本研究旨在探討臺北市國民小學資料導向決定與回應式介入的現況，以及資料導向決定與回應式介入之關係為何。本研究採問卷調查法，研究工具為自編之「臺北市國民小學資料導向決定與回應式介入調查問卷」，以臺北市公立國民小學144所學校教師為對象進行調查研究，抽取其中46校教師共670名，回收有效樣本數為435份。問卷回收後，分別以描述性統計、t考驗、單因子變異數分析、皮爾遜積差相關、逐步多元迴歸等方法進行資料分析，以了解教師知覺資料導向決定與回應式介入之情形。本研究所獲致之結論如下：

一、 臺北市國民小學教師知覺資料導向決定與回應式介入屬良好程度。
二、 教師知覺資料導向決定不會因其個人背景變項(性別、年齡、服務年資、最高學歷、專業背景)而有所不同。
三、 教師知覺資料導向決定會因為其個人背景變項(現任職務、學校規模、學校歷史)而有所不同。
四、 教師知覺回應式介入不會因個人背景變項(年齡、服務年資、最高學歷、專業背景)而有所不同。
五、 教師知覺回應式介入會因其背景變項(性別、現任職務、學校規模、學校歷史)而有所不同
六、 臺北市國民小學教師知覺資料導向決定與回應式介入具有正向的關係存在
七、 資料導向決定能對回應式介入有正向地預測，其中尤以「文化風氣層面」最有預測力

最後根據上述研究結論，分別對主管教育行政機關、學校及後續研究提出具體建議。

關鍵詞：國民小學、資料導向決定、回應式介入

he purpose of this study is to investigate the current situation of elementary school teacher’s perception of data-driven decision making and response to intervention and the relationship between these two variables. For the purpose of this study, a questionnaire was employed to survey 670 teachers in 46 public elementary schools in Taipei City, and 435 valid samples. The data was analyzed by using descriptive statistics, t-test, one way ANOVA, Pearson correlation, and stepwise multiple regression analysis to analyze teacher’s perception of data-driven decision making and response to intervention, and their relationship was also examined. The findings of this study follow:
I. The overall rating toward elementary school teacher’s perception of data-driven decision making and response to intervention is “good”.
II. Elementary school teacher’s perception of data-driven decision making did not cause any differences by different personal variables (sex, ages, seniority, the academic, and professional background).
III. Teacher’s perception of data-driven decision making did cause a differences by different personal variables (position, school scale, and school history).
IV. Teacher’s perception of response to intervention did not cause any differences by different personal variables (ages, seniority, the academic, and professional background).
Ⅴ. Teacher’s perception of response to intervention did cause a differences by different personal variables (sex, position, school scale, and school history).
Ⅵ. The correlation between data-driven decision making and response to intervention of elementary school Teacher’s perception is positive in Taipei City.
Ⅶ. Teacher’s perception of data-driven decision making has positive prediction to response to intervention, and the ”organizational culture and personal habit’ is the most predictive dimension.

Based on the findings, some suggestions were drawn for the administrative agency, elementary schools, and the further research as well.

Key words：elementary school, data-driven decision making, response to intervention

第一章 緒論
第一節 研究背景與動機
第二節 研究目的與待答問題
第三節 名詞釋義
第四節 研究方法與步驟
第五節 研究範圍與限制
第二章 文獻探討
第一節 資料導向決定之重要概念與立論基礎
第二節 回應式介入之重要概念與立論基礎
第三節 資料導向決定與回應式介入之相關研究
第三章 研究設計與實施
第一節 研究架構
第二節 研究對象
第三節 研究工具
第四節 實施程序
第五節 資料處理
第四章 研究結果分析與討論
第一節 教師知覺資料導向決定現況之分析
第二節 教師知覺回應式介入現況之分析
第三節 資料導向決定與回應式介入之關係
第四節 綜合討論
第五章 結論與建議
第一節 結論
第二節 建議
參考文獻 ……………………………………………………………………
壹、 中文部分
貳、 英文部分………………………………………………………
附 錄 ……………………………………………………………………
附錄一、臺北市國民小學資料導向決定與回應式介
入調查問卷【專家內容效度問卷】…………
附錄二、臺北市國民小學資料導向決定與回應式介
入調查問卷【預試問卷】……………………
附錄三、臺北市國民小學資料導向決定與回應式介
入調查問卷【正式問卷】……………………

參考文獻
一、中文部分
王世英、謝雅惠 (2005)。從資料驅動決定觀點簡介國立教育資料館
教育資源。教育資料與研究，67，37-51。
王如哲 (2001)。論教育領域的知識管理。教育政策論壇，5(1)，21-39。
王保進 (2006)。中文視窗版SPSS 與行為科學研究。臺北市：心理。
王淑惠 (2008)。普通班教師如何因應介入反應效果模式。國教新知，
55(4)，57-63。
吳怡慧 (2008)。國小專任輔導教師在學情障融合教育的角色定位。
國教新知，55(4)，43-56。
吳美燕 (2008)。教學反應模式在鑑定國小四年級閱讀障礙學生可行
性之研究(未出版碩士論文)，臺北市立教育大學，臺北市。
吳明隆、涂金堂 (2005)。SPSS 與統計應用分析(第二版)。臺北市：
五南。
吳金香 (2002)。學校組織行為與管理。臺北市：五南。
吳政達 (2002)。知識管理與學校行政。教育資料與研究，45，25-30。
吳清山 (2000)。學校行政。臺北市：心理。
吳清山 (2003)。知識經濟與教育發展。臺北市：師大書苑。
吳清山 (2008)。教育行政議題研究。臺北市：高等教育。
吳清山 (2009)。教育111 的理念。教師天地，160，10-16。
吳清山 (2010)。臺灣學校革新的回顧與展望。蔡培村(主持)，新世紀
學校革新之挑戰與展望國際研討會，臺北市。
吳清山、林天祐 (2004)。教育小辭書。臺北市：國立教育資料館。
吳清山、林天祐 (2010)。教育e 辭書。臺北市：高等教育。
吳清山、黃旭鈞 (2006)。國民小學推動知識管理之研究-有利條件、
困境、功能與策略。教育研究月刊，52(2)，33-65。
吳清山、賴協志 (2009)。知識領導-理論與研究。臺北市：高等教育。
吳清基 (1984)。賽蒙行政決定理論及其在教育行政上的應用(未出版
186
博士論文)。國立臺灣師範大學教育系，臺北市。
吳清基 (1996)。精緻教育的理念(第四版)。臺北市：師大書苑。
吳清基、陳美玉、楊振昇、顏國樑 (2004)。教育行政決定。載於伍
振鴛主編，教育行政。臺北市：五南。
林三木 (1996)。特殊教育行政。臺北市：五南。
林其賢 (2008)。學校層級資料導向決策系統資料內容之研究：臺北
市國民小學校長之意見調查(未出版碩士論文)。淡江大學，新北
市。
林其賢、高薰芳 (2009)。資料導向決策系統之設計：校長決策領導
的新思維。學校行政，62，80-97。
林芳如 (2009)。教學介入反應及其相關研究之探討。國小特殊教育，
48，23-31。
林珊如 (2001)。從教師知識分享與資源共享談教育效能之提升。教
育資料與研究，45，19-24。
林桂如 (2008)。回應式介入內涵及其對國內融合教育之啟示。國小
特殊教育，45，68-77。
林海清 (2002)。知識管理與教育發展。臺北市：元照。
林蕙芬 (2008a)。「全校性正向行為支持」方案的介紹。特教園丁，
24(2)，38-47。
林蕙芬 (2008b)。如何執行正向行為支持。特教園丁，24(1)，42-47。
邱上真 (2002)。特殊教育導論：帶好班上每位學生。臺北市：心理。
洪儷瑜、何淑玫 (2010)。「介入反應」在特殊教育的意義與運用，特
殊教育季刊，115，1-13。
孫愛華 (2009)。新竹縣市國小普通班教師對疑似學習障礙學生實施
介入反應效果模式現況之調查研究(未出版碩士論文)，國立新竹
教育大學特殊教育系，新竹市。
秦夢群 (2006)。教育行政-理論部分(第五版)。臺北市：五南。
高令秋 (1997)。資源教室功能之探討，載於中華民國特殊教育學會
187
(主編)。身心障礙教育的革新與展望-開發潛能再創新機(頁
93-104)。臺北市：心理。
張文穗 (2010)。臺北縣國小學校行政人員應用資料導向決定及其相
關因素之研究(未出版碩士論文)。臺北市立教育大學教育行政與
評鑑所，臺北市。
張世彗 (2008)。學習障礙、安置與融合教育。國教新知，55(4)，15-23。
張正芬 (2010)。日本的特殊教育改革。教育資料集刊，46，101-118。
張明輝 (2002)。學校經營與管理研究-前瞻、整合、學習與革新。臺
北市：學富文化。
張奕華、張敏章 (2009)。數位時代中提升學校效能新途徑：科技領
導與DDDM 模式。教育研究月刊，188，112-122。
張奕華、顏弘欽 (2010)。教師專業能力發展新取向：DDDM 模式的
實踐。北縣教育季刊，71，11-16。
張媛媛 (2008)。融合教育的省思與實踐-從教育機會均等的觀點。特
教園丁，23(3)，18-21。
張鈿富 (2001)。學校行政決定原理與實務。臺北市：五南。
教育部 (2008)。特殊教育報告書。取自
http://163.21.111.100/book_ul/33/885/特殊教育發展報告書.pdf
教育部 (2010)。國民小學校別資料。取自
http://www.edu.tw/statistics/content.aspx?site_content_sn=25760
郭為藩 (1993)。特殊兒童心理與教育。臺北市：文景。
郭進隆、齊若蘭 (譯) (2010)。第五項修煉：學習型組織的藝術與實
務 (原作者：Senge, P. M)。臺北市：天下遠見。
陳仁貴 (2008)。臺北市國民小學補救教學現況調查研究(未出版碩士
論文)。臺北市立教育大學特殊教育系，臺北市。
陳淑麗 (2004)。轉介前介入對原住民閱讀障礙診斷區辨效度之研究
(未出版博士論文)。國立臺灣師範大學特殊教育所，臺北市。
陳紹賓 (2008)。資料導向決定在國民小學校長願景領導應用之研
188
究—以臺北縣為例(未出版碩士論文)。國立臺北教育大學教育政
策與管理研究所，臺北市。
彭富源 (2010)。臺灣初等教育品質管理機制與省思。教育資料集刊，
45，1-26。
鈕文英 (2006)。融合教育的理念與作法(上)-理念、現況與作法篇。
高雄市：復文。
鈕文英 (2008)。建構生態的融合教育。中華民國特殊教育學會年刊，
31-56。
黃乃熒 (2003)。知識經濟時代之學校行政倫理實踐。載於張明輝主
編，教育政策與教育革新。臺北市：心理。
黃志強 (2009)。應用教學反應模式對國小學習障礙學生鑑定之研究
(未出版博士論文)。國立高雄師範大學特殊教育學系，高雄市。
黃秋霞 (2010)。轉介前識字教學介入對國小一年識字困難學童的學
習效果。屏東教育大學學報，35，155-202。
楊坤堂 (2005)。學習障礙導論。臺北市：五南。
楊坤堂 (2008)。正向行為支持的概念與策略。國小特殊教育，46，
1-12。
楊振昇 (2001)。知識管理之內涵及其在教育行政上之應用。教育政
策論壇，4(2)，61-86。
葉乃嘉 (2004)。知識管理-於電子商務與資訊管理之案例。臺北市：
全華科技。
詹士宜 (2007)。介入效果模式的學障鑑定。特殊教育季刊，103，
17-23。
趙慕芬、李青芬、李雅婷 (譯) (2006)。組織行為學(原作者：Robbins,
S. P.)。臺北市：華泰文化。
劉名峯 (2006)。國民小學校長應用資料導向決定之研究(未出版碩士
論文)，國立臺北教育大學教育政策與管理研究所，臺北市。
劉定霖 (2000)。知識經濟的趨勢對於教育工作之衝擊與影響。教育
189
資料集刊，41，26-28。
劉春榮 (1998)。教師專業自主。教育資料集刊，23，25-38。
劉鎮寧 (2003)。理性決定過程模式之探討。教育資料與研究，52，
100-107。
蕭偉智 (2009)。普教與特教的接軌-談攜手計畫與介入反應模式。中
等教育，60(4)，134-147。
謝文全 (2008)。教育行政學(第三版)。臺北市：高等教育。
謝寶煖 (2006)。決定樣本大小，取自
http://www.lis.ntu.edu.tw/~pnhsieh/epapers/no33.htm
簡明達、邱金滿 (2000)。教育安置。載於林寶貴(主編) 。特殊教育
理論與實務(頁335-362)。臺北市：心理。
二、英文部分
Acker, K. L. (2006). Data-driven decision making: From superintendent
to classroom (Master’s thesis). Available ProQuest Dissertations and
Theses database. (UMI: 3246665)
Armstrong, J., & Anthes, K. (2001). How data can help? Putting
information to work to raises student achievement. American School
Board Journal, 11, 1-4.
Bailey, L. N. (2010). Teacher’s perception of student support team and
response to intervention effectiveness (Master’s thesis). Available
ProQuest Dissertations and Thesis database. (UMI: 3398154)
Bernhardt, V. L. (2004). Continuous improvement: It takes more than test
score. ASCA Leadership, 16-19.
Block, N. F. (2008). A study of response to intervention for urban
sixth-grade: Analyzing reading, language and learning differences
in tier 1and tier2 (Master’s thesis). Available ProQuest Dissertations
and Theses database. (UMI: 3351235)
190
Brown-Chidsey, R., Bronaugh, L., & McGraw, K. (2009). RTI in the
classroom: Guidelines and recipes for success. New York : The
Guilford Press.
Brown-Chidsey, R., & Steege, M. W. (2010). Response to intervention:
Principles and strategies for effective practice. New York : The
Guilford Press.
Bowers, A. J. (2009). Reconsidering grades as data for decision making:
More than just academic knowledge. Journal of Educational
Administration, 47(5), 609-629.
Burns, M. K., Scholin, S. E., Kosciolek, S., & Livingston, J. (2010).
Reliability of decision-making framework for response to
intervention for reading. Journal of Psychoeducational Assessment,
28(2), 102-114.
Calabrese, R. L., & Zepeda S. J. (1999). Decision-making assessment:
Improving principal performance. The International Journal of
Educational Management, 13(1), 6-15.
Danielian, H. J. (2009). District level practice in data driven decision
making (Master’s thesis). Available ProQuest Dissertations and
Theses database. (UMI: 3355413)
Delbecq, A. L., Griffith, T. L., Madsen T. L., & Woolley, J. L. (2010). A
decision process model to support timely organizational innovation.
In Nutt, P. L. & Wilson, D. C. (eds.), Handbook of Decision Making
(pp.197-230). West Sussex, UK: John Wiley & Sons.
Dembosky, J. W., Pane, J. F., Barney, H., & Christina, R. (2005). Data
driven decision making in Southwestern Pennsylvania School
districts. RAND Education. Retrieved from
http://www.rand.org/pubs/working_papers/2006/RAND_WR326.pdf
Doyle, D. P. (2002). Knowledge-based decision making: Moving beyond
191
intuition through data-laced wisdom leading to informed actions.
The School Administration, 12, 30-34.
Dimmitt, C., Carey, J. C., & Hatch, T. (2007). Evidence-based school
counseling: Making a difference with data-driven practices.
Thousand Oaks, CA: Corwin Press.
Dynarski, M. (2008). Researchers and educators: Allies in Learning.
Education Leadership, 66(4), 48-53.
Dunlap, G., Sailor, W., Horner, R. H., & Sugai, G. (2009). Overview and
history of positive support. In Sailor, G., Dunlap, G., Sugai G., &
Horner, R. H. (eds.), Handbook of positive support behavior
(pp.3-16). New York : Springer Science Bussiness Media.
Earl, L. M., & Katz, S. (2006). Leading schools in a data-rich world.
Thousand Oaks, CA: Corwin Press.
Ervin, R. A., Schaughency, E., Matthews, A., Goodman, S. D., &
McGlinchey, M. T. (2007). Primary and secondary prevention of
behavior difficulties: Developing a data-informed problem-solving
model to guide decision making at school-Wide level. Psychology in
the Schools, 44(1), 7-18.
Feldman, J., & Tung, R. (2001). Whole school reform: How school use
data-based inquiry and decision making process. Paper presented at
the 82nd annual meeting of the American Educational Research
Association. Boston, MA.
Fiore, D. J. (2005). Making the right decisions. Larchmont, NY: Eye on
Education.
Fullan, M. (2009). Introduction to the change of change: Purposeful
action at work. In Fullan, M. (ed.). The change of change:Start
school improvement now(second edition) (pp.3-8). Thousand Oaks,
CA: Corwin Press.
192
Fuchs, L. S., & Fuchs, D. (2007). A model for implementint response to
intervention. Teaching Exceptional Children, 39(5), 13-20.
Gentry, D. R. (2005). Technology supported data-driven decision making
in an Oklahoma elementary school (Master’s thesis). Available
ProQuest Dissertations and Thesis database. (UMI No.3159278)
Gersten, R., & Dimino, J. A. (2006). RTI (Response to intervention):
Rethinking special education for students with reading
difficulties(yet again). Reading Research Quarterly, 41(2), 99-108.
Goddard, Y. L., Goddard, R. D., & Tschannen-Moran, M. (2007). A
theoretical and empirical investigation of teacher collaboration for
school improvement and student achievement in public elementary
school. Teachers College Record, 109(4), 77-96.
Goldring, E. B., & Berends, M. (2009). Leading with data: Pathways to
improve your school. Thousand Oaks, CA: Corwin Press.
Goodman, G. (2008). Interventions for struggling learners: Putting RTI
into practice. Peterborough, NH: Crystal Spring Books.
Greenfield, R., Renaldi, C., Proctor, C. P., & Cardarelli, .A. (2010).
Teacher’s perception of a response to intervention (RTI) reform
effort in an urban elementary school: A consensual qualitative
analysis. Journal of Disability Policy Studies, 21(1), 47-63.
Gresham, F. M. (2005). Response to Intervention: An alternative means
of identifying students as emotionally disturbed. Education and
Treatment of Children, 28(4), 328-344.
Grigorenko, E. L. (2009). Dynamic assessments and response to
Intervention: Two Sides of One Coin. Journal of Learning
Disabilities, 42(2), 111-132.
Groce, M. K. (2009). New probes for early literacy skills (Master’s
thesis). Available ProQuest Dissertations and Thesis database. (UMI
193
No.3357712)
Hair, J. F., Black, W. C., Babin, B. J.,& Anderson, R. E. (2010).
Multivariate data analysis (7th ed.). Upper Saddle River, NJ:
Prentice Hall.
Hess, F. D. (2008). The new stupid. Educational Leadership, 66(4),
12-17.
Hoover, J. J. (2009). RTI assessment essential for struggling learners.
Thousand Oaks, CA: Corwin Press.
Isaacs, M. L. (2003). Data-driven decision making: The engine of
accountability. Professional School Conseling,6(4), 288-295.
Jackson, D., & Temperley, J. (2007). From professional learning
community to networked learning community. In Stoll, E., & Louis,
K. S. (eds.), Professional Community: Divergence, depths and
dilemmas (pp.45-62). Two Penn Plaza, NY: Open University Press.
Jimerson, S. R., Burns, M. K., & Van Der Heyden, A. M. (2007).
Handbook of response to intervention: The science and practice
assessment and intervention. New York : Springer Science Business
Media.
Johnson, B. L., & Kruse, S. D. (2009). Decision making for educational
leaders. Allbany, NY: State University of New York Press.
Kadel, R. (2010). Data-driven decision making- Not just a buzz.
Learning & Reading, 37(7), 18-21.
Killion, J. M. (2009). Teacher programs and data-driven decision
making: Are we preparing our teachers to be data and assessment
literature? (Master’s thesis). Available ProQuest Dissertations and
Thesis database. (UMI No.3355465)
Kowalski, T. J. (2009). Evidence and decision making in professions. In
Kowalski, T. J., & Lasley, T. J. (eds). Handbook of data-based
194
decision making in education (pp.3-19). Madison Ave, NY:
Routledge.
Keeney, L. (1998). Using data for school improvement. Paper presented
at the Second Practitioner’s Conference for Annenberg Challenge
Site. Houston, Texas.
LasleyⅡ, T. J. (2009). Using data to make critical choices. In Kowalski,
T. J., & Lasley Ⅱ, T. J. (eds). Handbook of data-based decision
making in education (pp.243-258). New York : Routledge.
Lashway, L. (2003). Distributed leadership. Research Roundup, 19(4).
Retrieved from
https://scholarsbank.uoregon.edu/xmlui/bitstream/handle/1794/3487
/roundups_Summer_2003.pdf?sequence=1
Leithwood, K., Aitken, R., & Jantzi, D. (2006). Making schools smarter:
leading with evidence. Thousand Oaks, CA: Corwin Press.
Lewis, C. (2007). School improvement in action: Building shared
responsibility for student success. Kelowna, BC: SAEE.
Light, D., Wexler, D., & Heinz, C. (2005). Keeping teachers in the center:
A framework for data-driven decision-making. In C. Crawford et al.
(eds.), Proceedings of society for information technology & teacher
education international conference 2005 (pp. 128-133). Chesapeake,
VA: AACE.
Love, N. (2009). Building a high-performing data culture. In Love,
N.(ed.), Using data to improving learning for All:A collaborative
inquiry approach (pp.2-24). Thousand Oaks, CA: Corwin Press.
Lunenburg, F.C., & Ornstein, A. C. (2008). Educational
administration-concepts and practice (fifth edition). Belmont, CA:
Thomson Higher Education.
Luo, M. (2008). Structural eduation modeling for high school principals’
195
data-driven decision making: An analysis of information use
environments. Educational Administration Quarterly, 44(5),
603-634.
Mahoney, L. S., Roush, P. B., & Bandy, D. (2003). An investigation of
effects decisional guidance and cognitive ability on decision making
on involving uncertainty data. Information and Organization, 13,
85-110.
Mandinach, E. B., Honey, M., & Light, D. (2006). A theoretical
framework for data-driven decision making. Paper presented at the
annual meeting of AERA. San Francisco, CA.
Mandinach, E. B., Rivas, L., Light, D., Heinze, C., & Honey, M. (2006).
The impact of data-driven decision tools on education practice.
Paper presented at the annual meeting of AERA. San Francisco, CA.
Mandinach, E. B., Honey, M., Light, D., & Brunner, C. (2008). A
conceptual framework for data-driven decision making. In
Mandinach, E. B., & Honey, M. (eds.), Data-driven school
improvement:Linking data and learning (pp.13-31). Amsterdam
Avenue, NY: Teacher College Press.
Marsh, J. A., Pane, J. F., & Hamilton L. S. (2006). Making sense of
data-driven decision making in education. Rand Education. Retrived
from http://www.rand.org/pubs/occational_papers/OP170
Marsh, J. A., McCombs, J. S., & Martorell, F. (2010). How instructional
coaches support data-driven decision making: Policy
Implementation and Effects in Florida Middle Schools. Educational
policy, 24(6), 872-907.
Mason, S. (2002). Turning data into knowledge: Lessons from six
Milwaukee public schools. Paper presented at the annual conference
of the American Educational Research Association, New Orleans.
196
McDougal, J. L., Graney, S. B., Wright, J. A., & Ardoin, S. P. (2010). RTI
in practice: A practical guide to implementing effective
evidence-based intervention in your school. Hoboken, NJ: John
Wiley & Stones.
Mellard, D. F., Byrd, S. E., Johnson, E., Tollefson, J. M., & Boesche, L.
(2005). Foundation and research on identifying mode response to
intervention Sites. Learning Disability Quarterly, 27(4), 243-256.
Mellard, D. F., & Johnson, W. (2008). RTI:A practitioner’s guide to
implementing response to intervention. Thousand Oaks, CA: Corwin
Press.
Moody, L., & Dede, C. (2008). Models of data-based decision making: A
case study of the Milwaukee public schools. In Mandinach, E. B., &
Honey, M. (eds.). Data-driven school improvement:Linking data and
learning (pp.233-256). Amsterdam Avenue, NY: Teacher College
Press.
NCRTI (2010). Essential Components of RTI: Look at response to
intervention. Retrieved from http://www.rti4success.org
Nonaka, I. (1994). A dynamic theory of organizational knowledge
creation. Organizational Science, 5(1), 14-37.
NRCLD (2007). What is RTI? Retrieved from
http://www.nrcld.org/about/publications/papers/mellard.html
Pearce, L. R. (2009). Helping children with emotional difficulties: A
response to intervention investigation, The Rural Educator, 30(2),
34-46.
Petrides, L. A., & Guiney, S. Z. (2002). Knowledge management for
school leaders: An ecological framework for thinking schools.
Teacher College Record, 104(8), 1702-1717.
Popham, W. J. (2008). Anchoring down the data. Educational Leadership,
197
66(4), 85-86.
Poulson, D. S. (2007). Hand book of regression and modeling. Boca
Raton, FL: Taylor & Francis Group.
Preble, B., & Taylor, L. (2008). School climate through student’s eyes.
Education Leadership, 66(4), 35-40.
Press, P. G. (2007). Data-driven decision making and dynamic planning:
a school leader’s guide. Larchmont, NY : Eye on Education.
Ramsey, R. D. (2006). Lead, follow or get out of the way (second edition).
Thousand Oaks, CA: Corwin Press.
Reeves, D. B. (2002). The leaders guide to standards: A blueprint for
educational equality excellence. San Francisco : Jossey-Bass.
Root, L. G. (2010). How urban school superintendent effectively use
data-driven decision making to improvement student achievement
(Master’s thesis). Available ProQuest Dissertations and Thesis
database. (UMI No.3403754)
Rudy, D. W., & Conrad, W. H. (2004). Breaking down the data. American
School Board Journal,191(2), 39-41.
Russo, C., Tigerman, E., & Radziewicz, C. (2009). RTI guide: Making it
work. Port Chester, NY: Dude Publishing.
Sailors, W. (2009). Making RTI work: How smart schools are reforming
education through school-wide response to intervention. San
Francisco : Jossey-Bass.
Sallis, E., & Jones, G. (2002). Knowledge Management in Education.
London : Kogan Page.
Sanders, M. G. (2008). Using diverse data to develop and sustain school,
family and community partnership: A district case study.
Educational Management Administration & Leadership, 36(4),
530-545.
198
SAS. (2008). Data-driven decision making: Analyzing your data to
improve student learning. (103739_517492.1208). Retrived from
SAS Institute website: www.sas.com/gocedu/edu
Scherer, M. (2008). Driven dumb by data? Education Leadership, 66(4),
5-5.
Shapiro, E. S., & Clemens, N. H. (2009). A conceptual model for
evaluating system effects of response to intervention. Assessments
for Effective Intervention, 35(1),3-16.
Simon, H. A. (1991). Bounded rationality and organizational learning.
Organizational Science, 2(1), 125-134.
Smallwood, D. L., Christner, R. W.,& Brill, L. (2007). Applyng
cognitive-behavior therapy groups in school setting. In Christner, R.
W., Stewart, J. L., & Freeman, A. (eds.), Handbook cognitive
-behavior group therapy With children and adolescents: Specific
settings and presenting problems. New York: Taylor & Francis
Routledge.
Stokes, L. (2001). Lessons from an inquiry school: forms of inquiry and
conditions for teacher learning. In Lieberman, A., & Miller, L. (eds),
Teacher’s Caught in the Action:Professional devlopement matters
(pp.141-158). New York : Amsterdan Ave nue.
Sugai, G., Guardino, D., & Lathrop, M. (2007). Response to intervention:
Examining classroom behavior support in second grade. Council for
Exceptional Children, 73(3), 288-310.
VanDerHeyden, A. M., Witt, J. C., & Gilberston, D. (2007). A multi-year
evaluation of the effects of a response to intervention (RTI) model
on identification of children for special education. Journal of School
Psychology, 45, 225-256.
Wayman, J. C., Midgley, S., & Stringfield, S. (2006). Leadership for