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* Keyword mnemonic
* Imagery use for text learning
* Rereading<ref>{{Cite journal|last=Dunlosky|first=J.|last2=Rawson|first2=K. A.|last3=Marsh|first3=E. J.|last4=Nathan|first4=M. J.|last5=Willingham|first5=D. T.|year=2013|title=Improving students’ learning with effective learning techniques promising directions from cognitive and educational psychology|url=|journal=Psychological Science in the Public Interest|volume=14(1)|pages=4-58|via=}}</ref>
It is worth noting that the less effective strategies may be more commonly used in K-12 classrooms than the moderately effective and highly effective strategies. The authors suggest that students should be taught how to use more effective techniques and when they are most helpful in guiding their learning. When these strategies become internalized, students will have developed techniques in order to learn how to learn. This is critical as they move into the secondary level and are expected to be more independent in their studies.
== 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>Neuman, S. (2016). Code Red: The Danger of Data-Driven Instruction. Educational Leadership, 74(3), pps. 24-29</ref> (Neuman, 2016). 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.
== References ==
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