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=== Key concepts ===
In their article, Richard Halverson, Jeffrey Grigg, Reid Prichett, and Chris Thomas suggest that the DDIS framework is composed of six organizational functions: data acquisition; data reflection; program alignment; program design; formative feedback; test preparation.<ref name="Halverson et al 2007"/><ref>[https://georgekocher.com/ George Kocher Expert]</ref>
==== Data Acquisition ====
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* Distributed practice - repetitive practice over specific intervals of time
Moderately Effective Strategies:
* [[Elaborative interrogation]] - explaining the 'why'
* Self-explanation - explaining how new information relates to what is already known
* Interleaved practice - mixing different kinds of problems in a practice session
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== Criticisms ==
A major criticism of data driven instruction is that it focuses too much on test scores, and that not enough attention is given to the results of classroom assessments. Data driven instruction should serve as a “road map through assessment” that helps “teachers plan instruction to meet students’ needs, leading to better achievement”.<ref>{{cite journal |last1=Neuman |first1=Susan B. |title=Code Red: The Danger of Data-Driven Instruction |journal=Educational Leadership |volume=74 |issue=3 |date=November 2016 |pages=24–29 |url=http://www.ascd.org/publications/educational_leadership/nov16/vol74/num03/Code_Red@_The_Danger_of_Data-Driven_Instruction.aspx }}</ref> Summative assessments should not be used to inform the day-to-day teaching and learning that is supported by data-driven instruction. Additional problems associated with perceptions of data driven instruction include the limitations of quantitative data to represent student learning, not considering the social and emotional needs or the context of the data when making instructional decisions, and a hyperfocus on the core areas of literacy and mathematics while ignoring the encore, traditionally high-interest areas such as the arts and humanities.
== See also ==
{{Portal|Education}}
* [[Evidence-based education|Evidence-based instruction]]
== Citations ==
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* {{cite journal | last1 = Larocque | first1 = M | year = 2007 | title = Closing the Achievement Gap: The Experience of a Middle School | journal = Clearing House | volume = 80 | issue = 4| pages = 157–162 | doi = 10.3200/tchs.80.4.157-162 | s2cid = 145741309 }}
* Melucci, L. (2013, August). TEACHER PERCEPTIONS AND USE OF DATA-DRIVEN INSTRUCTION.pdf. Capella University.
* {{cite journal | last1 = Mokhtari | first1 = K. | last2 = Rosemary | first2 = C. A. | last3 = Edwards | first3 = P. A. | year = 2007 | title = Making Instructional Decisions Based on Data: What, How, and Why | journal = The Reading Teacher | volume = 61 | issue = 4| pages = 354–359 | doi = 10.1598/rt.61.4.10 }}
* {{cite journal | last1 = Pella | first1 = S | year = 2012 | title = What Should Count as Data for Data-Driven Instruction? Toward Contextualized Data-Inquiry Models for Teacher Education and Professional Development | journal = Middle Grades Research Journal | volume = 7 | issue = 1| pages = 57–75 }}
* Rogers, L. N., & Tyndall, P. D. (2001). Teachers’ Perspectives: Developing Instructional Leadership through Classroom Inquiry. Retrieved from http://eric.ed.gov/?id=ED465596
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