國中數學補習行為與數學學習成就研究

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2023

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本研究旨在探討影響國中學生數學補習行為與數學學習成就之因素,探究不同背景變項與因素對於國中學生參與數學補習行為與數學學習成就之差異情形,分析數學補習行為與數學學習成就之關係,並了解各項因素對於數學補習行為與數學學習成就之預測情形。本研究採用次級資料庫分析之方式,研究資料來源取自「後期中等教育長期追蹤資料庫」中的「106 學年度高一(專一)新生調查問卷」作為研究工具,針對106學年度高一(專一)新生進行普查,本研究有效樣本為7939份,再以敘述性統計、卡方檢定、t檢定、單因子變異數分析、多元迴歸分析、二元邏輯迴歸進形統計分析。本研究結果如下所述:1. 性別為「女性」、父母最高學歷為「大學、專科」、家庭經濟狀況為「小康」的同學參與數學補習的比例最高。2. 家庭經濟狀況「富裕」的同學,每週參與數學補習的時間最多;父母教育程度為「高中(職)以下」的同學,參與數學補習的時間顯著低於其他各組。3. 「數學學習動機」越強、「數學焦慮」越高、「數學學習習慣」越好的同學,在參與數學補習的比例與時間上顯著高於低分組同學。4. 教師願意使用高度「教師教學策略」的同學,在參與數學補習的比例顯著高於低分組同學;教師使用高度「多元教學方法」的同學,在參與數學補習的比例上顯著低於低分組同學。5. 在二元邏輯迴歸模型中,學生的「背景變項」相較於「數學學習態度」與「教師教學效能」對於「是否參加數學補習」有較強的預測正確率(62.1%)與解釋力。6. 在數學學業表現上,父母教育程度「碩士以上」、家庭經濟狀況「小康」的同學顯著高於其他各組;在數學素養表現上「男性」、家庭經濟狀況「富裕」表現較佳,父母教育程度「高中以下」則顯著低於其他各組。7. 「數學學習動機」越強、「數學學習習慣」越好的同學,在數學學業成績或素養表現上均顯著優於低分組同學;「數學焦慮」越高的同學,在數學學業成績或素養表現上均顯著低於焦慮感較低的同學。8. 在學業成績上,教師採用高度「教師教學策略」的同學,在數學會考成績上表現較佳;採用高度「多元教學方法」的同學,在數學會考成績表現上較差;在數學素養表現上,教師使用高度「教師教學策略」與「多元教學方法」的同學,在數學素養表現上均高於低分組同學。9. 「有參與數學補習」且「每週參與3-4小時」校外數學課程的學生在數學會考成績上表現最佳。10. 在多元迴歸模型中,「數學學習態度」相較於其他變項對於「數學會考成績」與「數學素養表現」的影響最為顯著,解釋力也最強。
This study aims to explore the factors influencing the cram school attendance and academic achievement in mathematics of junior high school students. It investigates the differences that cram school attendance and academic achievement in mathematics of junior high school students will make among different background variables and factors the students have. The study analyzes the relationship between cram school attendance and academic achievement in mathematics and seeks to understand the predictive nature of various factors on cram school attendance and academic achievement in mathematics.  This study utilized a secondary database analysis approach, with research data sourced from the"Freshman Survey Questionnaire for the 106th Academic Year (Grade 10)" of “Taiwan Upper Secondary Database." The survey was conducted on 10th graders in the 106th academic year. The study's effective sample consisted of 7,939 participants. Descriptive statistics, chi-square test, t-tests, one-way analysis of variance (ANOVA), multiple regression analysis, and binary logistic regression were employed for statistical analysis. The findings of this study are as follows: 1. The highest proportion of cram school attendance in mathematics was observed among students who were “female”, had parents with a highest education level of"university or college," and belonged to a "moderate" family economic status. 2. Students from "affluent" family economic backgrounds spent the most time per week taking cram school classes in mathematics. On the other hand, students whose parents' education level was "below high school (vocational)" significantly spent less time taking cram school classes in mathematics compared to other groups. 3. Students with stronger "mathematics learning motivation," higher "mathematics anxiety," and better "mathematics learning habits" exhibited significantly higher proportions and duration of cram school attendance in mathematics compared to students in the lower scoring groups. 4. Students whose teachers were willing to adopted high degree of "teacher instructional strategies" exhibited a significantly higher proportion of cram school attendance in mathematics compared to students in the low scoring groups. Conversely, students whose teachers used a high degree of "diverse teaching methods" had a significantly lower proportion of cram school attendance in mathematics compared to students in the low scoring groups.5. In the binary logistic regression model, compared to"mathematics learning attitudes" and "teacher instructional efficacy," students' "background variables" demonstrated a stronger predictive accuracy (62.1%) and explanatory power for "taking cram school classes in mathematics." 6. In terms of mathematics academic performance, students with parents who had an education level of "master's degree or above" and belonged to a "moderate" family economic status significantly outperformed other groups. In terms of mathematical literacy performance, "male" students and students from "affluent" family economic backgrounds performed better, while students with parents' education level "below high school" significantly performed lower than other groups. 7. Students with stronger "learning motivation toward mathematics" and better "learning habits relating to mathematics" demonstrated significantly better academic performance and mathematical literacy compared to students in the low scoring groups. On the other hand, students with higher levels of "mathematics anxiety" exhibited significantly lower academic performance and mathematical literacy compared to students with lower anxiety levels. 8. In terms of academic performance, students whose teachers employed a high degree of "teacher instructional strategies" performed better in mathematics on Senior High School Entrance Examination. However, students whose teachers utilized a high degree of "diverse teaching methods" had poorer performance in mathematics on Senior High School Entrance Examination. Regarding mathematical literacy performance, students whose teachers used a high degree of"teacher instructional strategies" or "diverse teaching methods" outperformed students in the low scoring groups. 9. Students who “take cram school classes in mathematics” and engaged in extracurricular mathematics courses for "3-4 hours per week" demonstrated the best performance in mathematics on Senior High School Entrance Examination. 10. In the multiple regression model, "learning attitudes toward mathematics" exhibited the most significant impact and had the strongest explanatory power on"mathematics scores on Senior High School Entrance Examination" and "mathematical literacy performance" compared to other variables.

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數學補習, 數學學習態度, 數學學習成就, cram school attendance in mathematics, learning attitudes toward mathematics, academic achievement in mathematics

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