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<https://discovery.ucl.ac.uk/id/eprint/10206159> <http://purl.org/dc/terms/title> "Understanding Interaction with Machine Learning through\r\na Thematic Analysis Coding Assistant: A User Study"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10206159> <http://purl.org/ontology/bibo/abstract> "Interactive Machine Learning (ML) enables users, including non-experts in ML, to iteratively train and improve\r\nML models. However, limited research has been reported on how non-experts interact with these systems.\r\nFocusing on thematic analysis as a practical application, we report on a user study where 20 participants\r\ninteracted with TACA, a functioning Interactive ML tool. Thematic analysis involves individual interpretation\r\nof ambiguous data, hence it is suited for and can benefit from the iterative customization of models supported\r\nby Interactive ML. Through a combination of interaction logs and semi-structured interviews, our findings\r\nrevealed that, by using TACA, participants critically reflected on their analysis, gained new thematic insights,\r\nand adapted their interpretative stance. We also document misconceptions of ML concepts, positivist views,\r\nand personal blame for poor model performance. We then discuss how applications could be designed to\r\nimprove the understanding of Interactive ML concepts and foster reflexive work practices."^^<http://www.w3.org/2001/XMLSchema#string> .
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