A hierarchical reasoning graph neural network for the automatic scoring of answer transcriptions in video job interviews

Chen, Kai; Niu, Meng; Chen, Qingcai

doi:10.1007/s13042-022-01540-8

Cited by 3 publications

(1 citation statement)

References 31 publications

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“…However, this "black box" or "dustbowl" empiricism can be problematic when issues arise in practice and there is no clear understanding of the mechanisms driving the effectiveness of various assessment and development techniques (Pam, 2020). For instance, multiple innovations within assessment and development have been put into practice while lacking explanatory theory (Lievens & Thornton, 2005); including speed assessments (Herde & Lievens, 2020), automatic scoring of job candidate essays and interviews (Campion et al, 2016;Chen et al, 2022), and asynchronous assessment (Lukacik et al, 2022). These modern practices may seem more resource-efficient than traditional methods.…”

Section: Research and Practice Converge (But Not Theory)mentioning

confidence: 99%

An epistemology for assessment and development: How do we know what we know?

Rupp,

Thornton,

Bisbey

et al. 2024

Ind. Organ. Psychol.

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To make informed decisions, assessment theorists, researchers, and practitioners can evaluate the overlap among (1) relevant theories, (2) empirical contributions, and (3) best practices. Unfortunately, such a task may seem daunting due to the so-called science-practice gap, which can thwart collaboration among these parties. This paper presents an epistemology for delineating the importance of integrating these three sources of knowledge. We then apply this epistemology to show that our current knowledge of assessment and development topics are well integrated in some places, but still quite lacking in others.

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Section: Research and Practice Converge (But Not Theory)mentioning

confidence: 99%

An epistemology for assessment and development: How do we know what we know?

Rupp,

Thornton,

Bisbey

et al. 2024

Ind. Organ. Psychol.

View full text Add to dashboard Cite

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Better job application systems: Objectively assessing measures of job performance from asynchronous video interviews

Pentland,

Wang,

Twyman

2025

Information & Management

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A Weighted Bonferroni-OWA Operator Based Cumulative Belief Degree Approach to Personnel Selection Based on Automated Video Interview Assessment Data

Asan

Soyer

2022

Mathematics

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Asynchronous Video Interviewing (AVI) is considered one of the most recent and promising innovations in the recruitment process. Using AVI in combination with AI-based technologies enables recruiters/employers to automate many of the tasks that are typically required for screening, assessing, and selecting candidates. In fact, the automated assessment and selection process is a complex and uncertain problem involving highly subjective, multiple interrelated criteria. In order to address these issues, an effective and practical approach is proposed that is able to transform, weight, combine, and rank automated AVI assessments obtained through AI technologies and machine learning. The suggested approach combines Cumulative Belief Structures with the Weighted Bonferroni-OWA operator, which allows (i) aggregating assessment scores obtained in different forms and scales; (ii) incorporating interrelationships between criteria into the analysis (iii) considering accuracies of the learning algorithms as weights of criteria; and (iv) weighting criteria objectively. The proposed approach ensures a completely data-driven and efficient approach to the personnel selection process. To justify the effectiveness and applicability of the suggested approach, an example case is presented in which the new approach is compared to classical MCDM techniques.

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A hierarchical reasoning graph neural network for the automatic scoring of answer transcriptions in video job interviews

Cited by 3 publications

References 31 publications

An epistemology for assessment and development: How do we know what we know?

An epistemology for assessment and development: How do we know what we know?

Better job application systems: Objectively assessing measures of job performance from asynchronous video interviews

A Weighted Bonferroni-OWA Operator Based Cumulative Belief Degree Approach to Personnel Selection Based on Automated Video Interview Assessment Data

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