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No Right Answer: A Feasibility Study of Essay Assessment with LDA


Abstract Essay scoring is a difficult and contentious business. The problem is exacerbated when there are no “right” answers for the essay prompts. This research developed a simple toolset for essay analysis by integrating a freely available Latent Dirichlet Allocation (LDA) implementation into a homegrown assessment assistant. The complexity of the essay assessment problem is demonstrated and illustrated with a representative collection of open-ended essays. This research also explores the use of “expert vectors” or “keyword essays” for maximizing the utility of LDA with small corpora. While, by itself, LDA appears insufficient for adequately scoring essays, it is quite capable of classifying responses to open-ended essay prompts and providing insi... (more)
Contributor Roberts, Tom (Author)
Series Research Project Report Series
Identifier Stock Number: ASU-SSEBE-CESEM-2013-RPR-005
Copyright
Reuse Permissions All Rights Reserved
Collaborating Institutions School of Sustainable Engineering and the Built Environment (SSEBE) / Center for Earth Systems Engineering and Management
Additional Formats MODS / OAI Dublin Core / RIS


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