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Let the algorithm decide?

Published: 24 May 2021 Publication History

Abstract

Algorithms fail their first test to replace student exams.

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  • (2024)Explainable Artificial Intelligence for Academic Performance Prediction. An Experimental Study on the Impact of Accuracy and Simplicity of Decision Trees on Causability and Fairness PerceptionsProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658953(1031-1042)Online publication date: 3-Jun-2024
  • (2024)Diverging perceptions of artificial intelligence in higher education: A comparison of student and public assessments on risks and damages of academic performance prediction in GermanyComputers and Education: Artificial Intelligence10.1016/j.caeai.2024.1003057(100305)Online publication date: Dec-2024
  • (2023)“The algorithm will screw you”: Blame, social actors and the 2020 A Level results algorithm on TwitterPLOS ONE10.1371/journal.pone.028866218:7(e0288662)Online publication date: 26-Jul-2023
  • Show More Cited By

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Published In

cover image Communications of the ACM
Communications of the ACM  Volume 64, Issue 6
June 2021
106 pages
ISSN:0001-0782
EISSN:1557-7317
DOI:10.1145/3467845
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 May 2021
Published in CACM Volume 64, Issue 6

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Cited By

View all
  • (2024)Explainable Artificial Intelligence for Academic Performance Prediction. An Experimental Study on the Impact of Accuracy and Simplicity of Decision Trees on Causability and Fairness PerceptionsProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658953(1031-1042)Online publication date: 3-Jun-2024
  • (2024)Diverging perceptions of artificial intelligence in higher education: A comparison of student and public assessments on risks and damages of academic performance prediction in GermanyComputers and Education: Artificial Intelligence10.1016/j.caeai.2024.1003057(100305)Online publication date: Dec-2024
  • (2023)“The algorithm will screw you”: Blame, social actors and the 2020 A Level results algorithm on TwitterPLOS ONE10.1371/journal.pone.028866218:7(e0288662)Online publication date: 26-Jul-2023
  • (2023)Living with AlgorithmsFrom Algorithms to Thinking Machines10.1145/3603178.3603184Online publication date: 19-Oct-2023
  • (2023)Trust or mistrust in algorithmic grading? An embedded agency perspectiveInternational Journal of Information Management: The Journal for Information Professionals10.1016/j.ijinfomgt.2022.10255569:COnline publication date: 1-Apr-2023
  • (2023)Fairness of Academic Performance Prediction for the Distribution of Support Measures for Students: Differences in Perceived Fairness of Distributive Justice NormsTechnology, Knowledge and Learning10.1007/s10758-023-09698-y29:2(1079-1107)Online publication date: 11-Nov-2023
  • (2023)From Algorithms to Thinking MachinesundefinedOnline publication date: 19-Oct-2023

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