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題名：學生數學學習策略及目標取向與數學成就關聯之縱貫性探討：潛藏轉移模型分析取向
作者：蔡宗憲
作者(外文)：TSAI,TSUNG-HSIEN
校院名稱：國立臺南大學
系所名稱：教育學系測驗統計博士班
指導教授：林素微
學位類別：博士
出版日期：2022
主題關鍵詞：學習意向；目標取向；學習策略；數學成就；潛藏轉移模型；learning disposition；goal orientation；learning strategies；mathematics achievement；Latent Transition Analysis
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大量研究表明，學生的數學成績與學習策略和目標取向有關。然而，很少有研究調查這些變量在學生成績之間的關聯。由於縱向數據收集的難度，大多數研究主要是橫斷面的一次性數據收集，但這可能會忽略時間因素和學習過程中的變化。本研究使用臺灣花蓮教育長期資料庫 2017 年、2018 年和 2019 年數學成就測試的數據。樣本為 1500 名五年級到七年級的學生，探討數學成績、目標取向和學習策略隨時間的變化。在本研究中，研究人員將目標取向和學習策略統稱為學習意向，並對數學學習意向與成就之間的關係進行縱向研究。除了討論每個年級的潛在類別數量外，本研究還使用潛在轉換模型分析 (LTA) 來評估學習意向和數學成績之間的動態關係，並將時間因素納入估計值。
研究結果發現，每個年級的學習意向可以分為三個潛在類別。 A 積極表現、精熟取向具有精緻化策略特質學生。 B類是表現積極、精熟取向和控制學習策略的學生。最後，C 類是學生放棄學習或被動表現取向，採取被動記憶學習策略。 LTA分析結果發現，性別與學習意向有關，不同傾向的學生數學成績不同。將三個年級的數學成績量表等化後顯示，這三個類別的平均成績在六年級最高，在七年級呈下降趨勢。研究發現，在跨年級學習過程中，許多學生的學習意向發生了變化。本研究表明，考慮時間影響的縱向分析比橫斷面數據分析更為精確和實用，並為未來數學教育的學習和教學提出了相關建議。
Numerous studies have shown that students' math performance is related to learning strategies and goal orientation. However, few studies have investigated the association among these variables across students' grades. Due to the difficulty of longitudinal data collection, most studies were mainly cross-sectional with one-time data collection, but this might ignore the time factor and change in the learning process. This study uses data from a county's 2017, 2018, and 2019 mathematics achievement tests in the Taiwan Education Long-Term Database. Exploring change over time of math achievement, goal orientation, and learning strategies for 1,500 students in grades five through seven. In this study, researchers collectively refer to goal orientations and learning strategies as learning dispositions and conduct a longitudinal study on the relationship between mathematics learning dispositions and achievement. In addition to discussing the number of latent categories for each grade level, this study used a Latent Transition Model Analysis (LTA) to assess the dynamic relationship between learning disposition and mathematics achievement, incorporating the time factor into the estimates (Collins & Lanza, 2009). The study results found that learning disposition can be divided into three potential categories in each grade. Category A is students with positive performance, mastery orientation, and elaborative learning strategies. Category B is students with positive performance, mastery orientation, and control learning strategies. Finally, category C is students giving up in learning or passive performance orientation and taking passive memorization learning strategies. The results of the LTA analysis found that gender was associated with learning disposition, and students with different dispositions had different math achievements. After equating the mathematics achievement scales of the three grades, it showed that the average performance of these three categories was the highest in the sixth grade and showed a downward trend in the seventh grade. It found that their learning disposition changed in lots of students in the cross-grade learning process. This study shows that the longitudinal analysis considering the influence of time is more precise and practical than the cross-sectional data analysis and proposes relevant suggestions for future study and instruction in mathematics education.
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