教師教學創新的跨國性比較：三種跨國性大數據分析方法的比較與介紹

本研究透過TALIS2018國際資料庫進行15個國家在教師教學創新的跨國性比較，並透過貝氏隨機效果模型、貝氏近似測量恆等，以及校準三種不同大數據分析方法，比較教師教學創新的跨國差異。研究發現，過往的精確測量恆等性分析並不適合使用在教師教學創新的跨國比較。而貝氏隨機效果模型、貝氏近似測量恆等及校準方法，可有效估計教師教學創新的跨國差異，值得推廣使用。此外，經由排序比較發現，臺灣教師在教學創新上仍有許多可以進步之處...

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Published inJiao yu yu xin li yan jiu Vol. 48; no. 1; pp. 037 - 063
Main Author 曾明基(Ming-Chi Tseng)
Format Journal Article
LanguageChinese
Published 台灣 國立政治大學教育學院 01.03.2025
Subjects
Bayesian approximate measurement invariance
Bayesian random effect model
calibration
TALIS 2018
teacher teaching innovation
TSSCI
教師教學創新
校準
貝氏近似測量恆等
貝氏隨機效果模型
貝氏近似測量恆等
教師教學創新
校準
Bayesian random effect model
TALIS 2018
貝氏隨機效果模型
Bayesian approximate measurement invariance
teacher teaching innovation
TSSCI
calibration
Online AccessGet full text
ISSN1024-9885

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Abstract 本研究透過TALIS2018國際資料庫進行15個國家在教師教學創新的跨國性比較，並透過貝氏隨機效果模型、貝氏近似測量恆等，以及校準三種不同大數據分析方法，比較教師教學創新的跨國差異。研究發現，過往的精確測量恆等性分析並不適合使用在教師教學創新的跨國比較。而貝氏隨機效果模型、貝氏近似測量恆等及校準方法，可有效估計教師教學創新的跨國差異，值得推廣使用。此外，經由排序比較發現，臺灣教師在教學創新上仍有許多可以進步之處
Research Motivation and Objective ＜br＞ The primary objective of this study is clear: To conduct a transnational comparison of teaching innovation among teachers across 15 countries, using the TALIS 2018 international database. This research aims to explore the differences in teaching innovation across these countries. To achieve this, the study employs three advanced big data analysis methods developed in recent years within the field of testing and assessment: Bayesian random effects models (Asparouhov ＆ Muthén, 2016; De Jong et al., 2007; Fox, 2010; Verhagen ＆ Fox, 2012), Bayesian approximate measurement invariance (Muthén ＆ Asparouhov, 2012, 2018), and Calibration (Asparouhov ＆ Muthén, 2014, 2022; Muthén ＆ Asparouhov, 2014, 2018). This research makes a definitive comparison of teaching innovation across
AbstractList 本研究透過TALIS2018國際資料庫進行15個國家在教師教學創新的跨國性比較，並透過貝氏隨機效果模型、貝氏近似測量恆等，以及校準三種不同大數據分析方法，比較教師教學創新的跨國差異。研究發現，過往的精確測量恆等性分析並不適合使用在教師教學創新的跨國比較。而貝氏隨機效果模型、貝氏近似測量恆等及校準方法，可有效估計教師教學創新的跨國差異，值得推廣使用。此外，經由排序比較發現，臺灣教師在教學創新上仍有許多可以進步之處
Author 曾明基(Ming-Chi Tseng)
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Keywords 貝氏近似測量恆等
教師教學創新
校準
Bayesian random effect model
TALIS 2018
貝氏隨機效果模型
Bayesian approximate measurement invariance
teacher teaching innovation
TSSCI
calibration
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Notes 1、原為年刊，第20期(民86年6月)起改為半年刊，第26卷第1期(民92年3月)起再改為季刊
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SubjectTerms Bayesian approximate measurement invariance
Bayesian random effect model
calibration
TALIS 2018
teacher teaching innovation
TSSCI
教師教學創新
校準
貝氏近似測量恆等
貝氏隨機效果模型
Title 教師教學創新的跨國性比較：三種跨國性大數據分析方法的比較與介紹
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