

th

resh

old

fo

r th

e

eff

icie

nc

y a

nd

qu

alit

y

sta

tist

ics?

? So

me

bu

dg

et

is a

lloc

ate

d t

o c

ove

r a

ll

yo

ur

ne

ed

s. W

e n

ee

d a

thre

sho

ld e

stim

ate

. W

e

ne

ed

a s

urv

ey o

f

co

un

trie

s – g

et

be

st

pra

ctic

e t

o g

et

the

% In

the

in

terim

we

ca

n

sug

ge

st a

ra

ng

e o

f

pe

rce

nta

ge

fo

r e

ac

h

Ass

ess

me

nt

leve

l. F

or

Leve

l 4 t

he

re s

ho

uld

be

90%

of

reso

urc

es

sho

uld

be

ava

ilab

le f

rom

sta

te

reso

urc

es

for

HEM

IS.

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

The

re is

no

Sta

te

bu

dg

et

for

the

pro

du

ctio

n o

f

sta

tist

ics,

wh

ich

is

larg

ely

fu

nd

ed

by

pa

rtn

ers

(a

t le

ast

80%

).

Less

th

an

60%

of

ke

y p

ost

s a

re f

ille

d

by q

ua

lifie

d s

taff

an

d s

om

e

fun

ctio

ns

are

ou

tso

urc

ed

to

exte

rna

l p

art

ne

rs.

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

The

re is

a b

ud

ge

t

for

the

pro

du

ctio

n o

f

sta

tist

ics,

wh

ich

is

co

st s

ha

red

with

oth

er

pa

rtn

ers

.

(< 5

0 a

nd

> 2

0 %

)

fro

m p

art

ne

rs b

ut

wh

ich

is

no

t

ad

eq

ua

te.

Mo

re t

ha

n 6

0%

of

ke

y p

ost

s a

re

fille

d b

y q

ua

lifie

d

sta

ff, in

clu

din

g a

t

lea

st o

ne

sta

tist

icia

n.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

The

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

bu

dg

et

for

the

pro

du

ctio

n o

f

ed

uc

atio

n

sta

tist

ics

is

suff

icie

nt

to

co

ve

r m

ost

of

the

HEM

IS c

en

sus

an

d is

rec

eiv

ed

with

in a

rea

son

ab

le

tim

efr

am

e.

Ove

r 80

% o

f th

e

ke

y H

EM

IS

po

sitio

ns

are

sta

ffe

d w

ith

qu

alif

ied

pe

rso

nn

el. A

t a

min

imu

m t

he

re is

a s

tatist

icia

n, a

pro

gra

mm

er,

an

d a

n H

EM

IS

Co

ord

ina

tor.

Qu

ality

Sta

tist

ics

Lev

el 4

The

re is

a

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

bu

dg

et

for

the

pro

du

ctio

n o

f

sta

tist

ics,

co

ve

rin

g 9

0%

of

the

fu

nd

ing

req

uire

me

nts

of

HEM

IS a

ctivitie

s.

10%

fro

m t

he

inst

itu

tio

ns

of

sta

tist

ics,

co

ve

rin

g 1

00

All

ke

y H

EM

IS

po

sitio

ns

are

fill

ed

by s

uff

icie

nt

qu

alif

ied

pe

rso

nn

el in

with

at

the

ve

ry le

ast

:

HEM

IS s

pe

cia

lists

,

ed

uc

atio

n

sta

tist

icia

ns,

syst

em

an

aly

sts,

pro

gra

mm

ers

,

ed

uc

atio

n

pla

nn

ers

, a

nd

da

ta c

ap

ture

rs.

Sta

nd

ard

s

Allo

ca

tio

n o

f

ap

pro

pria

te

bu

dg

et

The

re a

re

suff

icie

nt

qu

alif

ied

pe

rso

nn

el in

ke

y H

EM

IS

po

sitio

ns.

8.1

.1

8.1

.2

Co

mp

on

en

ts

Fin

an

ce

Pe

rso

nn

el


40

The

re a

re n

eith

er

tra

inin

g p

rog

ram

s

no

r st

rate

gy in

pla

ce

.

Min

istr

ies

of

Ed

uc

atio

n/u

niv

ers

iti

es/

inst

itu

tio

ns

do

no

t h

ave

a

stra

teg

y in

pla

ce

to

reta

in s

ca

rce

spe

cia

list

HEM

IS

skill

s.

The

re is

a p

lan

in

pla

ce

bu

t th

ere

is

no

tra

inin

g t

akin

g

pla

ce

.

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

ha

ve

a s

tra

teg

y

in p

lac

e t

o r

eta

in

sca

rce

sp

ec

ialis

t

EM

IS s

kill

s

bu

t n

o

imp

lem

en

tatio

n

Re

leva

nt

EM

IS

pe

rso

nn

el d

o n

ot

pa

rtic

ipa

te in

an

nu

al

co

nfe

ren

ce

s a

nd

wo

rkin

g g

rou

ps

(pro

du

ctio

n,

foru

ms,

pu

blic

atio

n…

) a

t

the

re

gio

na

l a

nd

inte

rna

tio

na

l

leve

l.

The

re is

a p

lan

an

d s

tra

teg

y in

pla

ce

an

d t

he

re

is t

rain

ing

ta

kin

g

pla

ce

in

mo

st

sub

se

cto

rs.

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

ma

ke

use

of

a

mo

tiva

tio

na

l

stra

teg

y t

o r

eta

in

sca

rce

sp

ec

ialis

t

HEM

IS s

kill

s,

wh

ich

is

pa

rtia

lly

imp

lem

en

ted

.

Re

leva

nt

EM

IS

pe

rso

nn

el

pa

rtic

ipa

te

oc

ca

sio

na

lly in

an

nu

al

co

nfe

ren

ce

s

an

d w

ork

ing

gro

up

s

(pro

du

ctio

n,

foru

ms,

pu

blic

atio

n…

) a

t

the

re

gio

na

l a

nd

inte

rna

tio

na

l

leve

l.

The

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

pro

mo

tes

an

d

imp

lem

en

ts

reg

ula

r

pro

fess

ion

al

de

ve

lop

me

nt

an

d u

pg

rad

ing

thro

ug

h t

rain

ing

pro

gra

mm

es

an

d

on

site

te

ch

nic

al

ass

ista

nc

e t

o

en

sure

pro

gre

ss

an

d c

on

tin

uity o

f

EM

IS w

ork

.

Off

ice

rs

suff

icie

ntly

tra

ine

d t

o

ma

nip

ula

te a

nd

an

aly

se t

he

ir

loc

al

da

tab

ase

s.16

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

ma

ke

use

of

a

mo

tiva

tio

na

l

stra

teg

y t

o r

eta

in

sca

rce

sp

ec

ialis

t

HEM

IS s

kill

s, w

hic

h

is f

ully

imp

lem

en

ted

.

Re

leva

nt

EM

IS

pe

rso

nn

el

an

nu

ally

pa

rtic

ipa

te in

all

co

nfe

ren

ce

s a

nd

wo

rkin

g g

rou

ps

(pro

du

ctio

n,

foru

ms,

pu

blic

atio

n…

) a

t

the

re

gio

na

l a

nd

inte

rna

tio

na

l

leve

l.

The

exis

ten

ce

an

d

imp

lem

en

tati

on

of

pro

fess

ion

al

De

ve

lop

me

nt

stra

teg

y8 in

pla

ce

fo

r

HEM

IS s

taff

.

Exis

ten

ce

an

d

imp

lem

en

tati

on

of

a

stra

teg

y t

o

reta

in

sca

rce

spe

cia

list

EM

IS

skill

s

Pa

rtic

ipa

tio

n

an

d

inte

rac

tio

n

with

inte

rna

tio

na

l

ne

two

rks

of

EM

IS e

xp

ert

s.

8.1

.3

8.1

.4

8.1

.5

8 Internal and external training programs


41

HEM

IS u

nit h

as

no

ICT

eq

uip

me

nt

NO

RM

AV

ER

AG

E

EM

IS u

nit h

as

wh

en

th

e n

ee

d

arise

. EM

IS u

nit

ha

s in

ad

eq

ua

te

ac

ce

ss t

o q

ua

lity

ICT

too

ls a

nd

eq

uip

me

nt,

pa

rtic

ula

rly in

ke

y

po

sts.

The

HEM

IS s

taff

ha

s a

cc

ess

to

ad

eq

ua

te IC

T

too

ls a

nd

eq

uip

me

nt,

bu

t

on

ly in

ke

y p

ost

s.

HEM

IS u

nit h

as

ac

ce

ss t

o q

ua

lity

ICT

eq

uip

me

nt

in

ad

eq

ua

te

nu

mb

er

Su

ffic

ien

t

ava

ilab

ility

of

ad

eq

ua

te

info

rma

tio

n

tec

hn

olo

gy

eq

uip

me

nt

an

d

co

mm

un

ica

ti

on

n t

oo

ls a

nd

oth

er

ne

ce

ssitie

s.

8.1

.6

Eq

uip

me

nt


42

NORM 9: COST EFFECTIVENESS

Resources must be effectively and efficiently used.


43

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

Min

istr

ies

of

Ed

uc

atio

n/u

niv

ers

iti

es/

inst

itu

tio

ns

do

no

t h

ave

an

y

inte

rna

l a

nd

exte

rna

l

me

ch

an

ism

s in

pla

ce

to

mo

nito

r

the

use

of

EM

IS

reso

urc

es.

ICTs

are

no

t u

sed

pro

du

ctive

ly.

HEM

IS p

ers

on

ne

l

are

no

t u

sed

in

lin

e

with

th

eir jo

b

de

scrip

tio

ns.

Fu

nd

s a

lloc

ate

d t

o

HEM

IS a

re d

ive

rte

d

to o

the

r

pro

gra

mm

es.

NO

RM

AV

ER

AG

E

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

ha

ve

un

imp

lem

en

ted

inte

rna

l a

nd

exte

rna

l

me

ch

an

ism

s in

pla

ce

to

mo

nito

r

the

use

of

EM

IS

reso

urc

es.

ICTs

are

no

t

op

tim

ize

d f

or

ess

en

tia

l

op

era

tio

ns

in t

he

sta

tist

ica

l va

lue

ch

ain

.

HEM

IS s

taff

do

es

no

t fu

lly s

atisf

y

the

re

qu

ire

me

nts

of

the

ir p

osi

tio

ns.

Fu

nd

s a

lloc

ate

d

to H

EM

IS a

re

use

d m

inim

ally

for

HEM

IS

ac

tivitie

s b

ut

ab

sorp

tio

n

ca

pa

city is

limite

d.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

ha

ve

pa

rtia

lly

imp

lem

en

ted

inte

rna

l a

nd

exte

rna

l

me

ch

an

ism

s in

pla

ce

to

mo

nito

r

the

use

of

EM

IS

reso

urc

es.

ICTs

are

op

tim

ize

d f

or

ess

en

tia

l

op

era

tio

ns

in t

he

sta

tist

ica

l va

lue

ch

ain

.

HEM

IS s

taff

use

d

in lin

e w

ith

th

eir

job

de

scrip

tio

ns.

Fu

nd

s a

lloc

ate

d

to H

EM

IS a

re

use

d s

pe

cific

ally

for

HEM

IS

ac

tivitie

s b

ut

ab

sorp

tio

n

ca

pa

city is

limite

d.

Qu

ality

Sta

tist

ics

Lev

el 4

Min

istr

ies

of

Ed

uc

atio

n/u

niv

er

sitie

s/in

stitu

tio

ns

ha

ve

fu

lly

imp

lem

en

ted

inte

rna

l a

nd

exte

rna

l

me

ch

an

ism

s in

pla

ce

to

mo

nito

r

the

use

of

EM

IS

reso

urc

es.

ICTs

re

op

tim

ize

d

for

all

op

era

tio

ns

in t

he

sta

tist

ica

l

va

lue

ch

ain

.9

HEM

IS s

taff

are

fully

use

d in

lin

e

with

th

eir jo

b

de

scrip

tio

ns.

Fu

nd

s a

lloc

ate

d

to H

EM

IS a

re

use

d s

pe

cific

ally

for

HEM

IS

ac

tivitie

s a

nd

ab

sorp

tio

n

ca

pa

city is

op

tim

al.

Sta

nd

ard

s

Exis

ten

ce

an

d

imp

lem

en

tati

on

on

of

inte

rna

l a

nd

exte

rna

l

me

ch

an

ism

s

for

the

mo

nito

rin

g o

f

EM

IS r

eso

urc

e

utiliz

atio

n

Utiliz

atio

n o

f

ICT.

Utiliz

atio

n o

f

HEM

IS s

taff

Utiliz

atio

n o

f

HEM

IS F

un

ds

9.1

.1

9.2

.1

9.2

.2

9.2

.3

Co

mp

on

en

ts

Mo

nito

rin

g o

f

reso

urc

e

utiliza

tio

n.

Tec

hn

olo

gy

EM

IS H

um

an

Re

sou

rce

s

Ma

na

ge

me

nt

Fin

an

ce

9 Some processes are automated. The productivity potential of ICT is being optimized for data collection, processing and dissemination. Active use of website, CDs, e-mails etc.


44

C. Statistical Processes

Specific international standards, guidelines and good practices must be fully observed in the

process used by Ministries /universities/institutions to organize, collect, process and disseminate

official statistics. The credibility of the statistics has been enhanced by a reputation for good

management and efficiency on statistical production processes. The relevant aspects are

sound methodology, appropriate statistical procedures, definitions and classifications of

internationally acceptable practices and non-excessive burden on respondents.

NORM 10: SOUND METHODOLOGY AND APPROPRIATE STATISTICAL

PROCEDURES

Sound methodology must underpin quality statistics. This requires appropriate statistical

procedures throughout the entire statistical value chain.


45

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

Too

ls f

or

da

ta

co

llec

tio

n a

nd

pro

ce

ssin

g a

re n

ot

in p

lac

e.

Da

ta c

olle

ctio

n

too

ls, d

ata

en

try

form

s a

nd

da

tab

ase

stru

ctu

res

are

no

t

test

ed

be

fore

use

.

Da

ta v

erific

atio

n

pro

ce

sse

s a

re n

ot

imp

lem

en

ted

at

diffe

ren

t st

ag

es

of

the

sta

tist

ica

l va

lue

ch

ain

.

No

Da

ta d

esi

gn

s o

r

sam

ple

se

lec

tio

ns

use

d.

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

Too

ls f

or

da

ta

co

llec

tio

n,

pro

ce

ssin

g

are

use

d in

som

e

are

as

of

the

sta

tist

ica

l va

lue

ch

ain

Test

ing

ma

y

oc

cu

r b

ut

ch

an

ge

s a

re

seld

om

inc

orp

ora

ted

.

Da

ta v

erific

atio

n

pro

ce

sse

s a

re

imp

lem

en

ted

oc

ca

sio

na

lly, a

t

mo

st s

tag

es

of

the

sta

tist

ica

l

va

lue

ch

ain

.

Da

ta d

esi

gn

s,

sam

ple

sele

ctio

ns

are

oc

ca

sio

na

lly

use

d b

ut

the

re is

no

do

cu

me

nta

tio

n.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

A s

tan

da

rd t

oo

l

for

da

ta

co

llec

tio

n,

pro

ce

ssin

g; a

nd

ne

ce

ssa

ry u

ser

an

d t

ec

hn

ica

l

ma

nu

als

are

ava

ilab

le.

Da

ta c

olle

ctio

n

too

ls, d

ata

en

try

form

s a

nd

da

tab

ase

stru

ctu

res

are

,

mo

st o

f th

e t

ime

(bu

t n

ot

alw

ays)

,

test

ed

be

fore

be

ing

use

d.

Da

ta v

erific

atio

n

pro

ce

sse

s a

re

syst

em

atic

ally

imp

lem

en

ted

at

mo

st s

tag

es

of

the

sta

tist

ica

l

va

lue

ch

ain

.

Da

ta d

esi

gn

s

an

d s

am

ple

sele

ctio

ns

are

use

d b

ut

the

re is

no

pro

pe

r

do

cu

me

nta

tio

n.

Qu

ality

Sta

tist

ics

Lev

el 4

Me

tho

do

log

y

too

ls u

sed

wh

ich

inc

lud

es

a d

ata

co

llec

tio

n a

nd

pro

ce

ssin

g

me

tho

do

log

y;

mo

nito

rin

g o

f th

e

sta

tist

ica

l c

ha

in,

de

fin

itio

ns

of

term

s a

nd

co

nc

ep

ts a

re

do

cu

me

nte

d;

Da

ta c

olle

ctio

n

too

ls, d

ata

en

try

form

s a

nd

da

tab

ase

stru

ctu

res

are

test

ed

be

fore

use

.

Da

ta v

erific

atio

n

pro

ce

sse

s a

re

syst

em

atic

ally

imp

lem

en

ted

at

eve

ry s

tag

e o

f

the

sta

tist

ica

l

va

lue

ch

ain

.

Su

rve

y d

esi

gn

s,

sam

ple

se

lec

tio

ns

an

d w

eig

hts

follo

w s

tan

da

rd

me

tho

do

log

y

an

d a

re p

rop

erly

do

cu

me

nte

d.

Sta

nd

ard

s

Me

tho

do

log

ie

s a

nd

to

ols

follo

ws

inte

rna

tio

na

l

/na

tio

na

l

sta

nd

ard

s o

r

pe

er

ag

ree

d

sta

nd

ard

s.

Test

ing

of

too

ls

Ve

rific

atio

n

pro

ce

sse

s

Da

ta d

esi

gn

s

10

.1.1

10

.1.2

10

.1.3

10

.2.1

Co

mp

on

en

ts

Da

ta

pro

ce

ssin

g

an

d

pu

blic

atio

n o

f

ed

uc

atio

na

l

sta

tist

ics

Sp

ec

ialize

d

surv

ey

me

tho

do

log

y


46

No

do

cu

me

nte

d

co

nc

ep

ts a

nd

de

fin

itio

ns

exis

t.

On

ly a

d-h

oc

da

ta

co

llec

tio

n

inst

rum

en

ts a

re

use

d.

Inst

itu

tio

na

l re

co

rds

are

no

t

sta

nd

ard

ize

d a

nd

no

t c

om

pa

tib

le

with

th

e A

nn

ua

l

Ed

uc

atio

n C

en

sus.

The

re is

little

eff

ort

to c

alc

ula

te t

he

mis

sin

g d

ata

.

Re

vis

ion

me

tho

ds

use

d d

o n

ot

follo

w

ac

ce

pte

d

sta

nd

ard

s, s

ets

of

gu

ide

line

s o

r

tra

nsp

are

nt

pra

ctic

es.

Sta

nd

ard

co

nc

ep

ts a

nd

de

fin

itio

ns

are

oc

ca

sio

na

lly

do

cu

me

nte

d.

Min

istr

ies

ha

ve

a

sta

nd

ard

da

ta

co

llec

tio

n

inst

rum

en

t o

nly

for

som

e

sub

sec

tors

.

Sc

ho

ol re

co

rd

ke

ep

ing

co

ve

rs a

few

are

as

of

sch

oo

l

ma

na

ge

me

nt.

It

is n

ot

co

mp

atib

le

with

th

e a

nn

ua

l

ed

uc

atio

n

ce

nsu

s.

No

nsc

ien

tific

me

tho

ds

are

use

d t

o c

alc

ula

te

the

mis

sin

g d

ata

.

Re

vis

ion

me

tho

ds

follo

w a

cc

ep

ted

sta

nd

ard

bu

t se

ts

of

gu

ide

line

s a

re

no

t tr

an

spa

ren

t

in p

rac

tic

e.

Sta

nd

ard

co

nc

ep

ts,

de

fin

itio

ns

an

d

Cla

ssific

atio

ns

are

mo

stly

do

cu

me

nte

d

an

d u

sed

.

Min

istr

ies

ha

ve

a

sta

nd

ard

da

ta

co

llec

tio

n

inst

rum

en

t fo

r

mo

st s

ub

sec

tors

(at

lea

st 4

).

Sc

ho

ol re

co

rds

are

sta

nd

ard

ize

d

bu

t o

fte

n n

ot

co

mp

atib

le w

ith

the

in

form

atio

n

ne

ed

s o

f th

e

an

nu

al

ed

uc

atio

n

ce

nsu

s

inst

rum

en

t.

Ma

nu

al sc

ien

tific

me

tho

ds

are

use

d t

o

ca

lcu

late

so

me

of

the

mis

sin

g

da

ta.

Re

vis

ion

s fo

llow

sta

nd

ard

s a

nd

tra

nsp

are

nt

pro

ce

du

res.

Sta

nd

ard

co

nc

ep

ts,

de

fin

itio

ns

an

d

cla

ssific

atio

ns

are

co

nsi

ste

ntly

ap

plie

d in

th

e

sta

tist

ica

l va

lue

ch

ain

an

d

do

cu

me

nte

d,

Min

istr

ies

ha

ve

a

sta

nd

ard

qu

est

ion

na

ire

(da

ta c

olle

ctio

n

inst

rum

en

t)

for

ea

ch

su

bse

cto

r

(fo

rma

l a

nd

no

n-

form

al

ed

uc

atio

n)

Sta

nd

ard

ize

d

10in

stitu

tio

na

l

rec

ord

s11 a

re

co

mp

atib

le w

ith

the

in

form

atio

n

ne

ed

s o

f th

e

Ed

uc

atio

n

Ce

nsu

s.

Ap

pro

pria

te

au

tom

ate

d

ed

itin

g a

nd

scie

ntific

imp

uta

tio

n

syst

em

s a

re u

sed

an

d r

eg

ula

rly

revis

ed

as

req

uire

d.

Re

vis

ion

s fo

llow

sta

nd

ard

s, a

nd

we

ll e

sta

blis

he

d

an

d t

ran

spa

ren

t

pro

ce

du

res.

De

fin

itio

n o

f

sta

nd

ard

co

nc

ep

ts a

nd

term

s a

re

ava

ilab

le,

do

cu

me

nte

d

an

d u

sed

.

Ava

ilab

ility

of

qu

est

ion

-

na

ire

s fo

r

sub

sec

tors

Ha

rmo

niz

atio

n o

f sc

ho

ol

rec

ord

s a

nd

co

mp

atib

ility

with

sc

ho

ol

ce

nsu

ses.

Imp

uta

tio

n o

f

mis

sin

g d

ata

Da

ta

Re

vis

ion

s

10

.2.2

10

.2.3

10

.3.1

10

.3.2

10

.3.3

Re

co

rd

Sy

ste

ms

10 Standardised in terms of uniformity and quality; there has to be a glossary of standard concepts. 11 Includes all institutions – schools, training colleges, universities, etc.


47

Po

pu

latio

n

est

ima

tes

are

ob

tain

ed

fro

m

un

au

tho

rize

d

sou

rce

s.

NO

RM

AV

ER

AG

E

The

la

test

po

pu

latio

n

fig

ure

s a

nd

ag

e

bre

akd

ow

n,

som

etim

es

ob

tain

ed

fro

m

Sta

tist

ica

l

au

tho

rity

(CSO

/NSO

) a

nd

oth

er

tim

es

fro

m

inte

rna

tio

na

l

sou

rce

s o

uts

ide

of

Sta

tist

ica

l

au

tho

rity

.

The

la

test

po

pu

latio

n

fig

ure

s a

nd

ag

e

bre

akd

ow

n,

som

etim

es

ob

tain

ed

fro

m

Sta

tist

ica

l

au

tho

rity

The

la

test

su

rve

y

or

ce

nsu

s

po

pu

latio

n

est

ima

tes

an

d

pro

jec

tio

ns

ob

tain

ed

fro

m

the

Sta

tist

ica

l

au

tho

rity

(CSO

/NSO

) a

re

use

d t

o c

alc

ula

te

ed

uc

atio

n

ind

ica

tors

.

So

urc

e o

f

po

pu

latio

n

sta

tist

ics1

2

10

.3.4

12 This is to make sure that there is one source of population statistics –Central Statistics Office.


48

NORM 11: NON-EXCESSIVE BURDEN ON RESPONDENTS

The reporting burden should be proportionate to the needs of the users and should not be

excessive for respondents. Ministries of Education/Universities/Institutions monitor the response

burden and set targets for its reduction.


49

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

De

ba

te f

oc

use

d o

n le

ve

l

1

Pro

ble

m is

tha

t th

is m

igh

t

be

th

e f

un

ctio

n o

f th

e

na

tio

na

l b

ure

au

of

sta

tist

ics

-

Ho

we

ve

r, c

ou

ntr

ies

ag

ree

d t

ha

t th

is is

the

role

of

EM

IS in

ed

uc

atio

n.

It s

ho

uld

be

co

ord

ina

ted

by E

MIS

. W

e m

ust

en

sure

tha

t EM

IS is

in t

he

lo

op

of

all

surv

eys

eve

n t

ho

se

co

ord

ina

ted

by t

he

NSO

.

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

Ed

uc

atio

n

sta

tist

ica

l su

rve

ys

are

ove

rlo

ad

ed

with

de

tail

or

do

no

t a

dd

ress

th

e

min

imu

m n

ee

ds

of

use

rs e

xc

ee

d b

ut

are

no

t re

leva

nt.

No

sa

mp

ling

is

do

ne

oth

er

tha

n

ce

nsu

s.

EM

IS d

oe

s n

ot

mo

nito

r o

the

r

ed

uc

atio

n s

urv

eys

exc

ep

t e

du

ca

tio

n

surv

eys

by t

he

Min

istr

y.

NO

RM

AV

ER

AG

E

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

The

ra

ng

e a

nd

de

tail

of

ed

uc

atio

n

sta

tist

ics

co

llec

ted

Exc

ee

d t

he

ba

sic

ess

en

tia

ls a

re

rele

va

nt

to t

he

bro

ad

er

sco

pe

Re

spo

nd

ing

to

qu

est

ion

na

ire

s is

spre

ad

th

rou

gh

sam

plin

g

tec

hn

iqu

es

So

me

tim

es

EM

IS

mo

nito

rs

ed

uc

atio

na

l

surv

eys.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

The

ra

ng

e a

nd

de

tail

of

ed

uc

atio

n

sta

tist

ics

co

llec

ted

exc

ee

ds

the

ir

de

ma

nd

th

e

ess

en

tia

l d

ata

req

uire

d b

y f

or

an

aly

sis.

Re

spo

nd

ing

to

qu

est

ion

na

ire

s is

spre

ad

as

wid

ely

as

po

ssib

le o

ve

r

surv

ey

po

pu

latio

ns

thro

ug

h

ap

pro

pria

te

sam

plin

g

tec

hn

iqu

es

Mo

st o

f th

e t

ime

,

EM

IS m

on

ito

rs a

ll

inte

rna

l

ed

uc

atio

na

l

surv

eys.

Th

e E

MIS

un

it c

olla

bo

rate

s

with

all

pro

du

ce

rs o

f

ed

uc

atio

n

surv

eys.

Qu

ality

Sta

tist

ics

Lev

el 4

The

ra

ng

e a

nd

de

tail

of

ed

uc

atio

n s

tatist

ics

de

ma

nd

s is

lim

ite

d t

o

wh

at

is e

sse

ntia

l.

The

bu

rde

n o

f

resp

on

din

g t

o

qu

est

ion

na

ire

s is

spre

ad

as

wid

ely

as

po

ssib

le o

ve

r su

rve

y

po

pu

latio

ns

thro

ug

h

ap

pro

pria

te s

am

plin

g

tec

hn

iqu

es

in in

sta

nc

es

wh

ere

a c

en

sus

of

ed

uc

atio

n in

stitu

tio

ns

is

no

t b

ein

g u

nd

ert

ake

n.

The

Min

istr

y’s

EM

IS u

nit

is t

he

co

ord

ina

tin

g a

nd

reg

iste

rin

g b

od

y o

f

inte

rna

l e

du

ca

tio

n

surv

eys

in c

olla

bo

ratio

n

with

th

e n

atio

na

l

sta

tist

ica

l o

ffic

e. Th

is

en

sure

s th

at

the

y

arb

itra

te t

he

qu

an

tity

,

qu

alit

y a

nd

sta

nd

ard

s

of

surv

eys

un

de

rta

ke

n

in e

du

ca

tio

n a

nd

tra

inin

g in

stitu

tio

ns.

Sta

nd

ard

s

Co

re

info

rma

tio

n

va

lida

tio

n,

revie

w a

nd

pu

blic

atio

n

ne

ed

s.

The

bu

rde

n o

f

resp

on

se.

Co

llab

ora

tio

n

on

ed

uc

atio

n

da

ta

co

llec

tio

n

11

.1.1

11

.1.2

11

.1.3

Co

mp

on

en

ts

Ess

en

tia

l

min

imu

m


50

D. Education Information Reporting

Published and disseminated education statistics must meet users’ needs and comply with

international quality standards in order to serve the needs of African Universities, Institutions,

Governments, Research institutions, Business concerns and the Public generally. Important issues

concern the extent to which the statistics are relevant, accurate and reliable, timely, coherent,

comprehensive, comparable, over time, across regions and countries and readily accessible by

users.

NORM 12: RELEVANCE

Education statistics must meet the needs of users.


51

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

The

ass

ess

me

nt

me

tho

do

log

y w

as

use

d

to m

ea

sure

an

d a

na

lyze

a p

erf

orm

an

ce

or

pro

du

ct

to p

rovid

e

qu

alit

y, tim

ely

fe

ed

ba

ck

for

imp

rove

me

nt

by

inc

lud

ing

th

e q

ua

lity

leve

ls a

s a

me

an

s fo

r

de

term

inin

g t

he

qu

alit

y

leve

l o

f th

e e

vid

en

ce

.

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

No

att

em

pt

ha

s

be

en

ma

de

to

cre

ate

a u

ser

list.

No

co

nsu

lta

tio

ns

or

pro

ce

sse

s o

n u

ser

ne

ed

s in

pla

ce

.

Ide

ntifie

d n

ee

ds

are

ad

dre

sse

d in

less

th

an

50%

of

ca

ses

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

Att

em

pts

ha

ve

be

en

ma

de

to

cre

ate

a u

ser

list.

So

me

use

r d

ata

an

d t

he

ir

co

nta

cts

are

kn

ow

n, b

ut

no

pro

pe

r lis

t e

xis

ts.

The

lis

t is

inc

om

ple

te o

r

no

t re

gu

larly

up

da

ted

.

Pro

ce

sse

s a

re in

pla

ce

bu

t

co

nsu

lta

tio

ns

are

on

an

ad

ho

c13

ba

sis.

The

re a

re n

o

inst

itu

tio

na

l

pro

ce

sse

s in

pla

ce

.

Ide

ntifie

d n

ee

ds

are

ad

dre

sse

d in

50%

to

79%

of

ca

ses

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

Ke

y u

sers

ha

ve

be

en

id

en

tifie

d

with

so

me

of

the

co

nta

ct

de

tails

no

t u

p t

o d

ate

.

The

mo

st r

ec

en

t

up

da

te w

as

co

nd

uc

ted

mo

re

tha

n t

wo

ye

ars

ag

o. Th

is is

no

t

the

up

da

ted

lis

t.

Pro

ce

sse

s a

re in

pla

ce

bu

t u

sers

are

so

me

tim

es

no

t c

on

sulte

d.

Inst

itu

tio

na

l

pro

ce

sse

s a

re in

pla

ce

bu

t u

sers

are

on

ly

co

nsu

lte

d in

som

e c

ase

s.

Ide

ntifie

d n

ee

ds

are

ad

dre

sse

d in

80%

to

94%

of

ca

ses

Qu

ality

Sta

tist

ics

Lev

el 4

Ke

y u

sers

14 o

f

da

ta h

ave

be

en

ide

ntifie

d w

ith

the

ir m

ost

re

ce

nt

co

nta

ct

de

tails

.

Exis

ten

ce

of

a

co

mp

reh

en

sive

an

d u

pd

ate

d lis

t

or

inve

nto

ry.

Pro

ce

sse

s a

re in

pla

ce

to

re

gu

larly

co

nsu

lt u

sers

reg

ard

ing

th

eir

ne

ed

s, e

va

lua

te

the

re

leva

nc

e

an

d p

rac

tic

al

utilit

y o

f e

xis

tin

g

sta

tist

ics

in

me

etin

g t

he

ir

ne

ed

s, a

nd

ad

vis

e o

n t

he

ir

em

erg

ing

ne

ed

s

an

d p

rio

riti

es.

15

Ide

ntifie

d n

ee

ds

are

ad

dre

sse

d in

mo

re t

ha

n 9

5%

of

ca

ses

Sta

nd

ard

s

Use

r

ide

ntific

atio

n

of

da

ta.

Co

nsu

lta

tio

n

pro

ce

sse

s

with

da

ta

use

rs

Ad

dre

ssin

g o

f

ne

ed

s

exp

ress

ed

by

use

rs in

da

ta

co

llec

tio

n

pro

ce

sse

s

12

.1.1

12

.1.2

12

.1.3

Co

mp

on

en

ts

Use

r n

ee

ds

13 Ad hoc means driven by user request 14 Data needs for school record keeping through to district, regional performance reporting and Head Office needs of various directories are taken into consideration.

15 Availability of dissemination, briefing, distribution of outputs etc.


52

Inst

itu

tio

na

l d

ata

rep

ort

s a

re n

ot

sen

t

ba

ck t

o in

stitu

tio

ns.

No

Use

r

Sa

tisf

ac

tio

n S

urv

ey

or

oth

er

arr

an

ge

me

nts

are

pla

ce

.

No

pla

ns

in p

lac

e.

Inst

itu

tio

na

l d

ata

rep

ort

s a

re

seld

om

se

nt

ba

ck t

o s

om

e

inst

itu

tio

ns

an

d

som

e

ad

min

istr

ative

leve

ls.

The

re is

little

or

no

follo

w-u

p.

No

Use

r

Sa

tisf

ac

tio

n

Su

rve

y e

xis

ts b

ut

the

re a

re o

the

r

info

rma

l

arr

an

ge

me

nts

in

pla

ce

to

co

llec

t

fee

db

ac

k

The

re a

re a

nn

ua

l

Min

istr

y p

lan

s

tha

t in

clu

de

EM

IS

bu

t n

o s

ep

ara

te

Str

ate

gic

Pla

n f

or

EM

IS.

This

on

ly

co

nc

ern

s so

me

ed

uc

atio

n

sub

sec

tors

.

Inst

itu

tio

na

l d

ata

rep

ort

s a

re

som

etim

es

sen

t

ba

ck t

o a

ll

inst

itu

tio

ns

an

d

diffe

ren

t

ad

min

istr

ative

leve

ls f

or

fee

db

ac

k.

Fo

llow

-up

is

som

etim

es

co

nd

uc

ted

.

Exis

ten

ce

of

surv

ey t

o a

sse

ss

use

r sa

tisf

ac

tio

n

bu

t n

o f

orm

al

me

asu

res

are

in

pla

ce

to

co

llec

t

fee

db

ac

k.

The

EM

IS

stra

teg

ic p

lan

exis

ts b

ut

on

ly

co

ve

rs a

fe

w

sub

sec

tors

.

Inst

itu

tio

na

l d

ata

rep

ort

s a

re

alw

ays

sen

t b

ac

k

to a

ll in

stitu

tio

ns

an

d t

he

ir

diffe

ren

t

ad

min

istr

ative

leve

ls f

or

fee

db

ac

k a

nd

to

allo

w h

igh

er

ed

uc

atio

n

inst

itu

tio

ns

to

ma

ke

co

mp

ariso

ns.

Fo

llow

-up

is

co

nd

uc

ted

.

Exis

ten

ce

of

a

surv

ey t

o a

sse

ss

use

r sa

tisf

ac

tio

n

or

an

d a

ll o

the

r

form

al m

ea

sure

s

use

d a

nn

ua

lly t

o

co

llec

t fe

ed

ba

ck

fro

m u

sers

an

d

pro

du

ce

rs o

f th

e

info

rma

tio

n, in

pa

rtic

ula

r th

ose

inst

itu

tio

ns

wh

o

are

in

vo

lve

d in

the

co

llec

tio

n,

co

mp

ilatio

n a

nd

pro

du

ctio

n o

f

rep

ort

s o

n

ed

uc

atio

na

l

info

rma

tio

n.

The

re is

an

EM

IS

stra

teg

ic p

lan

in

pla

ce

th

at

co

ve

rs s

ub

-

sec

tors

an

d

ad

dre

sse

s th

e

Min

istr

y's

po

licy

imp

era

tive

s.16

Fe

ed

ba

ck

rep

ort

s.

A U

ser

Sa

tisf

ac

tio

n

Su

rve

y is

co

nd

uc

ted

.

EM

IS S

tra

teg

ic

Pla

n

12

.2.1

12

.3.1

12

.4.1

Use

r a

nd

inte

rna

l

pro

du

ce

r

fee

db

ac

k

Fe

ed

ba

ck

co

lle

ctio

n

16 Existence of a documented strategy.


53

An

aly

sis

an

d

tra

ckin

g o

f

sta

tist

ica

l in

dic

ato

rs

are

in

fre

qu

en

t.

No

eff

ort

is

ma

de

to m

ake

co

mp

ariso

ns

with

inte

rna

tio

na

lly

co

mp

ara

ble

ind

ica

tors

.

No

eff

ort

is

ma

de

to m

ake

co

mp

ariso

ns

with

inte

rna

tio

na

lly

co

mp

ara

ble

ind

ica

tors

.

NO

RM

AV

ER

AG

E

Ind

ica

tors

are

rare

ly u

sed

to

me

asu

re t

he

pe

rfo

rma

nc

e o

f

limite

d s

ub

-

sec

tors

of

the

ed

uc

atio

n

syst

em

.

Ind

ica

tors

are

limite

d t

o t

he

me

asu

rem

en

t o

f

na

tio

na

l

ob

jec

tive

s, w

ith

po

or

inte

rna

tio

na

l a

nd

reg

ion

al

co

mp

ariso

ns.

Ind

ica

tors

are

limite

d t

o t

he

me

asu

rem

en

t o

f

na

tio

na

l

ob

jec

tive

s, w

ith

po

or

inte

rna

tio

na

l a

nd

reg

ion

al

co

mp

ariso

ns.

An

aly

sis

of

ind

ica

tors

in

an

nu

al st

atist

ica

l

pu

blic

atio

ns

larg

ely

allo

ws

for

the

le

ve

ls o

f

som

e s

ub

-se

cto

rs

of

the

ed

uc

atio

n

syst

em

to

be

me

asu

red

.

Inte

rna

tio

na

l a

nd

reg

ion

al

co

mp

ariso

ns

are

oc

ca

sio

na

lly

ma

de

.

Inte

rna

tio

na

l a

nd

reg

ion

al

co

mp

ariso

ns

are

oc

ca

sio

na

lly

ma

de

.

Ke

y in

dic

ato

rs

are

an

aly

sed

an

d t

rac

ke

d t

o

me

asu

re

pe

rfo

rma

nc

e o

f

the

en

tire

ed

uc

atio

n

syst

em

.

Inte

rna

tio

na

l a

nd

reg

ion

al

co

mp

ariso

n o

f

ind

ica

tors

is

wid

ely

use

d.

Inte

rna

tio

na

l a

nd

reg

ion

al

co

mp

ariso

n o

f

ind

ica

tors

is

wid

ely

use

d.

Co

ve

rag

e o

f

Ind

ica

tors

in

An

nu

al

Sta

tist

ica

l

pu

blic

atio

ns

Co

mp

ariso

ns

of

Ind

ica

tors

in

An

nu

al

Sta

tist

ica

l

pu

blic

atio

ns

Co

mp

ariso

ns

of

Ind

ica

tors

in A

nn

ua

l

Sta

tist

ica

l

pu

blic

atio

ns

12

.4.2

12

.4.3

12

.4.4


54

NORM 13: ACCURACY AND RELIABILITY

Education statistics must accurately and reliably portray reality. The accuracy of the statistical

information is the degree to which the output correctly describes the phenomenon it was

designed to measure.


55

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

The

re is

an

inc

om

ple

te

na

tio

na

l lis

t o

f

hig

he

r e

du

ca

tio

n

an

d t

ert

iary

inst

itu

tio

ns

wh

ich

is

up

da

ted

irr

eg

ula

rly

on

an

ad

ho

c

ba

sis.

The

re a

re f

ew

er

tha

n 5

0%

of

inst

itu

tio

ns

resp

on

din

g t

o t

he

ce

nsu

s

qu

est

ion

na

ire

.

Re

spo

nse

ra

tes

are

no

t re

po

rte

d

an

nu

ally

.

The

re is

an

inc

om

ple

te

na

tio

na

l lis

t o

f

hig

he

r e

du

ca

tio

n

an

d t

ert

iary

inst

itu

tio

ns

wh

ich

is

up

da

ted

irr

eg

ula

rly

on

an

ad

ho

c

ba

sis.

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

The

re is

an

inc

om

ple

te

na

tio

na

l lis

t o

f

pu

blic

an

d

priva

te h

igh

er

ed

uc

atio

n a

nd

tert

iary

in

stitu

tio

ns

wh

ich

wa

s la

st

up

da

ted

ove

r a

ye

ar

ag

o.

Co

mp

ariso

ns

are

ma

de

with

th

e

size

of

the

pre

vio

us

ye

ar’

s

po

pu

latio

n.

The

re a

re

be

twe

en

50 -

79

% o

f in

stitu

tio

ns

resp

on

din

g t

o

the

ce

nsu

s

qu

est

ion

na

ire

.

Re

spo

nse

ra

tes

are

no

t p

ub

lish

ed

with

th

e

sta

tist

ica

l re

po

rts.

The

re is

an

inc

om

ple

te n

atio

na

l

list

of

pu

blic

an

d

priv

ate

hig

he

r

ed

uc

atio

n a

nd

tert

iary

inst

itu

tio

ns

wh

ich

wa

s la

st

up

da

ted

ov

er

a

ye

ar

ag

o.

Co

mp

ariso

ns

are

ma

de

with

th

e s

ize

of

the

pre

vio

us

ye

ar’

s p

op

ula

tio

n.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

The

re is

a

co

mp

lete

lis

t o

f

pu

blic

hig

he

r

ed

uc

atio

n a

nd

tert

iary

inst

itu

tio

ns

wh

ich

ha

s b

ee

n

up

da

ted

with

in

the

ye

ar.

Th

e lis

t

of

priva

te h

igh

er

ed

uc

atio

n a

nd

tert

iary

inst

itu

tio

ns

is le

ss

relia

ble

as

up

da

tin

g is

mo

re

diffic

ult.

The

re is

80

-94%

resp

on

se r

ate

fro

m p

ub

lic a

nd

priva

te

inst

itu

tio

ns

in

retu

rnin

g t

he

ir

qu

est

ion

na

ire

s.

Re

spo

nse

ra

tes

are

so

me

tim

es

rep

ort

ed

.

The

re is

a c

om

ple

te

list

of

pu

blic

hig

he

r

ed

uc

atio

n a

nd

tert

iary

inst

itu

tio

ns

wh

ich

ha

s b

ee

n

up

da

ted

with

in t

he

ye

ar.

Th

e li

st o

f

priv

ate

hig

he

r

ed

uc

atio

n a

nd

tert

iary

inst

itu

tio

ns

is

less

re

liab

le a

s

up

da

tin

g is

mo

re

diffic

ult.

Qu

ality

Sta

tist

ics

Lev

el 4

The

re is

a

co

mp

reh

en

sive

an

d u

pd

ate

d lis

t

of

hig

he

r

ed

uc

atio

n a

nd

tert

iary

inst

itu

tio

ns,

wh

ich

is u

sed

to

de

term

ine

th

e

size

of

the

ta

rge

t

po

pu

latio

n.

All

pu

blic

an

d

priva

te h

igh

er

ed

uc

atio

n a

nd

tert

iary

in

stitu

tio

ns

are

lis

ted

an

d

up

da

ted

an

nu

ally

The

re is

a

resp

on

se r

ate

of

ove

r 9

5%

fro

m

bo

th p

riva

te a

nd

pu

blic

in

stitu

tio

ns

in r

etu

rnin

g t

he

ir

ce

nsu

s

qu

est

ion

na

ire

s.

Re

spo

nse

ra

tes

an

d t

he

ass

um

ptio

ns

on

mis

sin

g in

stitu

tio

ns

are

cle

arly

The

re is

a

co

mp

reh

en

siv

e a

nd

up

da

ted

list

of

hig

he

r e

du

ca

tio

n

an

d t

ert

iary

inst

itu

tio

ns,

wh

ich

is

use

d t

o d

ete

rmin

e

the

siz

e o

f th

e t

arg

et

po

pu

latio

n.

All

pu

blic

an

d

priv

ate

hig

he

r

ed

uc

atio

n a

nd

tert

iary

inst

itu

tio

ns

are

list

ed

an

d

up

da

ted

an

nu

ally

Sta

nd

ard

s

Co

ve

rag

e o

f

ce

nsu

s o

f

hig

he

r

ed

uc

atio

n

an

d t

ert

iary

inst

itu

tio

ns

Re

spo

nse

ra

te

to c

en

sus

of

hig

he

r

ed

uc

atio

n

an

d t

ert

iary

inst

itu

tio

ns

Co

ve

rag

e o

f

ce

nsu

s o

f

hig

he

r

ed

uc

atio

n

an

d t

ert

iary

inst

itu

tio

ns

13

.1.1

13

.2.1

13

.2.2

Co

mp

on

en

ts

Ass

ess

me

nt

of c

ov

era

ge

of

da

ta

co

lle

ctio

n in

co

mp

ari

son

to

the

ta

rge

t

po

pu

latio

n

Ass

ess

me

nt

of

resp

on

se r

ate

s

to t

he

ce

nsu

s

Ass

ess

me

nt

of c

ov

era

ge

of

da

ta

co

lle

ctio

n in

co

mp

ari

son

to

the

ta

rge

t

po

pu

latio

n


56

Da

ta u

nu

sab

le.

Me

asu

res

of

sam

plin

g e

rro

rs a

re

no

t c

alc

ula

ted

This

ne

ve

r

ha

pp

en

s.

NO

RM

AV

ER

AG

E

The

re a

re

nu

me

rou

s n

on

-

sam

plin

g e

rro

rs.

Me

asu

res

of

sam

plin

g e

rro

rs

are

ava

ilab

le o

n

req

ue

st f

or

the

ma

in v

aria

ble

s

on

ly

This

se

ldo

m

ha

pp

en

s.

The

re a

re

min

ima

l n

on

-

sam

plin

g e

rro

rs.

Me

asu

res

of

sam

plin

g e

rro

rs

are

pu

blis

he

d f

or

the

ma

in

va

ria

ble

s.

Me

asu

res

of

oth

er

va

ria

ble

s

are

no

t a

va

ilab

le

eve

n o

n r

eq

ue

st

This

oc

ca

sio

na

lly

ha

pp

en

s w

he

n

yo

u id

en

tify

a

po

ssib

le e

rro

r.

The

re a

re n

o n

on

- sa

mp

ling

err

ors

.

Me

asu

res

of

sam

plin

g e

rro

rs

mu

st b

e

ca

lcu

late

d f

or

the

ma

in

va

ria

ble

s. T

he

y

mu

st b

e

ava

ilab

le f

or

the

oth

er

va

ria

ble

s

on

re

qu

est

An

nu

al H

igh

er

Ed

uc

atio

n

Ce

nsu

s d

ata

is

reg

ula

rly

co

mp

are

d w

ith

oth

er

sou

rce

s o

f

da

ta -

Ho

use

ho

ld S

urv

ey

da

ta a

nd

oth

er

da

ta s

ou

rce

s.

All

no

n-

sam

plin

g

err

ors

are

ca

lcu

late

d

e.g

.17

Me

asu

res

of

sam

plin

g

err

ors

for

ke

y

va

ria

ble

s a

re

ca

lcu

late

d

e.g

. Sta

nd

ard

err

or,

co

eff

icie

nt

of

va

ria

tio

n

Da

ta

co

nsi

ste

nc

y.

13

.3.1

13

.3.2

13

.3.3

No

n s

am

plin

g

err

ors

Sa

mp

lin

g

Err

ors

Tria

ng

ula

tio

n o

f

Da

ta

17 E.g. Poor responses to survey questionnaires either deliberately or due to lack of comprehension or poor conceptualization by the surveyors.


57

NORM 14: TIMELINESS AND PUNCTUALITY

Education statistics must be disseminated in a timely and punctual manner.


58

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

An

nu

al st

atist

ica

l

rep

ort

is

no

t

pu

blis

he

d a

t a

ll.

No

gu

ide

line

s e

xis

t

for

the

fre

qu

en

cy

of

rele

ase

an

d

rele

ase

da

tes.

Mo

st

of

the

se d

ec

isio

ns

are

le

ft a

t th

e

dis

cre

tio

n o

f th

e

rele

va

nt

Dire

cto

rate

/de

pa

rt

me

nt

he

ad

.

The

re is

no

cla

rity

in

term

s o

f re

lea

se

da

tes

an

d n

o

just

ific

atio

n is

pro

vid

ed

fo

r d

ela

ys

with

da

ta

pu

blic

atio

n.

Pre

limin

ary

sta

tist

ics

are

no

t m

ad

e

ava

ilab

le t

o u

sers

.

NO

RM

AV

ER

AG

E

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

An

nu

al st

atist

ica

l

rep

ort

is

pu

blis

he

d in

mo

re t

ha

n 2

ye

ars

.

Tho

ug

h

gu

ide

line

s o

n

fre

qu

en

cy a

nd

rele

ase

da

tes

are

in p

lac

e,

the

y

are

oft

en

dis

reg

ard

ed

.

No

tific

atio

n o

f

de

lays

is r

are

.

No

gu

ide

line

s in

pla

ce

fo

r th

e

rele

ase

of

pre

limin

ary

da

ta.

Ad

ho

c

pre

limin

ary

da

ta

ca

n b

e m

ad

e

ava

ilab

le o

n

req

ue

st.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

An

nu

al st

atist

ica

l

rep

ort

is

pu

blis

he

d w

ith

in

2 y

ea

rs.

Gu

ide

line

s o

n

fre

qu

en

cy e

xis

ts

bu

t a

re o

nly

ad

he

red

to

in

som

e in

sta

nc

es,

with

so

me

rele

ase

da

tes

un

spe

cifie

d o

r

mis

sed

.

The

pu

blic

is

Oc

ca

sio

na

lly

no

tifie

d in

ad

va

nc

e o

f

de

lays

in t

he

dis

sem

ina

tio

n

sch

ed

ule

.

Gu

ide

line

s fo

r

the

re

lea

se o

f

sta

tist

ica

l d

ata

are

in

pla

ce

.

Pre

limin

ary

da

ta

is d

isse

min

ate

d

bu

t th

e

sug

ge

ste

d t

ime

fra

me

is

no

t

ad

he

red

to

.

Qu

ality

Sta

tist

ics

Lev

el 4

An

nu

al st

atist

ica

l re

po

rt

is p

ub

lish

ed

du

rin

g t

he

ac

ad

em

ic y

ea

r o

f

co

llec

tio

n.

Cle

ar

gu

ide

line

s a

re in

pla

ce

sta

tin

g t

he

fre

qu

en

cy o

f re

lea

sin

g

sta

tist

ics,

an

d s

ett

ing

ou

t a

tim

e f

ram

e f

or

the

ir r

ele

ase

.

The

pu

blic

is

info

rme

d

of

an

y d

isru

ptio

n t

o t

he

dis

sem

ina

tio

n

sch

ed

ule

. Exp

lan

atio

ns

are

giv

en

an

d a

ne

w

da

te is

set.

Gu

ide

line

s fo

r th

e

rele

ase

of

sta

tist

ica

l

da

ta a

re in

pla

ce

.

Qu

alit

y p

relim

ina

ry

da

ta is

dis

sem

ina

ted

in

ac

co

rda

nc

e w

ith

th

e

rec

om

me

nd

ed

tim

e

fra

me

.

Sta

nd

ard

s

An

an

nu

al

sta

tist

ica

l

rep

ort

is

pu

blis

he

d.

Gu

ide

line

s o

n

the

fre

qu

en

cy

an

d r

ele

ase

da

tes

for

da

ta in

pla

ce

The

pu

blic

is

info

rme

d o

f

de

lays

in t

he

dis

sem

ina

tio

n

sch

ed

ule

.

Pre

limin

ary

da

ta is

dis

sem

ina

ted

in

ac

co

rda

nc

e

with

th

e s

et

tim

e f

ram

e.

14

.1.1

14

.2.1

14

.3.1

14

.3.2

Co

mp

on

en

ts

Pu

blic

atio

n o

f

sta

tist

ics

Ca

len

da

r o

f

da

ta

pu

blic

atio

n

Pu

nc

tua

lity

of

rele

ase


59

NORM 15: COHERENCE, CONSISTENCY, COMPARABILITY AND

INTERPRETABILITY

Education statistics should be coherent and consistent over time, and comparable between

regions and countries; it should be possible to combine and make joint use of related data from

different sources.


60

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

No

co

nsi

de

ratio

n is

giv

en

to

th

e

co

mp

ilatio

n o

f

sta

tist

ics

on

th

e

ba

sis

of

co

mm

on

sta

nd

ard

s

The

co

nsi

ste

nc

y o

f

the

sta

tist

ics

is

rare

ly v

erifie

d a

nd

pu

blis

he

d.

Sta

tist

ics

for

the

ye

ar

in p

rog

ress

are

ha

rdly

co

mp

are

d

to t

he

sta

tist

ics

for

the

pre

vio

us

ye

ar

to v

erify

co

he

ren

ce

.

No

tary

dis

cre

pa

nc

ies

are

ide

ntifie

d.

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

Sta

tist

ics

are

oc

ca

sio

na

lly

co

mp

iled

on

th

e

ba

sis

of

co

mm

on

sta

nd

ard

s.

The

co

nsi

ste

nc

y

of

the

sta

tist

ics

is

som

etim

es

ve

rifie

d.

Err

ors

are

ide

ntifie

d,

co

mp

arin

g

lon

gitu

din

al b

ase

da

ta (

ove

r

seve

ral ye

ars

).

Sta

tist

ics

for

the

ye

ar

in p

rog

ress

are

co

mp

are

d t

o

the

sta

tist

ics

for

the

pre

vio

us

ye

ar

in f

ew

ca

ses

to

ve

rify

co

he

ren

ce

.

Co

he

ren

ce

is

ac

ce

pta

ble

.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

Sta

tist

ics

are

mo

stly

co

mp

iled

on

th

e b

asi

s o

f

co

mm

on

sta

nd

ard

s.

The

co

nsi

ste

nc

y

of

the

sta

tist

ics

is

ve

rifie

d o

fte

n in

co

mp

ariso

n w

ith

ba

se s

tatist

ics,

inc

lud

ing

mis

sin

g

da

ta.

The

re a

re

min

ima

l e

rro

rs

an

d e

rro

rs a

re

pu

blis

he

d.

Sta

tist

ics

for

the

ye

ar

in p

rog

ress

are

co

mp

ara

ble

to t

he

sta

tist

ics

for

the

pre

vio

us

ye

ar

in m

ost

ca

ses.

The

sta

tist

ics

are

co

he

ren

t.

Qu

ality

Sta

tist

ics

Lev

el 4

Sta

tist

ics

are

alw

ays

co

mp

iled

on

th

e b

asi

s o

f

co

mm

on

sta

nd

ard

s.

Info

rma

tio

n o

n

sta

tist

ica

l

pro

ce

du

res

an

d

da

ta d

ictio

na

ry

are

ava

ilab

le.

Sta

tist

ics

are

alw

ays

co

nsi

ste

nt

an

d f

ollo

w t

he

sam

e p

rin

cip

les

an

d p

roc

ed

ure

s.

Sta

tist

ics

are

co

he

ren

t o

r

co

mp

atib

le o

ve

r

a m

axim

um

of

five

ye

ars

.

Sta

nd

ard

s

Sta

tist

ics

are

co

mp

iled

on

the

ba

sis

of

fixe

d

co

mm

on

sta

nd

ard

s.

Sta

tist

ics

are

co

nsi

ste

nt

ove

r tim

e.

Sta

tist

ics

are

co

he

ren

t o

ve

r

tim

e.

15

.1.1

15

.1.2

15

.1.3

Co

mp

on

en

ts

Co

he

ren

ce

an

d

co

nsi

ste

nc

y o

f

da

ta


61

On

ly s

tatist

ics

on

ad

min

istr

ative

en

titie

s c

an

be

co

mp

are

d.

Da

tab

ase

s a

re

sta

nd

alo

ne

an

d

ha

ve

little

or

no

links.

Na

tio

na

l st

atist

ics

are

no

t c

om

pa

red

with

oth

er

sta

tist

ica

l sy

ste

ms.

Lac

k o

f a

va

ilab

le

da

ta m

ake

s ro

bu

st

inte

rpre

tatio

n

diffic

ult.

NO

RM

AV

ER

AG

E

Sta

tist

ics

fro

m

diffe

ren

t so

urc

es

ca

n b

e

co

mp

are

d, b

ut

with

gre

at

diffic

ulty a

s it is

seld

om

do

ne

.

Na

tio

na

l st

atist

ics

are

ra

rely

co

mp

are

d w

ith

oth

er

sta

tist

ica

l

syst

em

s.

Two

ye

ars

’ d

ata

is a

va

ilab

le f

or

rob

ust

inte

rpre

tatio

n.

Sta

tist

ics

fro

m

diffe

ren

t so

urc

es

ca

n a

nd

are

, in

som

e c

ase

s,

co

mp

are

d.

Na

tio

na

l st

atist

ics

are

o

cc

asi

on

ally

co

mp

are

d w

ith

oth

er

na

tio

na

l

surv

eys

an

d

invo

lve

d in

inte

rna

tio

na

l a

nd

reg

ion

al

co

mp

ariso

ns

Thre

e y

ea

rs’

da

ta is

ava

ilab

le

for

rob

ust

inte

rpre

tatio

n.

Sta

tist

ics

are

co

mp

atib

le w

ith

oth

er

go

ve

rnm

en

t

da

tab

ase

s (s

uc

h

as

ce

ntr

al

sta

tist

ica

l

Off

ice

an

d o

the

r

go

ve

rnm

en

t

min

istr

ies)

thro

ug

h u

niq

ue

ide

ntifie

rs.

Co

mp

ariso

ns

are

ma

de

with

ho

use

ho

ld

surv

eys

wh

en

ne

ce

ssa

ry.

Cro

ss n

atio

na

l

co

mp

ara

bili

ty o

f

the

da

ta is

en

sure

d t

hro

ug

h

fre

qu

en

t

co

mp

ariso

ns

with

oth

er

inte

rna

tio

na

l

sta

tist

ics

(UIS

, A

U

Ou

tlo

ok

Da

tab

ase

) a

nd

reg

ion

al

ass

ess

me

nts

of

co

un

try s

tatist

ics.

Fiv

e y

ea

rs’

da

ta

is a

va

ilab

le f

or

rob

ust

inte

rpre

tatio

n.

Sta

tist

ics

fro

m

diffe

ren

t

min

istr

ies

ca

n

ea

sily

be

co

mp

are

d

ba

sed

on

. R

eg

ion

al

co

de

s,

. Sc

ho

ols

co

de

s,

. lo

ca

tio

n

co

ord

ina

tes

etc

.

Sta

tist

ics

are

co

mp

are

d

with

oth

er

sta

tist

ica

l

syst

em

s.

On

e s

et

of

da

ta t

o a

llow

for

rob

ust

inte

rpre

tatio

n.

15

.2.1

15

.3.1

15

.4.1

Co

mp

atib

ility

Co

mp

ari

son

with

oth

er

syst

em

s

Inte

rpre

tab

ility


62

NORM 16: ACCESSIBILITY AND CLARITY

Education statistics should be presented in a clear and understandable form, disseminated in a

suitable and convenient manner, available and accessible on an impartial basis with supporting

metadata and guidance.


63

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

Sta

tist

ics

lac

k

cla

rity

an

d a

re n

ot

an

aly

zed

.

Sta

tist

ica

l re

po

rt

no

t d

isse

min

ate

d.

The

re is

no

arr

an

ge

me

nt

to

pro

vid

e

info

rma

tio

n o

the

r

tha

n d

istr

ibu

tio

n o

f

an

nu

al st

atist

ica

l

rep

ort

s.

Use

rs a

re n

ot

info

rme

d a

bo

ut

the

sta

tist

ica

l p

roc

ess

es

an

d s

tatist

ica

l

ou

tpu

ts.

Qu

est

ion

ab

le

Sta

tist

ics

Lev

el 2

Sta

tist

ics

are

cle

arly p

rese

nte

d

bu

t w

ith

ou

t

an

aly

sis.

Lim

ite

d

dis

trib

utio

n u

sin

g

mo

de

rn

info

rma

tio

n a

nd

co

mm

un

ica

tio

n

tec

hn

olo

gie

s a

nd

ha

rdc

op

y

rep

ort

s.

The

re is

no

est

ab

lish

ed

arr

an

ge

me

nt

to

pro

vid

e

info

rma

tio

n t

o

use

rs. H

ow

eve

r, it

is c

om

mo

n t

o

co

op

era

te a

nd

pro

vid

e

info

rma

tio

n.

Use

rs a

re r

are

ly

info

rme

d t

hro

ug

h

pro

vis

ion

of

me

tad

ata

on

th

e

me

tho

do

log

y o

f

sta

tist

ica

l

pro

ce

sse

s a

nd

the

qu

alit

y o

f

sta

tist

ica

l

ou

tpu

ts.

Ac

ce

pta

ble

Sta

tist

ics

Lev

el 3

Sta

tist

ics

are

cle

arly

pre

sen

ted

bu

t

with

lim

ite

d

an

aly

sis.

Sta

tist

ica

l re

po

rts

are

dis

trib

ute

d

usi

ng

mo

de

rn

tec

hn

olo

gy

ma

inly

with

ha

rdc

op

y

rep

ort

s in

lim

ite

d

nu

mb

ers

.

Mo

st o

f th

e t

ime

the

re is

an

arr

an

ge

me

nt

to

pro

vid

e

info

rma

tio

n t

o

use

rs b

ut

the

dis

sem

ina

tio

n is

seld

om

cu

sto

miz

ed

to

the

ir n

ee

ds.

Use

rs a

re

som

etim

es

info

rme

d

thro

ug

h p

rovis

ion

of

me

tad

ata

on

the

me

tho

do

log

y o

f

sta

tist

ica

l

pro

ce

sse

s a

nd

the

qu

alit

y o

f

sta

tist

ica

l

ou

tpu

ts.

Qu

ality

Sta

tist

ics

Lev

el 4

Sta

tist

ics

are

an

aly

zed

an

d

pre

sen

ted

in

a

form

th

at

fac

ilita

tes

pro

pe

r

inte

rpre

tatio

n

an

d m

ea

nin

gfu

l

co

mp

ariso

ns.

Dis

sem

ina

tio

n

serv

ice

s u

se

mo

de

rn

info

rma

tio

n a

nd

co

mm

un

ica

tio

n

tec

hn

olo

gy a

nd

tra

ditio

na

l h

ard

co

py.

The

Min

istr

y

est

ab

lish

es

an

info

rma

tio

n d

esk

to c

ate

r fo

r u

sers

an

d c

ust

om

ize

s

its

dis

sem

ina

tio

n

of

an

nu

al

pu

blic

atio

ns

to

me

et

the

ne

ed

s

of

diffe

ren

t ta

rge

t

gro

up

s.

Use

rs a

re k

ep

t

info

rme

d t

hro

ug

h

pro

vis

ion

of

me

tad

ata

on

th

e

me

tho

do

log

y o

f

sta

tist

ica

l

pro

ce

sse

s a

nd

the

qu

alit

y o

f

sta

tist

ica

l

ou

tpu

ts.

Sta

nd

ard

s

The

sta

tist

ics

are

pre

sen

ted

in a

cle

ar

an

d

un

de

rsta

nd

a

ble

ma

nn

er.

An

nu

al

Sta

tist

ica

l

rep

ort

s

dis

sem

ina

ted

utiliz

ing

va

rio

us

me

tho

ds.

Re

gu

lar

dis

sem

ina

tio

n

stra

teg

y in

pla

ce

.

Use

rs a

re

info

rme

d

ab

ou

t th

e

sta

tist

ica

l

pro

ce

sse

s

an

d o

utp

uts

.

16

.1.1

16

.2.1

16

.2.2

16

.2.3

Co

mp

on

en

ts

Cla

rity

of

ed

uc

atio

n

sta

tist

ics

Dis

sem

ina

te o

n


64

Low

er

leve

ls o

f

go

ve

rnm

en

t

stru

ctu

res

do

no

t

rec

eiv

e a

nn

ua

l

sum

ma

ry s

tatist

ics

No

tra

inin

g o

n

an

aly

tic

al re

po

rtin

g

is p

rovid

ed

.

No

me

tad

ata

is

do

cu

me

nte

d a

nd

no

exp

lan

atio

n is

ava

ilab

le.

NO

RM

AV

ER

AG

E

Low

er

leve

ls o

f

go

ve

rnm

en

t

stru

ctu

res

rec

eiv

e

an

nu

al su

mm

ary

sta

tist

ics

som

e

tim

es.

Ad

ho

c t

rain

ing

on

an

aly

tic

al

rep

ort

ing

is

pro

vid

ed

to

som

e le

ve

ls.

No

fo

rma

l

do

cu

me

nta

tio

n

of

me

ta-d

ata

exis

ts b

ut

this

ca

n

be

exp

lain

ed

ve

rba

lly b

y E

MIS

pe

rso

nn

el.

Low

er

leve

ls o

f

go

ve

rnm

en

t

stru

ctu

res

rec

eiv

e a

nn

ua

l

sum

ma

ry

sta

tist

ics

mo

st o

f

the

tim

es.

An

nu

al tr

ain

ing

on

an

aly

tic

al

rep

ort

ing

is

pro

vid

ed

to

all

ce

ntr

al a

nd

low

er

leve

l EM

IS

pe

rso

nn

el.

An

ac

ce

pta

ble

leve

l o

f

do

cu

me

nta

tio

n

of

me

tad

ata

exis

ts. B

ut

do

cu

me

nta

tio

n

is in

co

mp

lete

.

Low

er

leve

ls o

f

go

ve

rnm

en

t

stru

ctu

res

alw

ays

rec

eiv

e o

ffic

ial o

r

pu

blis

he

d a

nn

ua

l

sum

ma

ry

sta

tist

ics

(bo

th

ac

tua

l a

nd

ind

ica

tor

sta

tist

ics)

ap

pro

pria

te t

o

the

ir a

rea

.

An

nu

al tr

ain

ing

on

an

aly

tic

al

rep

ort

ing

is

pro

vid

ed

to

all

EM

IS p

ers

on

ne

l a

t

all

leve

ls.

Do

cu

me

nta

tio

n

of

me

ta-d

ata

exis

ts o

n t

he

da

tab

ase

. Th

is

do

cu

me

nta

tio

n

inc

lud

es

a d

ata

dic

tio

na

ry a

nd

info

rma

tio

n o

n

ho

w t

he

sta

tist

ics

are

co

llec

ted

,

pro

du

ce

d a

nd

sto

red

.

An

aly

tic

al

rep

ort

s

pro

vid

ed

to

low

er

stru

ctu

res.

Re

gu

lar

tra

inin

g g

ive

n

for

EM

IS

pe

rso

nn

el a

t

low

er

leve

ls

on

an

aly

tic

al

rep

ort

ing

.

Do

cu

me

nta

ti

on

of

me

tad

ata

18

exis

ts.

16

.2.4

16

.2.5

16

.3.1

Me

tad

ata

18 Metadata is a description of your statistics and the methodological procedures being followed.


65

NORM 17: COMPREHENSIVENESS

Education statistics and information are published on all sectors of education and training.


66

Ass

ess

me

nt

Lev

els

of

the

Qu

ality

of

Sta

tist

ics

Co

mm

en

ts

Sc

ore

Po

or

Sta

tist

ics

Lev

el 1

The

an

nu

al

sta

tist

ica

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(s)

inc

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all

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. . Th

ese

are

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17

.1.1

17

.1.2

17

.2.1

Co

mp

on

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ts

Co

mp

reh

en

-

siv

e s

tatist

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ed

s

19 For e.g. completion rate, promotion rate, repetition rate, dropout rates, pass rate, teacher pupil ratio, textbook pupil ratio disaggregated by gender.


67

CONCLUSION

Developing and harmonizing effective statistical Norms and standards for the African Region in

creating a sustainable and efficient Higher Education MIS is a challenge that requires great

attention from African countries and Higher Education institutions. MIS decision-makers’

perception of EMIS relevance is an important aspect of supporting its development initiatives

and enhancing collaboration with HE partners.

This benchmarking framework recommends that the effective and efficient EMIS should be user-

friendly and accessible to all stakeholders. This means the framework is able to guide in

producing authentic data and information that meets stakeholders’ demands. It is the role of

EMIS to influence Higher Education and partners’ utilization of its outputs and promote an

institutional culture which values information sharing and use of scientific evidence for

educational planning, management and decision-making processes. It is expected that policy

makers and other stakeholders will use these Benchmarking tool and suggestions to improve

EMIS development strategies and enhance stakeholders’ partnership in matters pertaining to

strengthening EMIS functions, particularly in low-resource contexts.


68

ANNEXURE A: SCORING MATRIX Country…………………………… Date of Assessment………………………………………..

Please Tick where appropriate

Focus area Policy and legal framework Norm average

Focus Area A. Policy And Legal Framework Norm Average

Score

Norm 1. Mandate For Data Collection

Norm 2: Quality Commitment

Norm 3: Statistical Confidentiality

Norm 4: Reporting Accountability

Norm 5: Impartiality And Objectivity

Norm 6: Registration Of Institutions

Norm 7: Registration Of Learners

Focus Area Average

Focus Area B. Resources Availability And Utilisation Norm Average

Score

Norm 8: Adequate Resources

Norm 9: Cost Effectiveness

Focus Areas Average

Focus Area C. Statistical Processes Norm Average

Score

Norm 10: Sound Methodology And Appropriate Statistical Procedures

Norm 11: Non-Excessive Burden On Respondents

Focus Area Average


69

Focus Area D. Education Information Reporting Norm Average

Score

Norm 12: Relevance

Norm 13: Accuracy And Reliability

Norm 14: Timeliness And Punctuality

Norm 15: Coherence, Comparability And Integration

Norm 16: Accessibility And Clarity

Norm 17: Comprehensiveness

Focus Area Average

External Peer Team Assessment Country evaluation Other

Overall Average of all Standards

Add each score per standard and divide by 84 (total number of standards)

Overall Score


70

ANNEXURE B: EXTERNAL PEER RATING TEAM AND COUNTRY SCORING

MATRIX

The Ministry of Education and Peer Review Team engage in joint discussions and reach a

consensus on ranking. In cases where the country assessment and the peer assessment differ

significantly and no consensus on scoring is reached the two scores shall be averaged with the

country score constituting 45% and the Peer Review Team 60%.

Focus Area A. Policy And Legal Framework Country Score

Peer Review

Team Score

Average

Score

Norm 1. Mandate For Data Collection

Norm 2: Quality Commitment

Norm 3: Statistical Confidentiality

Norm 4: Reporting Accountability

Norm 5: Impartiality And Objectivity

Norm 6: Registration Of Institutions

Norm 7: Registration Of Learners

Focus Area Average

Focus Area B. Resources Availability And

Utilisation Country Score

Peer Review

Team Score

Average Score

Norm 8: Adequate Resources

Norm 9: Cost Effectiveness

Focus Areas Average

Focus Area C. Statistical Processes Country Score

Peer Review

Team Score

Average Score

Norm 10: Sound Methodology And Appropriate

Statistical Procedures

Norm 11: Non-Excessive Burden On

Respondents

Focus Area Average


71

Focus Area D. Education Information Reporting Country Score

Peer Review

Team Score

Average Score

Norm 12: Relevance

Norm 13: Accuracy And Reliability

Norm 14: Timeliness And Punctuality

Norm 15: Coherence, Comparability And

Integration

Norm 16: Accessibility And Clarity

Norm 17: Comprehensiveness

Focus Area Average


72

REFERENCES

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2. Leo L. Pipino, Yang W. Lee and Richard Y. Wang (2002) Data Quality Assessment,

Communication of the ACM April

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Accessed October 2010

4. Principles Governing International Statistical Activities.

5. Statistics Finland. Guidelines of Professional Ethics.

6. Statistics South Africa (2008). South African Quality Assessment Framework (SASQAF). First

Edition. National Statistical System. Republic of South Africa.

7. Statistics South Africa (2010). South African Quality Assessment Framework (SASQAF). Second

Edition. National Statistical System. Republic of South Africa.

8. Statistics South Africa (2010). South African Quality Assessment Framework (SASQAF).

Operational standards and guidelines. First Edition. National Statistical System. Republic of

South Africa.

9. Statistics Norway. Ethics and Statistics.

10. Statistics UK. National Statistics Code of Practice.

11. UNESCO Institute of Statistics (2008). Data Quality Assessment Framework (DQAF).

Unpublished.

12. CDS Almanacs or the 2014 CDS Benchmarking Report

13. European Statistics Code of Practice - revised edition 2011ISBN: 978-92-79-21679-

4http://ec.europa.eu/eurostat/web/quality/european-statistics-code-of-practice. Assessed

September, 2017.

Facilitated and Printed By

Association for the Development of Education in Africa (ADEA)

Working Group on Education Management and Policy Support

8 Kenilworth Road

Newlands, Harare

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DEVELOPMENT AND HARMONIZATION OF EFFECTIVE … · very difficult to get comprehensive and exhaustive statistics. The development of an effective Higher Education Management Information