Opening the Black Box: A practitioner’s guide to Artificial Intelligence and Machine Learning in assessment (Part 1)
| Autor: | Bao Sheng (Aiden) Loe, Mark Abrahams, Philippa Riley |
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| Rok vydání: | 2018 |
| Zdroj: | Assessment and Development Matters. 10:29-33 |
| ISSN: | 2752-8111 2040-4069 |
| DOI: | 10.53841/bpsadm.2018.10.2.29 |
| Popis: | Key digested messageThe use of machine learning (ML) and Artificial Intelligence (AI) is beginning to impact the assessment of human characteristics across a number of domains. Assessment practitioners are increasingly presented with assessments which purport to be‘ML or AI scored’, as well as new approaches to assessment design which previously used psychometrics. Computer-driven scoring can appear opaque and confusing to the assessment user who is unlikely to understand why or how a score is derived.In the first of two articles, we explain what is and is not machine learning, and how it differs from psychometric approaches and Artificial Intelligence. The second part will build on this to guide assessment practitioners on the questions to ask and issues to consider when deciding whether to use ML-based assessment, as well as signposting some jargon used by data scientists. |
| Databáze: | OpenAIRE |
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