Automatic identification of storytelling responses to past‐behavior interview questions via machine learning
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29 mars 2023
- handle: 10670/1.vd8j7g
- hal: hal-04131007
- doi: 10.1111/ijsa.12428
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info:eu-repo/semantics/altIdentifier/doi/10.1111/ijsa.12428
http://creativecommons.org/licenses/by-nc/ , info:eu-repo/semantics/OpenAccess
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Field guides Keys (Identification guides) Identification guides Story-telling Telling of stories Competence Learning, Machine Forensic identification AlgorismCiter ce document
Adrian Bangerter et al., « Automatic identification of storytelling responses to past‐behavior interview questions via machine learning », HALSHS : archive ouverte en Sciences de l’Homme et de la Société, ID : 10.1111/ijsa.12428
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Résumé
Structured interviews often feature past-behavior questions, where applicants are asked to tell a story about past work experience. Applicants often experience difficulties producing such stories. Automatic analyses of applicant behavior in responding to past-behavior questions may constitute a basis for delivering feedback and thus helping them improve their performance. We used machine learning algorithms to predict storytelling in transcribed speech of participants responding to past-behavior questions in a simulated selection interview. Responses were coded as to whether they featured a story or not. For each story, utterances were also manually coded as to whether they described the situation, the task/action performed, or results obtained. The algorithms predicted whether a response features a story or not (best accuracy: 78%), as well as the count of situation, task/action, and response utterances. These findings contribute to better automatic identification of verbal responses to past-behavior questions and may support automatic provision of feedback to applicants about their interview performance.