Datasets:
id int64 1 5 | document stringclasses 5
values | issuer stringclasses 4
values | year int64 2.02k 2.03k | governance_form stringclasses 5
values | primary_emphasis stringclasses 5
values | question_for_comparison stringclasses 5
values |
|---|---|---|---|---|---|---|
1 | Global Education Monitoring Report 2023: Technology in Education - A Tool on Whose Terms? | UNESCO | 2,023 | Global monitoring report | Relevance, equity, evidence, sustainability | What counts as educational benefit and whose needs define it? |
2 | OECD Digital Education Outlook 2023: Towards an Effective Digital Education Ecosystem | OECD | 2,023 | Comparative policy analysis | Data governance, privacy, interoperability, procurement | Who controls educational data and infrastructure? |
3 | Guidance for Generative AI in Education and Research | UNESCO | 2,023 | International guidance | Human-centered, privacy-conscious, age-appropriate use | How are educational purpose and human judgment preserved? |
4 | Regulation (EU) 2024/1689 (Artificial Intelligence Act) | European Parliament and Council of the EU | 2,024 | Regional binding regulation | Risk-based requirements, including certain education uses | Which educational uses are treated as high risk and why? |
5 | Guidance on AI and Children Version 3.0 | UNICEF Office of Research-Innocenti | 2,025 | Child-rights policy guidance | Safety, privacy, fairness, transparency, accountability | How are children's rights and interests incorporated? |
Algorithmic Governance and Comparative Education in Times of Polycrisis
Digital Monitoring, Institutional Compliance, and Educational Systems
Companion materials for a book chapter by Vivien Jiaqian Zhu (UC Berkeley), prepared for the forthcoming IntechOpen volume Comparative Education in Times of Polycrisis – Deconstruction of the Field? (Education and Human Development series; academic editor Ana Ancheta Arrabal; co-editors Alicia Sianes-Bautista and Tania Fátima Gómez Sánchez). The chapter is in preparation; this repository will be updated when it is published.
Summary
The chapter treats algorithmic governance as a sociotechnical arrangement through which educational institutions collect data, classify learners, evaluate performance, allocate resources, and demonstrate accountability. Using deconstruction as a method and polycrisis as context, it argues that educational indicators are not neutral descriptions of pre-existing realities: their definitions and uses shape what institutions recognize as achievement, risk, and legitimate performance. It proposes a five-dimensional framework for comparing how education systems govern digital monitoring and compliance.
Contents
| File | Description |
|---|---|
corpus.csv |
The five policy documents in the chapter's purposive, document-based comparison (Table 1 of the chapter). |
framework.csv |
The five comparative dimensions, with core questions, possible evidence, and analytical risks (Table 2). |
IntechOpen-Chapter_Proposal_Review_Report.pdf |
IntechOpen's chapter proposal review report (September 29, 2026), recording acceptance of the proposal for inclusion. Definitive acceptance depends on full chapter review. This document is IntechOpen's and is not covered by the CC BY 4.0 license of the rest of this repository. |
Framework dimensions
- Problem definition
- Data infrastructure
- Classification and intervention
- Accountability
- Distribution and agency
Method and scope
Document-based comparative policy analysis. Each document was read against five questions: what educational problem it identifies; what data, systems, or actors become objects of governance; what oversight, disclosure, or risk-management mechanisms it proposes or requires; who is responsible for decisions and remedies; and how equity, contextual variation, and the agency of learners and educators are addressed.
Limitations
- The corpus is small and purposive, not representative of all national policies.
- The documents differ in legal status and function (monitoring report, policy synthesis, guidance, binding regulation, child-rights framework) and are not treated as equivalent.
- The framework is interpretive, not a scoring instrument. It does not evaluate compliance in specific schools or countries, and policy texts are not evidence of implementation.
Related work
- The Corporate Stage (interactive demo of algorithmic workplace surveillance): https://huggingface.co/spaces/jvzhu/the-corporate-stage
Citation
@incollection{zhu2027algorithmic,
author = {Zhu, Vivien Jiaqian},
title = {Algorithmic Governance and Comparative Education in Times of Polycrisis: Digital Monitoring, Institutional Compliance, and Educational Systems},
booktitle = {Comparative Education in Times of Polycrisis -- Deconstruction of the Field?},
publisher = {IntechOpen},
address = {London},
year = {2027},
note = {Forthcoming}
}
Contact
- Downloads last month
- 41