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摘要
外文摘要
引文資料
題名:
美國學生學習歷程縱貫性大數據系統P-20W的啟示與借鏡
書刊名:
當代教育研究季刊
作者:
洪錦珠
/
蕭佳賓
/
李育齊
作者(外文):
Hung, Ching-chu
/
Hsiao, Jia-bin
/
Li, Yu-chi
出版日期:
2019
卷期:
27:3
頁次:
頁1-33
主題關鍵詞:
教育大數據
;
縱貫性資料
;
資料策略
;
資料探勘
;
品質保證
;
Educational big data
;
Longitudinal data
;
Data strategy
;
Data mining
;
Quality assurance
原始連結:
連回原系統網址
相關次數:
被引用次數:期刊(
1
) 博士論文(0) 專書(0) 專書論文(0)
排除自我引用:
1
共同引用:
8
點閱:2
建置教育大數據主要目的在於針對社會各界所關注的教育議題尋找影響學生學習成果的關鍵因素,以做為改善教育制度與教學現場問題、預測未來教育趨勢之參據,落實以「證據為本」的教育決策模式。本研究旨在探討如何建構和推動學生學習歷程的縱貫性教育大數據,爰美國建構P-20W縱貫性大數據系統多年並獲得豐碩成果,故以其為研究對象,蒐集相關法令及實際案例,採用文獻分析法進行探討和說明。研究發現P-20W是以改善學生學習成效為策略目標,建置學生自學齡前教育至就業的個人化歷程資料和教育研究為手段,擷取與分析足以有效達成策略目標的資訊,提供教育決策及改善教育現場問題參考。為落實該項策略並確保資料品質,投入資源並訂定相關法案,建構有利的環境和摒除可能的障礙,並輔以關鍵配套措施。本研究結合教育與資訊技術的角度,參考資訊系統規劃實務,從資料策略,確認教育需求與問題,建立資料治理結構與流程,到學生個資隱私、安全與保密,依序呈現並提出建議,以作為我國建置此類資料庫的參考。
以文找文
The main purpose of constructing an educational database is to find the key factors that affect students' learning outcomes in view of the educational issues that are of great concern by all sectors of society, so as to improve the educational system and teaching site problems, to predict future educational trends, and to implement an educational decision-making mode that is "evidence-based". The purpose of this study is to explore how to construct and promote the longitudinal educational database of students' learning process. Since the United States has already obtained fruitful results from its construction of the P-20W longitudinal educational database, this study takes it as the research object, collects relevant laws and practical cases, and uses the document analysis approach to explore and explain the findings. This study notes that P-20W has taken a series of actions to achieve its strategic objective at improving students' learning effectiveness, which include building personal data on learning for each student from pre-school through workforce entry, capturing information sufficient to effectively achieve its strategic objective, analyzing and providing this information to help stakeholders make educational decisions, and improving problems in the classroom. To implement the strategy and ensure data quality, P-20W has invested a lot of resources, formulated relevant bills, set up a helpful environment, removed related barriers, and supported it with various activities. Based upon the perspective of education and information technology and referring to the planning practice of an information system, this study presents the research results through the sequence of working out data strategy, identifying the educational needs and problems, establishing data governance structure and processing, setting up privacy, security, and confidentiality policies and facilities for students' data, and finally proposing some suggestions as a reference for the establishment of such databases in Taiwan.
以文找文
期刊論文
1.
Mandinach, E. B.、Gummer, E. S.(2013)。A systemic view of implementing data literacy in educator preparation。Educational Researcher,42(1),30-37。
2.
Rios-Aguilar, C.(2015)。Using big (and critical) data to unmask inequities in community colleges。New Directions for Institutional Research,163,43-57。
3.
蔡明學、黃建翔(2015)。大數據分析在我國教育發展應用上之探討。教育脈動,4,154-164。
延伸查詢
4.
曾元顯(20160300)。校務研究資料庫的建構與分析應用。當代教育研究季刊,24(1),107-134。
延伸查詢
5.
Davenport, Thomas H.、Patil, D. J.(2012)。Data Scientist: The Sexiest Job of the 21st Century。Harvard Business Review,90(10),70-76。
6.
王金龍(20150700)。銘傳Moodle大數據分析與學生學習成效。評鑑雙月刊,56,22-27。
延伸查詢
7.
張佳琳(20140501)。「大數據」趨勢對中小學教育的影響引發討論。教育部電子報,612。
延伸查詢
8.
楊孟山、林宜玄(20160700)。臺灣教育資料庫的現在與未來。臺灣教育評論月刊,5(7),10-18。
延伸查詢
9.
Baker, R. S.(2014)。Educational data mining: An advance for intelligent systems in education。IEEE Intelligent Systems,29(3),78-82。
10.
Baker, R. S. J. D.、Yacef, K.(2009)。The state of educational data mining in 2009: A review and future visions。Journal of Educational Data Mining,1(1),3-17。
會議論文
1.
Pavlik, P. I. Jr.、Cen, H.、Koedinger, K. R.(2009)。Performance factors analysis – A new alternative to knowledge tracing。14th International Conference on Artificial Intelligence in Education。Brighton, England。
圖書
1.
彭森明(2013)。高等教育校務研究的理念與應用。高等教育出版社。
延伸查詢
2.
Mayer-Schönberger, V.、Cukier, K.(2014)。Learning with big data: The future of education。Houghton Mifflin Harcourt。
3.
彭森明(2010)。大學生學習成果評量:理論、實務與應用。臺北市:高等教育文化事業有限公司。
延伸查詢
4.
Mayer-Schönberger, Viktor、Cukier, Kenneth(2013)。BIG DATA: A Revolution That Will Transform How We Live, Work, and Think。Houghton Mifflin Harcourt。
5.
National Forum on Education Statistics(2010)。Traveling through time: The forum guide to longitudinal data systems. Book one of four: What is an LDS?。Washington, DC:National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education。
6.
National Forum on Education Statistics(2011)。Traveling through time: The forum guide to longitudinal data systems. Book three of four: Effectively managing LDS data。Washington, DC:National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education。
其他
1.
國家教育研究院(2018)。「臺灣學生學習成就評量資料庫」建置計畫,https://www.naer.edu.tw/files/11-1000-1408.php?Lang=zh-tw。
延伸查詢
2.
教育部(2018)。高級中等學校學習歷程資料庫系統建置成果與後續推展宣導規劃,https://ws.moe.edu.tw/001/Upload/23/relfile/8059/55480/b4edd469-e9a6-4bd3-b49f-b642da1982f1.pdf。
延伸查詢
3.
Bernard, M.(2014)。6 key skills every business needs,https://www.dummies.com/programming/big-data/6-key-big-data-skills-every-business-needs/。
4.
Bernard, M.(2014)。Big data: The 4 layers everyone must know,http://www.slideshare.net/BernardMarr/big-data-4-layers。
5.
Christer, J.(2015)。Advancing analytics to predict specific needs,http://www.huffingtonpost.com/christer-johnson/ibm-advancing-analytics_b_1760680.html。
6.
Council of Chief State School Officers(2015)。About the standards,http://www.corestandards.org/about-the-standards/。
7.
Data Quality Campaign(2013)。Investing in educator data literacy improves student achievement,http://files.eric.ed.gov/fulltext/ED548266.pdf。
8.
Dumbill, E.(2012)。What is big data?,http://orm-atlas2-prod.s3.amazonaws.com/pdf/e11376d1c19a651736042656f2aae705.pdf。
9.
Erhard, R.,Hong, H. D.(2015)。Data cleaning: Problems and current approaches,https://www.betterevaluation.org/sites/default/files/data_cleaning.pdf。
10.
Guidera, A. R.(2011)。Using data to improve student achievement: A conversation with members of the montana education and local government interim committee,https://slideplayer.com/slide/3832574/。
11.
Gane, B. D.,Okoroh, C.,Dibello, L. V.,Minstrell, J.(2015)。Making sense of big data from classroom assessments: Teacher Case studies and facets-based physics assessments,https://www.academia.edu/12105549/Making_Sense_of_Big_Data_from_Classroom_Assessments_Teacher_Case_Studies_and_Facetsbased_Physics_Assessments。
12.
Guidera, A. R.(2013)。The four Ts of state data systems (turf, trust, technology, and time): Policy perspective on empowering education stakeholders with data,https://drive.google.com/open?id=1WXfGbGnIHCLbMwHY1hxCvjOFq_4yAj2n。
13.
Kowalski, P.(2013)。P-20W data governance: Critical roles for success, education, commission of the states,https://drive.google.com/file/d/128U9qswrplu4gfUmwa-qm-MnUyviXLaA/view?usp=sharing。
14.
North Carolina Department of Commerce(2014)。A Report on the operations of the north carolina common follow-up system,https://docplayer.net/16538676-A-report-on-the-operations-of-the-north-carolina-common-follow-up-systemmay-2014.html。
15.
Shah, R.(2012)。Pivotal role of policymakers as leaders of P-20/Workforce data governance,https://files.eric.ed.gov/fulltext/ED538830.pdf。
16.
Shelley, T. R.,Dasgupta, C.,Moher, T.,Lyon, L.(2014)。Supporting learners' construction of understandings of animal behaviors from large image sets,https://drive.google.com/open?id=12MzcakTtmgvlGJW_5QGfsqkj2SCbTNYF。
17.
Swan, K. P.(2012)。Big data and the predictive analytics reporting (PAR) framework,https://drive.google.com/open?id=1rS4Egzr_e1H3Cy0VLTW6BAee-NpTuy99。
18.
U.S. Department of Education(2002)。Education sciences reform act of 2002,https://legcounsel.house.gov/Comps/Education%20Sciences%20Reform%20Act%20Of%202002.pdf。
19.
U.S. Department of Education(2015)。Strategic plan for fiscal years 2014-2018,http://www2.ed.gov/about/reports/strat/plan2014-18/strategic-plan.pdf。
20.
Virginia Longitudinal Data System(2018)。Insights of VLDS,https://vlds.virginia.gov/insights。
21.
Wagner, E.,Davis, B.(2013)。The predictive analytics reporting (PAR) framework, WCET,http://er.educause.edu/articles/2013/12/the-predictiveanalytics-reporting-par-framework-wcet。
22.
Zeke, P. J.(2016)。50-State comparison: Statewide longitudinal data systems,https://www.ecs.org/state-longitudinal-data-systems/。
23.
Zeke, P. J.(2017)。Examining SLDS development and utility,https://www.ecs.org/examining-slds-development-and-utility/。
圖書論文
1.
Baker, S.、Inventado, P. S.(2016)。Educational data mining and learning analytics: Potentials and possibilities for online education。Emergence and Innovation in Digital Learning。
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