智慧學校推動、資料導向決策與教師專業發展關係之研究

Abstract

本研究旨在探討智慧學校推動、資料導向決策與教師專業發展之現況，並分析不同背景變項之教師知覺智慧學校推動、資料導向決策與教師專業發展之差異情形與線性關係。\n本研究採用問卷調查法，研究對象為臺灣中小學智慧學校的教師，共寄發582份問卷，回收的有效問卷共有494份，有效問卷回收率為84.87%。本研究以描述性統計、獨立樣本t檢定、單因子變異數分析及結構方程模式 (SEM) 進行統計分析，並使用IBM SPSS Statistics 26.0 及LISREL 8.80 為資料分析軟體，獲得結論如下：\n壹、智慧學校推動量表信效度良好。\n貳、中小學智慧學校推動現況良好，「科技創新」較佳，「教材準備」較低。\n參、中小學資料導向決策現況良好，「資料探究文化」較佳，「資料與科技素養」較低。\n肆、中小學教師專業發展現況良好，「課程教學實踐」較佳，「社群互動分享」較低。\n伍、不同年齡、教育程度、學校設置智慧教室比率之教師在知覺智慧學校推動無顯著差異。\n陸、不同性別、服務年資、現任職務、學校類別、學校規模之教師在知覺智慧學校推動有顯著差異。\n柒、不同性別、教育程度、學校類別、學校設置智慧教室比率之教師在知覺資料導向決策無顯著差異。\n捌、不同年齡、服務年資、現任職務、學校規模之教師在知覺資料導向決策有顯著差異。\n玖、不同性別、教育程度、學校類別、學校設置智慧教室比率之教師在知覺教師專業發展無顯著差異。\n拾、不同年齡、服務年資、現任職務、學校規模之教師在知覺教師專業發展有顯著差異。\n壹拾壹、整體模式適配度良好，智慧學校推動可透過資料導向決策的中介作用，正向影響教師專業發展\n本研究根據上述結論，提出具體建議，做為教育行政機關、學校與校內教師以及未來研究作為參考。

The purpose of this study is to understand the situation and to analyze the\ndifferences and linear relations of smart school promotion, data driven decision\nmaking and teacher professional development.\nIn this study, a questionnaire survey method was employed. The subjects of the\nstudy were teachers from secondary and primary smart schools in Taiwan. A total of 582 questionnaires were distributed, 494 valid questionnaires were collected, and the effective questionnaire return rate was 84.87%. The data were analyzed by data analysis software, IBM SPSS Statistics 26.0 and LISREL 8.80, using descriptive statistics, independent sample t-test, one-way ANOVA, and structural equation modeling (SEM). The conclusions of this study are as follows:\n1. The reliability and validity of the scale “Smart School Promotion” are fine.\n2. The current states of smart school promotion in secondary and primary school are still good. “Technology innovation” is the highest, and “teaching material\npreparation” is the lowest.\n3. The current states of data driven decision making in secondary and primary\nschools are still good. “Data-inquiry culture” is the highest, and “data and\ntechnology literacy” is the lowest.\n4. The current states of teacher professional development in secondary and primary schools are still good. “Practice of course teaching” is the highest, and\n“community interaction and sharing” is the lowest.\n5. For all teachers of different ages, educational backgrounds, and percentage of\nsmart classroom setting, show no significant differences on teachers’ perceptions\nof smart school promotion.\n6. For all teachers of different genders, in-service years, administrative duties, types of school and school sizes show the significant differences on teachers’\nperceptions of smart school promotion.\n7. For all teachers of genders, educational backgrounds, types of school and\npercentage of smart classroom setting show no significant differences on teachers’perceptions of data driven decision making.\n8. For all teachers of different ages, in-service years, administrative duties and school sizes show the significant differences on teachers’ perceptions of data driven decision making.\n9. For all teachers of genders, educational backgrounds, types of school and\npercentage of smart classroom setting show no significant differences on teachers’perceptions of teacher professional development.\n10. For all teachers of different ages, in-service years, administrative duties and school sizes show the significant differences on teachers’ perceptions of teacher\nprofessional development.\n11. The model fits well, and the positive effect of smart school promotion on teacher professional development could be moderated by data driven decision making.\nBased on the above conclusions, this study makes specific recommendations and\nserves as a reference for educational administration, school teachers, and future\nresearch.