Sun-bok Lee

A dropout early warning system enables schools to preemptively identify students who are at risk of dropping out of school, to promptly react to them, and eventually to help potential dropout students to continue their learning for a better future. However, the inherent class imbalance between dropout and non-dropout students could pose difficulty in building accurate predictive modeling for a dropout early warning system. The present study aimed to improve the performance of a dropout early war

In vivo detection and quantification of cells labeled with superparamagnetic iron oxide (SPIO) nanoparticles has been attracting increasing attention. In particular, positive contrast methods, such as susceptibility gradient mapping (SGM) and phase gradient mapping (PGM), have been proposed for the improved detection of SPIO nanoparticles. In this study, a different implementation of the PGM method is introduced; it calculates the phase gradient in the image space using a fast Fourier transform

This study aims to identify the Philippines teachers’ concerns in K–12 implementation. The Concerns Based Adoption Model was applied to determine the level of concerns, and the Stages of Concern Questionnaire has been administered to 400 teachers. Findings indicate that consequence and collaboration was the teachers’ current concern (impact stage). Furthermore, experience and education factors showed the biggest significance affecting their collaboration among teachers. These current concerns ma

본 연구는 2022 개정 교육과정 정책의 쟁점을 분석하기 위해 텍스트마이닝(text mining) 기법을 활용하여 뉴스 기사를 분석한 것이다. 언론매체의 관심도를 확인하기 위한 버즈 분석(buzz analysis)과 뉴스 기사의 키워드 빈도 분석 그리고 토픽모델링의 대표적인 기법인 잠재 디리클레 할당(Latent Direichlet Allocation, LDA) 기법을 활용하여 정책의 쟁점을 분석하였다. 버즈 분석과 키워드 빈도 분석 결과, 첫째, 국내 주요 언론매체의 관심도는 정책 형성 단계의 초·중반에는 관련 보도가 거의 없다가 교과별 공청회 개최 전후로 급상승하였다. 둘째, 국내 주요 언론매체는 ’고교학점제’와 ‘역사 교과서의 자유민주주의 용어’ 논란에 집중한다는 점이 확인되었다. LDA 분석 결과, 2022 개정 교육과정 정책의 쟁점은 ① 고교학점제 전면 도입, ② 역사 교과에 ‘자유민주주의’ 용어 논란, ③ 미래 지향적 교육과정과 디지털 환경, ④ 선택교과 확대와 국·영·수

The logistic regression (LR) procedure for testing differential item functioning (DIF) typically depends on the asymptotic sampling distributions. The likelihood ratio test (LRT) usually relies on the asymptotic chi-square distribution. Also, the Wald test is typically based on the asymptotic normality of the maximum likelihood (ML) estimation, and the Wald statistic is tested using the asymptotic chi-square distribution. However, in small samples, the asymptotic assumptions may not work well. T

The present study focused on parents' social cue use in relation to young children's attention. Participants were ten parent-child dyads; all children were 36 to 60 months old and were either typically developing (TD) or were diagnosed with autism spectrum disorder (ASD). Children wore a head-mounted camera that recorded the proximate child view while their parent played with them. The study compared the following between the TD and ASD groups: (a) frequency of parent's gesture use; (b) parents'

Distinguishing between ordinal and disordinal interaction in multiple regression is useful in testing many interesting theoretical hypotheses. Because the distinction is made based on the location of a crossover point of 2 simple regression lines, confidence intervals of the crossover point can be used to distinguish ordinal and disordinal interactions. This study examined 2 factors that need to be considered in constructing confidence intervals of the crossover point: (a) the assumption about t

A Monte Carlo simulation study is an essential tool for examining the behavior of various models in structural equation modeling (SEM). Recently, the tidyverse package in R is gaining popularity for data science because of its efficient data manipulation, exploration, and visualization capabilities. This article introduces how to write more parsimonious, readable, maintainable, and parallelizable R simulation codes using the tidyverse package. Specifically, this article (a) introduces some key f

맞춤형 학습은 교육이 지향해야 할 궁극적인 방향이라고 할 수 있으며 오래전부터 많은 연구자가 맞춤형 학습을 구현하기 위해 노력해 왔다. 하지만 맞춤형 학습에 대한 오랜 관심과 기대에도 불구하고 인간 교수자가 대규모 학습자를 대상으로 맞춤형 학습을 제공하는 것은 시간과 자원의 제약으로 인해 현실적으로 어려운 일이었다. 이러한 문제에 대한 해결책으로 기술 기반 맞춤형 학습이 주목받아 왔으며 최근 인공지능 기술이 발전함에 따라 인공지능을 활용한 맞춤형 학습의 구현에 대한 기대가 그 어느 때보다도 높아지고 있다. 지능형 튜터링 시스템은 맞춤형 학습을 제공하기 위한 인공지능 기반 컴퓨터 시스템으로 지능형 튜터링 시스템에 대한 전반적인 이해는 현재 인공지능을 활용해 맞춤형 학습을 구현하고자 하는 많은 연구와 개발에 도움을 줄 수 있을 것이다. 맞춤형 학습을 위한 지능형 튜터링 시스템에 관한 관심과 기대가 높아지고 있는 이때 우리는 우리가 원하는 진정한 맞춤형 학습의 의미를 돌아보고, 지능형 튜

A Monte Carlo simulation study is an essential tool for evaluating the behavior of various quantitative methods including structural equation modeling (SEM) under various conditions. Typically, a large number of replications are recommended for a Monte Carlo simulation study, and therefore automating a Monte Carlo simulation study is important to get the desired number of replications for a simulation study. This article is intended to provide concrete examples for automating a Monte Carlo simul

Confidence intervals for an effect size can provide the information about the magnitude of an effect and its precision as well as the binary decision about the existence of an effect. In this study, the performances of five different methods for constructing confidence intervals for ratio effect size measures of an indirect effect were compared in terms of power, coverage rates, Type I error rates, and widths of confidence intervals. The five methods include the percentile bootstrap method, the