DIGITAL GOVERNANCE OF THE NATIONAL HIGHER EDUCATION RANKING: AN AI-BASED MONITORING ARCHITECTURE

Authors

  • Mamajonova Mukhlisakhon Muzaffar kizi

DOI:

https://doi.org/10.5281/zenodo.22091057

Abstract

This article examines the national ranking of higher education institutions in Uzbekistan from the perspective of
digital governance: not what the ranking measures, but how its indicators can be produced, verified, and monitored. The
2026 regulation establishes 25 indicators and links ranking outcomes to strategic and funding decisions, yet it leaves the
data infrastructure behind the ranking undefined, and current practice relies on an annual campaign of manual reporting.
Using document analysis of the indicator formulas and a design science approach, the study first maps every indicator
to its primary data elements, source system, and update cadence, and then classifies the indicators into three automation-
readiness tiers. The results show that 76 of the 100 ranking points rest on administrative registers and external
machine-readable databases rather than surveys, and that between 57 and 65 points, depending on institutional category,
can be generated fully automatically from data already maintained in existing digital systems. On this basis, the article
proposes a four-layer monitoring architecture - source systems, an interoperability layer, an analytics and artificial intelligence
layer, and a governance interface - and assigns concrete AI functions to specific indicators: rule-based validation,
cross-source verification, anomaly detection, and short-term forecasting. The discussion identifies four governance risks
of such a system, including data-quality failures and metric gaming, and formulates safeguards for each.

Keywords

digital governance, higher education, national ranking, education management information systems, data governance, artificial intelligence in the public sector, monitoring architecture.

Author Biography

Mamajonova Mukhlisakhon Muzaffar kizi

PhD in Economics, Senior Lecturer
Tashkent State University of Economics, Tashkent, Uzbekistan


References

Regulation “On maintaining the national ranking of higher education institutions”, approved by Order No. 8 of 6

February 2026 of the Director of the National Agency for Quality Assurance in Education under the Administration of the

President of the Republic of Uzbekistan (registration No. 10/26/3783/0179, 2 March 2026). URL: https://lex.uz/docs/8067678

Decree of the President of the Republic of Uzbekistan No. PF-58 of 10 April 2026 “On additional measures to

improve the system of higher education, science and innovation” https://lex.uz/uz/docs/-8129755.

Decree of the President of the Republic of Uzbekistan No. DP-6079 of 5 October 2020 “On approval of the Strategy

‘Digital Uzbekistan - 2030’ and measures for its effective implementation” https://lex.uz/docs/5030957.

Dunleavy P., Margetts H., Bastow S., Tinkler J. New public management is dead - long live digital-era governance

// Journal of Public Administration Research and Theory. - 2006. - Vol. 16, No. 3. - P. 467-494.

Margetts H., Dunleavy P. The second wave of digital-era governance: a quasi-paradigm for government on the web

// Philosophical Transactions of the Royal Society A. - 2013. - Vol. 371, No. 1987. - 20120382.

Janowski T. Digital government evolution: From transformation to contextualization // Government Information

Quarterly. - 2015. - Vol. 32, No. 3. - P. 221-236.

Mergel I., Edelmann N., Haug N. Defining digital transformation: Results from expert interviews // Government

Information Quarterly. - 2019. - Vol. 36, No. 4. - 101385.

OECD. The OECD Digital Government Policy Framework: Six dimensions of a digital government. OECD Public

Governance Policy Papers No. 02. - Paris: OECD Publishing, 2020.

European Commission. New European Interoperability Framework: Promoting seamless services and data flows

for European public administrations. - Luxembourg: Publications Office of the European Union, 2017.

Wirtz B.W., Weyerer J.C., Geyer C. Artificial intelligence and the public sector - applications and challenges //

International Journal of Public Administration. - 2019. - Vol. 42, No. 7. - P. 596-615.

Zuiderwijk A., Chen Y.-C., Salem F. Implications of the use of artificial intelligence in public governance: A systematic

literature review and a research agenda // Government Information Quarterly. - 2021. - Vol. 38, No. 3. - 101577.

Sun T.Q., Medaglia R. Mapping the challenges of artificial intelligence in the public sector: Evidence from public

healthcare // Government Information Quarterly. - 2019. - Vol. 36, No. 2. - P. 368-383.

Khatri V., Brown C.V. Designing data governance // Communications of the ACM. - 2010. - Vol. 53, No. 1. - P.

-152.

Otto B. Data governance // Business & Information Systems Engineering. - 2011. - Vol. 3, No. 4. - P. 241-244.

Wang R.Y., Strong D.M. Beyond accuracy: What data quality means to data consumers // Journal of Management

Information Systems. - 1996. - Vol. 12, No. 4. - P. 5-33.

ISO 8000-61:2016. Data quality - Part 61: Data quality management: Process reference model. - Geneva:

International Organization for Standardization, 2016.

ISO/IEC 25012:2008. Software engineering - Software product Quality Requirements and Evaluation (SQuaRE)

- Data quality model. - Geneva: International Organization for Standardization, 2008.

Abdul-Hamid H. What Matters Most for Education Management Information Systems: A Framework Paper. SABER

Working Paper Series No. 7. - Washington, DC: The World Bank, 2014.

UNESCO Institute for Statistics. SDG 4 Data Digest 2019: How to Produce and Use the Global and Thematic

Education Indicators. - Montreal: UIS, 2019.

Hazelkorn E. Rankings and the Reshaping of Higher Education: The Battle for World-Class Excellence. 2nd ed. -

London: Palgrave Macmillan, 2015. - 304 p.

Espeland W.N., Sauder M. Rankings and reactivity: How public measures recreate social worlds // American

Journal of Sociology. - 2007. - Vol. 113, No. 1. - P. 1-40.

Power M. The Audit Society: Rituals of Verification. - Oxford: Oxford University Press, 1997. - 208 p.

Muller J.Z. The Tyranny of Metrics. - Princeton: Princeton University Press, 2018. - 240 p.

Campbell D.T. Assessing the impact of planned social change // Evaluation and Program Planning. - 1979. - Vol.

, No. 1. - P. 67-90.

Strathern M. ‘Improving ratings’: audit in the British University system // European Review. - 1997. - Vol. 5, No. 3.

- P. 305-321.

Bevan G., Hood C. What’s measured is what matters: Targets and gaming in the English public health care system

// Public Administration. - 2006. - Vol. 84, No. 3. - P. 517-538.

Hevner A.R., March S.T., Park J., Ram S. Design science in information systems research // MIS Quarterly. - 2004.

- Vol. 28, No. 1. - P. 75-105.

Peffers K., Tuunanen T., Rothenberger M.A., Chatterjee S. A design science research methodology for information

systems research // Journal of Management Information Systems. - 2007. - Vol. 24, No. 3. - P. 45-77.

Gregor S., Hevner A.R. Positioning and presenting design science research for maximum impact // MIS Quarterly.

- 2013. - Vol. 37, No. 2. - P. 337-355.

Bowen G.A. Document analysis as a qualitative research method // Qualitative Research Journal. - 2009. - Vol.

, No. 2. - P. 27-40.

Chandola V., Banerjee A., Kumar V. Anomaly detection: A survey // ACM Computing Surveys. - 2009. - Vol. 41,

No. 3. - Article 15.

Hyndman R.J., Athanasopoulos G. Forecasting: Principles and Practice. 3rd ed. - Melbourne: OTexts, 2021.

Baas J., Schotten M., Plume A., Côté G., Karimi R. Scopus as a curated, high-quality bibliometric data source

for academic research in quantitative science studies // Quantitative Science Studies. - 2020. - Vol. 1, No. 1. - P. 377-386.

Haak L.L., Fenner M., Paglione L., Pentz E., Ratner H. ORCID: a system to uniquely identify researchers //

Learned Publishing. - 2012. - Vol. 25, No. 4. - P. 259-264.

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Published

2026-08-01

How to Cite

Mamajonova , M. (2026). DIGITAL GOVERNANCE OF THE NATIONAL HIGHER EDUCATION RANKING: AN AI-BASED MONITORING ARCHITECTURE. Innovation Science and Technology, 2(8), 73–82. https://doi.org/10.5281/zenodo.22091057
Vol. 2 No. 8 (2026): Innovation Science and Technology