# data[].attributes.body
How can you use captions to locate information in a text?

“I can use captions to ________.”

# data[].attributes.body
What can the sentence in the story tell us about an illustration?

A sentence can tell us what is happening in an illustration by…

# data[].attributes.body
Q: How can you use bold print to identify key information in a text?

Stem: I can use bold print to identify key information in text by ________________ .

# data[].attributes.headline
How do captions on photos help me to better understand the text? 

# data[].attributes.subject
How do captions on photos help me to better understand the text? 

# data[].attributes.body
A photo caption helps me to understand…

# data[].attributes.body
Q: What predictions can you make based on the caption provided in the passage?
Stem: I can predict that _________ based on the caption.

# data[].attributes.body
What do captions tell us about the picture?

Captions tell us

# data[].attributes.headline
Question: How do text features help a reader gain information?

# data[].attributes.subject
Question: How do text features help a reader gain information?

# data[].attributes.body
S: Text features help readers gain information by...

# data[].attributes.body
What do the captions tell you about the picture?
The caption tells me....

# data[].attributes.body
Q: How can we use text features to increase understanding of the passage?
Ss: Text features help me understand unfamiliar words because ————-

# data[].attributes.body
What text feature do you see under the picture.
Under the ppicture I see _________.

# data[].attributes.body
Why did the author include the (whichever text feature you are focusing on) to support this selection?

Sentence stem:
The author included ________________ to support this selection by_____________.

# data[].attributes.body
First Grade

Q: How would you use text features to locate information and make predictions about a book?

Stem: I can use ________ features to help me locate _________.

# data[].attributes.body
Q:  How can you use text features to make predictions.
Stem:  I make predictions using.......

# data[].attributes.body
How Does the author’s  use of captions help you to be a better reader?

Captions help me be a better reader by......

# data[].attributes.body
Based on the caption, I can predict _______________________________________________________________________________.

# data[].attributes.body
Q:“Why are some words darker than others?”
Stem: Words are darker (bold print)  because....

# data[].attributes.body
Question: How can text features help us make predictions about a passage?

Sentence stem: We can use ________to locate info by...

# data[].attributes.body
Which text feature can you use to help you find information quickly in a text book?

The _______________ helps you find information quickly in a text book

# data[].attributes.body
How can you use text features to enhance important information in a writing passage? / Stem: Some text features we can use are...

# data[].attributes.body
How does bold print help you make predictions in a reading chapter?

Sentence stem: Bold print helps me make predictions by__________ because ____________

# data[].attributes.body
Question: Look at the picture/photograph. Make a prediction. Now read the caption. How does this caption confirm or change your prediction?

Stem: This caption confirms my prediction because ______. This caption changes my prediction because _________

# data[].attributes.headline
How do titles and subtitles increase my understanding of a reading passage?

# data[].attributes.subject
How do titles and subtitles increase my understanding of a reading passage?

# data[].attributes.body
I use titles and subtitles to _______ because _________.

# data[].attributes.body
Q: what conclusions can you draw from the data?
Stem: Based on the data, I can conclude that...

# data[].attributes.body
How does the table of contents help you locate something in a book?
Sentence Stem:
I use the table of contents to______
When I can't ______ I use the table contents.

# data[].attributes.headline
Question: How can text features help you identify the main idea of a non-fiction text?

# data[].attributes.subject
Question: How can text features help you identify the main idea of a non-fiction text?

# data[].attributes.body
Stem (at expectations): _______________ (text feature) helps you identify the main idea because it tells you _____________________________.
Stem (needs more support): Headings help you identify the main idea by telling you ___________________________.
Stem (above expectations): __________(text feature) helps you identify that the main idea of this text is : _________________ because _____________________.

# data[].attributes.body
Question: Why do you think some of these words are bold?
Stem: Some of these words are bold because ____________

# data[].attributes.body
What are the different types of precipitation?
Stem: The different types of precipitation are_______, ______ and _______.

# data[].attributes.headline
Question: How do bold words and the glossary allow readers to better understand the text?

# data[].attributes.subject
Question: How do bold words and the glossary allow readers to better understand the text?

# data[].attributes.body
Stem:  Bold words along with the glossary allow readers to better understand the text by ______

# data[].attributes.body
Question: How does bold print help readers?

Stem: As a reader, bold print helps me _________.

# data[].attributes.body
How did you use bold print and images to make predictions about the meaning of the text?

Stem:
On page ____ using the book ______ I predicted _________.

# data[].attributes.headline
Question:  Why do writers use bold print?

# data[].attributes.subject
Question:  Why do writers use bold print?

# data[].attributes.body
Stem: Writers use bold print to ____________________.

# data[].attributes.body
Question:
What do captions and titles help readers?

Stem:
This reminds me of the magazine about ______ because the caption showed how _________.

# data[].attributes.attachment_link.readable_text
Marzano's Six Step Process

In "Building Academic Vocabulary" (Marzano, 2004), Marzano outlines a comprehensive approach to learing the context specific academic vocabulary, or the brick words that students encounter in their reading. The first three steps help us introduce new terms during the frist lesson; the last three steps help students practice & reinforce those terms over time.

Remember: Describe, Describe, Draw, Do, Discuss, Play

Step 1: Describe - Instead of a standard definition, teachers give students a description or explanation of the word or term using examples and visuals. The goal is to appeal to learners of ALL types in order to help them understand new vocabulary.

Step 2: Describe - Students are asked to give their own description or explanation using their own words. By listening/reading student descriptions/explanations, we can assess mastery or provide help. Students record descriptions in their personal notebooks to reference later.

Step 3: Draw - Students draw representations of the new vocabulary word/term. Acceptable ways to complete this task include: drawing pictures, designing symbols, making graphics, creating cartoons, finding a visual on Internet or magazine. This can be done individually or in groups.

Step 4: Do - Give students more practice using new vocabulary words/terms. Have them participate in activities such as: identifying prefixes, suffixes, synonyms, antonyms, related words and additional visuals.

Step 5: Discuss - Students discuss words/terms as they work with/in partners, triads or groups. This conversation is more effective when structured. Monitoring discussions clears up any confusion students may have.

Step 6: Play - Students participate in games that reinforce deep understanding or new vocabulary words/terms. Examples of games include: Jeopardy, Wordo (like Bingo), Charades, Pictionary, Scrabble, etc...

If you like what you see be sure to follow along with #SiglerNation on Twitter. You can follow Matt Arend on Facebook and Twitter.

# data[].attributes.attachment_link.description
7 Steps...Language Rich Classrooms - By, John Seidlitz by McClure Marshals | This newsletter was created with Smore, an online tool for creating beautiful newsletters for educators, nonprofits, businesses and more