• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.753-762
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• 2020

With an increasing interest in integrating artificial intelligence (AI) into interview processes, the Republic of Korea (ROK) army is trying to lead and analyze AI-powered interview platform. This study is to analyze the AI interview data using a unified non-crossing multiple quantile tree (UNQRT) model. Compared to the UNQRT, the existing models, such as quantile regression and quantile regression tree model (QRT), are inadequate for the analysis of AI interview data. Specially, the linearity assumption of the quantile regression is overly strong for the aforementioned application. While the QRT model seems to be applicable by relaxing the linearity assumption, it suffers from crossing problems among estimated quantile functions and leads to an uninterpretable model. The UNQRT circumvents the crossing problem of quantile functions by simultaneously estimating multiple quantile functions with a non-crossing constraint and is robust from extreme quantiles. Furthermore, the single tree construction from the UNQRT leads to an interpretable model compared to the QRT model. In this study, by using the UNQRT, we explored the relationship between the results of the Army AI interview system and the existing personnel data to derive meaningful results.

• Education of Primary School Mathematics
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• v.16 no.1
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• pp.35-55
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• 2013

The purposes of this study were to development and verify the effect of educational program apply on STEAM for the mathematical prodigy. To accomplish these purposes literature review on development of the program and qualitative study were conducted. The mixed-model design was applied for this qualitative experimental study. The conclusions of this study were as follows. First, the program for mathematical prodigy education applied on the conceptual model of STEAM integration approach was developed. Second, a learning satisfaction about constitution of the workbook was lowly. Third, principal of STEAM was the best interest and difficult of the program applied on STEAM. Fourth, the creativity and problem solving ability was founded about angle and velocity of mathematical domain and making the Angrybirds Game on GeoGebra environment. In spite of difficulty about principal of the Angrybirds Game, confidence and satisfaction were founded about a result product.