Level of Expertise: 4
What is the strategy?
Text previewing directs students to thoroughly examine the text giving attention to key features, titles, subheadings, objectives, examples, charts and graphs. Students use this information to review their level of familiarity with these features of the text. Students determine what concepts they are able to describe or show examples of versus ones with which they are unfamiliar (Garber-Miller, 2006).
Why use this strategy?
This strategy will help my students determine key concepts within this unit as well as increases their level of interest. As a pre-reading activity, my students are given the opportunity to analyze the main ideas and determine what they already know about topics such as Front-End Estimation and Compatible Numbers. By activating prior knowledge, these students can compare new information with already understood concepts.
How does it work?
1. EXAMINE- Students will preview the selected reading (Charles, Branch-Boyd, Illingworth, Mills, Reeves, & Thompson, 2004, pp. 5-10). I will ask them to pay close attention to the key features, titles, subheadings, objectives, examples, charts and graphs.
2. LIST- I will ask students to identify key features, titles, subheadings, objectives, examples, charts and graphs that they feel are key pieces of information in order to understand the unit. Students will write words such as estimate round and clustering on a sheet of paper.
3. CATEGORIZE- Students will place the key features, titles, subheadings, objectives, examples, charts and graphs into two categories: What’s Old and What’s New. Information that the student is able to define clearly and/or give an example of will go in the What’s New category. Information the student is not able to define or provide an example of will go in the What’s Old category.
Sources Referenced: Charles, Branch-Boyd, Illingworth, Mills, Reeves, & Thompson, 2004; Garber-Miller, 2006
What does it look like?
What’s Old | What New |
Round Sum Difference Whole number Estimate Digits Multiply Quotient Least Greatest | Compatible Front-End Estimation Front-End Digits Clustering |
