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On The Move Toward Excellence

Winter 2015

Preview

Your D187 weekly update!

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March

3/2 – Casmir Pulaski Day – SCHOOL IN SESSION

3/13 – End of Third Quarter

3/18 – Report Cards due to Principals

3/19 – Teacher Institute Day

3/20 – Parent Teacher Conferences (8:00-11:00)

3/23-3/27 – Spring Break – No school

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Attention ALL Staff

The Illinois 5 Essentials Survey is open. We are

asking that ALL staff spend 3-5 minutes to complete the survey before March 13th.

The information collected through the survey is reviewed and analyzed to generate a 5Essentials Report for each school. The 5Essentials Report includes a breakdown of teacher and student responses and, most importantly, provides a comprehensive picture of how schools fared on five factors that have been tied to school improvement. The five factors are:

• Effective Leaders

• Collaborative Teachers

• Involved Families

• Supportive Environment

• Ambitions Instruction

Please click on the link below to complete the survey:

https://survey.5-essentials.org/Illinois/

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Attendance Matters

Attendance has been steadily improving all year! Let’s reinforce our efforts to finish February strong!!!

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Inspiration Station PARCC ready

• What tools has PARCC created for educators

• How can these support classroom instruction

• Unpack and deconstruct sample tasks

http://fw.to/cMBMHFK

Graphic  organizers.  

Allow students to practice planning out their ideas in a visual form. In A Handbook for the Art and Science of Teaching (2009), Marzano states that, “The use of a wide range of graphic representations [such as graphic organizers] also enhances students’ reading comprehension and critical reasoning skills” (p. 74). To help students organize their thinking, then, you may wish to create a graphic organizer in which students can map out their ideas for an introduction, body paragraphs, and conclusion for each essay. Then, students can note their support and evidence that they plan to use underneath each box.

As the students begin to compose their essays, it is now much easier to focus on the writing, since they have taken the time to think through the content of the response. Plus, creating a written outline or list to plan out ideas may not be the best way for a visual learner to brainstorm; the graphic organizer will certainly aid these students.

Think-­‐alouds  and  modeling.  

Show students how to continue to revise their essays to catch areas that are unclear, disorganized, or faulty in their logic. To do this, model the revision step with a student or teacher-created sample of a rough draft of an essay. Walk students through the process of rereading the question/prompt, verbalizing their ideas, and then critically reviewing what they wrote.

For example, if the task requires the writer to describe the possible motivation behind a character’s actions, you could use your sample to think-aloud as you review and discover places in your essay where you made a point but failed to support your claim – and then model how to revisit the text to locate supporting evidence. Or, you could provide a sample in which the supporting details aren’t really relevant to what you are trying to explain. In any of these instances, model revising the words, ideas, and examples to accurately reflect understanding.

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North Chicago CUSD 187

Toolbox Tidbits Each issue, a new “tidbit” will be featured! When you use the tidbit in your classroom,

please email a brief summary of what you did and how your class responded!

From Marshall Memo 565: Using Data to See At-Risk Students’ Futures – and Change Them In this Kappan article, Jim Soland (Stanford University) says predictive analytics, inspired by their

use in baseball (Moneyball) and the stock market, are becoming popular in schools. Data experts look at various indicators (e.g., low attendance, poor grades, discipline issues) to predict which students are at risk of dropping out or having other problems.

But there are differences between baseball and stocks and K-12 schools. “Perhaps most important,”

says Soland, “teachers already know a great deal about their students – far more than an investor knows about a stock or a baseball scout about an up-and-coming pitcher. In fact, teachers are a veritable treasure trove of data on student behaviors, attitudes, and aspirations – information not typically included in a statistical model. Teachers also have far more power to shape what happens to students, an influence driven in part by their opinions of each kid.” Soland has found that teachers accurately predict which

students will drop out 89 percent of the time, very similar to the 88 percent track record for statistical models.

Practicing for PARCC

Each week until our PARCC testing is complete, we will focus on PARCC readiness tools!

Have you taken the PARCC practice test yet? If you have not, please take some time and review the different PARCC practice tests our students will be taking. The practice tests are available at http://parcconline.org/computer-based-samples. The tasks that are being asked of our students are very different than with ISAT or NWEA.

Student test tip…

- Stamina o Expect students to type for extended periods without complaint. Common Core State

Standards require this. Common Core State Standards require this. That’s what “one page in a sitting in 4th grade, 2 pages in a sitting in 5th grade, 3 pages in a sitting in 6th grade” means. The Assessments expects students have that sort of stamina. They’re long tests with lots of keyboarding and other tech skills. Make sure your students have practiced working at computers for extended periods.

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So do data models add any value? Absolutely, says Soland, for two reasons. First, teachers tend to overestimate the number of African-American and Hispanic students who will drop out and fail to

graduate; statistical data provide a check on this kind of subjectivity. Second, there’s the danger that being told that certain students are likely to drop out could change teachers’ assessment and subtly depress those students’ achievement – the Pygmalion effect. Soland believes these two reasons are an argument for combining statistical and human information in the same way that doctors combine sophisticated diagnostic data and their professional judgment. “Such combinations can allow users to capitalize on professional judgment while safeguarding against bias and incorporating the seemingly limitless

information made possible by computers,” he says.

Soland draws a distinction between early warning indicators (predicting which students are likely to drop out) and early warning systems (what’s done to prevent it). “Once the prediction is made, the job of educating begins,” he says. “… Early Warning Indicators only become Early Warning Systems when

educators have built supports and interventions for teachers and students around the predictions in a meaningful way.” Soland’s big point is that districts and states need to think through how they will put

data to work improving student outcomes and use that theory of action to decide which information to gather. Here are several possible data targets:

- Students who might be off-track for graduation but haven’t yet come to teachers’ attention;

- Keeping close tabs on students who are at risk of dropping out;

- Generating predictions that are less biased toward certain student subgroups;

- Monitoring how many students who were predicted to drop out actually do; how many of the predictions

were correct, and when they weren’t, what made the difference?

These possibilities aren’t mutually exclusive and there are others, says Soland, and next steps and costs will differ

depending on the choices made. Policy decisions at this level should drive the data-gathering process, ensuring

improved outcomes for at-risk students.

“Is ‘Moneyball’ the Next Big Thing in Education?” by Jim Soland in Phi Delta Kappan, December 2014/January 2015 (Vol. 96, #4, p. 64-67), www.kappanmagazine.org; Soland can be reached at jsoland@stanford.edu.