TASK- AND NON-TASK-SPECIFIC FACTORS CLASSIFYING PROBLEM-SOLVING EXPERTS AND NOVICES: COMPARING STUDENTS OF THE TOP TEN HIGH-PERFORMING EASTERN AND WESTERN ECONOMIES IN PISA 2012

區分問題解決專家和新手的任務和非任務特定因素：比較PISA 2012前十名東西方經濟體學生之表現

金松麗(Songli Jin) ； 張國祥(Kwok-Cheung Cheung) ； 薛寶嫦(Pou-Seong Sit)

《當代教育研究季刊》 25卷3期 (2017/09) Pp. 71-103

https://doi.org/10.6151/CERQ.2017.2503.03

摘要

Purpose The purpose of this study is to make use of the computer-generated log files to derive task-specific indicator variables of problem-solving processes of an exemplary problem task (TRAFFIC) to examine factors of relative importance and thereby classify and differentiate high-performing problem-solving experts from low-performing problem-solving novices. Added to the task-specific indicators are non-task-specific variables collated from questionnaires administered in the Programme for International Student Assessment (PISA) 2012 study. Design/methodology/approach The participants are 2,651 fifteen-year-old high-performing problem-solving experts and low-performing problem-solving novices who have responded to the TRAFFIC problem task coming from the top ten high-performing economies in the PISA 2012 digital problem-solving study. The educational data mining tool Classification and Regression Tree (CART) is the main analytic technique used. Factors found for the students of the top ten high-performing Eastern economies are compared with those of high-performing Western economies. Findings The factors affecting student performance in Eastern and Western high-performing economies share commonalities and differences. In the Eastern economies, the factors identified in descending order of relative importance are: Discovery of the optimal solution path of the problem task, mathematics self-efficacy, and experience with pure mathematics tasks at school. In the Western economies, the factors identified in descending order of relative importance are: Mathematics self- efficacy, discovery of the optimal solution path of the problem task, familiarity with mathematical concepts, and mathematics work ethics. Originality/value Based on the findings, educational practitioners may be informed how to design problem-based learning (PBL) in their respective economies. Furthermore, it is hoped that the methodologies developed are useful in furnishing new ideas to the future studies of digital problem solving.

關鍵字

problem solving ； educational data mining ； log file ； classification and regression tree (CART) ； PISA

並列摘要

研究目的：本研究旨在利用電腦生成的log 文檔探索「交通」這道題解難過程中的任務特定指標變量，然後加上整理自「學生能力國際評估計劃（PISA）2012」問卷資料的非任務特定變量，檢視區分高表現問題解決專家和低表現問題解決新手有哪些相對重要的因素。研究設計／方法／取徑：本研究在PISA 2012電子問題解決測試排名前十名的高表現經濟體的15歲學生中，選取參與回答「交通」這一道題的高表現問題解決專家和低表現問題解決新手，人數合共2,651名。接著將學生分為東方高表現經濟體組和西方高表現經濟體組，分別以教育數據探勘工具「分類與回歸樹」作為主要的分析技術，找出區分高表現問題解決專家和低表現問題解決新手的因素，並將影響東方高表現經濟體和西方高表現經濟體學生表現的因素進行比較。研究發現或結論：影響東方高表現經濟體和西方高表現經濟體學生表現的因素有同有異。在東方經濟體中，探索出的影響因素按重要性排序依次為：找到任務的最佳解決路徑，數學自我效能感，和在學校中完成純數學任務的體驗。在西方經濟體中，結果依次為：數學自我效能感，找到任務的最佳解決路徑，熟悉數學概念，和數學中的敬業態度。研究原創性／價值性：根據研究結果，有助教育工作者在各自的環境中設計基於問題的學習方案。此外，本研究的分析方法，亦能夠為未來的電子問題解決研究提供新的思路。

並列關鍵字

問題解決 ； 教育數據探勘 ； log文檔 ； 分類與回歸樹 ； PISA

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