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“What are they not telling me?” Learning machine learning: Understanding the challenges for novices

Cinca, Robert; Costanza, Enrico; Musolesi, Mirco; Alebri, Muna; (2025) “What are they not telling me?” Learning machine learning: Understanding the challenges for novices. International Journal of Human-Computer Studies , 196 , Article 103438. 10.1016/j.ijhcs.2024.103438. Green open access

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Abstract

Machine Learning (ML) is increasingly accessible to users with limited knowledge of its theoretical foundations. However, misapplying it can lead to negative consequences. This paper reports on a qualitative study designed to reveal challenges that novices encounter when learning about basic ML concepts and building their first models. Twenty participants were introduced to fundamental ML concepts for classification through an interactive tutorial involving an off-the-shelf GUI application, built their own ML model for a shape gesture dataset, and participated in a semi-structured interview. A thematic analysis revealed insights into these challenges, particularly around problem selection and multi-dimensionality, but also around what constitutes ML, algorithm selection, cross-validation, and interpreting visualizations. Despite these and other misconceptions, participants reflected on good model building practices, discussing that algorithm selection might require knowledge and context and that input features may introduce bias. We discuss the findings’ implications for the design of ML tools for novices.

Type: Article
Title: “What are they not telling me?” Learning machine learning: Understanding the challenges for novices
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.ijhcs.2024.103438
Publisher version: https://doi.org/10.1016/j.ijhcs.2024.103438
Language: English
Additional information: Copyright © 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Learning machine learning; Machine learning; Explainable AI; Algorithms; Visualization; Black-box
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > UCL Interaction Centre
URI: https://discovery.ucl.ac.uk/id/eprint/10208636
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