When Postal Codes Matter More Than Studying: Algorithms as Arbiters of Fair Assessment
- Kristjan Kikerpill
, - Andra Siibak,
- Maris Männiste
Abstract
During the Covid-19 pandemic, educational systems around the world became heavily reliant on data-intensive technologies and algorithmic decision-making systems. In the UK, concerns over grade inflation for A-levels qualifications led the overseeing authority to using a grading algorithm in the hopes of providing objective, neutral and fair assessment. In reality, the algorithm displayed bias by downgrading nearly 36% of the grades of students coming from more marginalised groups, resulting in an ‘A-levels fiasco’.
We applied a critical discursive psychology approach to explore how students, teachers, parents and policymakers impacted by algorithm-based grading expressed and relied on different senses of fairness (formal, implied contractual, relational, retributive) when commenting on the incident in international news media (N=329).
Our findings indicate that while the affected agents evoked and clung to different senses of fairness, the algorithm itself also emerged as a meta-agent of fairness in the discursive constructs of social reality. The analysis further illustrates how public authorities held overly optimistic and techno-solutionist imaginaries about the neutrality and objectivity of AI-based systems, revealing a crucial need for oversight bodies that guide public institutions in responsibly deploying safe and trustworthy data technologies.
Keywords
algorithms, education, assessment, algorithmic grade, critical discursive psychology
Author Biography
Kristjan Kikerpill
Kristjan Kikerpill is a lecturer in Information Law and Digital Sociology at the Institute of Social Studies, University of Tartu, Estonia. His main research areas are the social and communicative aspects of cybercrime and critical data studies with a focus on privacy and surveillance in everyday life.
Andra Siibak
Andra Siibak is a Professor of Media Studies and Deputy Head of Research at the Institute of Social Studies, University of Tartu, Estonia. Her research focuses on the opportunities and risks associated with the use of AI-based technologies and the internet. Together with Giovanna Mascheroni she has co authored “Datafied Childhoods: Data Practices and Imaginaries in Children’s Lives” (Peter Lang, 2021), and “Children and AI: Changing Digital Childhoods” (Palgrave, 2026). She serves as Governing Body member for the European Communication Research and Education Association (ECREA) and is currently the Vice President of the Association of Internet Researchers (AoIR).
Maris Männiste
Maris Männiste is a lecturer in Critical Data Studies at the Institute of Social Studies, University of Tartu, Estonia. Her research focuses on the intersection of critical data and algorithm studies, media and communication, and public administration, with a particular emphasis on welfare automation. She investigates how data-driven and automated decision-making in welfare services reshapes citizen-state relations and what challenges increasing automation poses at individual, institutional and societal levels. Her work also engages with the datafication of education and the use of artificial intelligence in educational contexts, examining how similar dynamics unfold across domains.