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    题名: 以反事實架構角度推估因果效應：2000年至2023年臺灣教育研究領域相關期刊論文之擇要回顧
    Estimating Causal Effects with the Counterfactual Framework: A Selected Review of Journal Articles in Educational Research from Taiwan (2000-2023)
    作者: 關秉寅;彭思錦
    Kuan, Ping-Yin;Peng, Ssu-Chin
    贡献者: 社科院
    关键词: 科學為本的教育研究;隨機化實驗;反事實因果推論;潛在結果模型
    Scientifically-based educational research;Randomized trials;Counterfactual causal inference;Potential outcome models
    日期: 2024-09
    上传时间: 2024-10-25 10:08:16 (UTC+8)
    摘要: 本文回顧2000年至2023年台灣教育研究應用與反事實因果推論架構相關之經驗研究的期刊論文。本文第一節簡要回顧了美國倡議教育研究以「科學為本」之歷史。第二節則探討隨機化實驗做為研究設計的「黃金標準」與潛在結果模型的關連，並說明以觀察性研究資料從事反事實因果推論的策略。第三節就以發表於TSSCI第一級教育學門期刊為主，其他學門及國外相關期刊論文為輔的57篇論文為基礎，擇要回顧台灣教育研究使用各類符合反事實因果推論架構方法的情況。文獻回顧發現台灣的教育研究並不缺乏實驗設計的經驗研究，但這些研究屬於小規模準實驗設計，且以課程或教學活動為主。其次，台灣雖然沒有大型實驗設計的研究，但過往二、三十年業已出現各種大型重複性橫斷面調查及長期追蹤資料庫，讓研究者得以使用符合反事實因果推論的各類統計模型，以模擬實驗設計的角度，探索各項教育政策或措施之影響的議題。本文最後一節除建議未來教育研究的方向應推動大規模實地教育研究實驗外，也討論了結構方式模型與反事實因果推論架構間關係的議題。
    This article selectively reviews educational research papers in Taiwan from 2000 to 2023 that utilized methods consistent with counterfactual causal inference frameworks. The first section briefly examines the history of the United States advocating for educational research to be "scientifically based." The second section explores the relationship between randomized experimental trials as the "gold standard" in research design and potential outcome models. It also elucidates strategies for counterfactual causal inference using observational research data. The third section focuses on 57 papers published mainly in first-tier educational journals in Taiwan. It selectively introduces studies using various statistical methods that conform to the counterfactual causal inference framework. The literature review finds that Taiwan's educational research is not lacking in empirical studies with experimental design. However, these studies primarily utilize small-scale quasi-experimental designs focusing on curriculum or teaching activities. Furthermore, while Taiwan lacks large-scale experimental educational research, various long-scale repeated cross-sectional surveys and longitudinal data have emerged over the past two or three decades. These datasets enable researchers to employ various statistical models that conform to counterfactual causal inference, facilitating experimental design simulation and exploration of the impact of various educational policy issues. In addition to recommending future directions for educational research to promote large-scale field experiments, the final section of this article also discusses issues on the relationship between structural equation modeling and the counterfactual causal inference framework.
    關聯: 中國統計學報, Vol.62, No.3, pp.222-262
    数据类型: article
    DOI: 10.29973/JCSA
    显示于类别:[社會科學學院] 期刊論文

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