ERIC Number: EJ1351808
Record Type: Journal
Publication Date: 2022-Nov
Pages: 13
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1525-822X
EISSN: EISSN-1552-3969
A Machine Learning Model Helps Process Interviewer Comments in Computer-Assisted Personal Interview Instruments: A Case Study
Billington, Catherine; Rivero, Gonzalo; Jannett, Andrew; Chen, Jiating
Field Methods, v34 n4 p275-287 Nov 2022
During data collection, field interviewers often append notes or comments to a case in open text fields to request updates to case-level data. Processing these comments can improve data quality, but many are non-actionable, and processing remains a costly manual task. This article presents a case study using a novel application of machine learning tools to assist in the evaluation of these comments. Using over 5,000 comments from the Medical Expenditure Panel Survey, we built features that were fed to a machine learning model to predict a grouping category for each comment as previously assigned by data technicians to expedite processing. The model achieved high top-3 accuracy and was incorporated into a production tool for editing. A qualitative evaluation of the tool also provided encouraging results. This application of machine learning tools allowed a small but worthwhile increase in processing efficiency, while maintaining exacting standards for data quality.
Descriptors: Artificial Intelligence, Interviews, Data Collection, Notetaking, Computer Mediated Communication, Accuracy, Man Machine Systems, Natural Language Processing
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A