Leveraging natural language processing to support automated assessment and feedback for student open responses in mathematics

Background Teachers often rely on the use of open‐ended questions to assess students' conceptual understanding of assigned content. Particularly in the context of mathematics; teachers use these types of questions to gain insight into the processes and strategies adopted by students in solving...

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Veröffentlicht in:	Journal of computer assisted learning Jg. 39; H. 3; S. 823 - 840
Hauptverfasser:	Botelho, Anthony, Baral, Sami, Erickson, John A., Benachamardi, Priyanka, Heffernan, Neil T.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Chichester, UK John Wiley & Sons, Inc 01.06.2023 Wiley Wiley Subscription Services, Inc
Schlagworte:	Academic Achievement Artificial Intelligence automated assessment Automation Computer Assisted Testing Distance learning Domains Electronic Learning Error analysis Error Analysis (Language) Feedback Feedback (Response) feedback recommendation Language Processing Machine learning Mathematical analysis Mathematics Mathematics Achievement Mathematics Education Mathematics Tests Natural Language Processing open responses Performance prediction Prediction Questions Semantics sentence embeddings similarity Student Evaluation Student Journals Students Teachers Teaching Methods Test Format
ISSN:	0266-4909, 1365-2729
Online-Zugang:	Volltext
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