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DATA ANALYSIS FOR SUBGROUPS OF STUDENTS

Data Analysis for Subgroups of Students

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Page 1: Data Analysis for Subgroups of Students

DATA ANALYSIS FOR SUBGROUPS OF STUDENTS

Page 2: Data Analysis for Subgroups of Students

© Relay Graduate School of Education. All rights reserved. 2

AGENDA OBJECTIVES

Agenda and Objectives

• Teaching Context• Data Analysis for All Students• Data Analysis for Subgroups of

Students• Data Analysis for One Student

Compare examples of a written teaching context to determine characteristics of a strong submission

Identify requirements for academic analysis in the Data Narrative

Compare various graphs, charts, and tables to determine best practices for displaying student data

Compare various summaries and explanations to determine best practices for describing student data

Describe relationships between various measures of student performance

Page 3: Data Analysis for Subgroups of Students

© Relay Graduate School of Education. All rights reserved. 3

Subgroups: Rubric & Assessment Template

This is in your Handout

Page 4: Data Analysis for Subgroups of Students

© Relay Graduate School of Education. All rights reserved. 4

Read Kip’s Subgroups Section. Consider Questions Below.

1) What is one strong feature of the research questions Kip chose?

2) What is one strong feature of the rationale for the research questions that Kip wrote?

3) What is one strong feature of Kip’s disaggregation and analysis?

Page 5: Data Analysis for Subgroups of Students

Click ahead when you’ve read the

appropriate section of the Sample Data

Narrative

Page 6: Data Analysis for Subgroups of Students

© Relay Graduate School of Education. All rights reserved. 6

Strong Features of the Research Questions?

1) Research questions are minable—he can thoroughly explore this question

2) Research questions are crisp—they are succinct and easy to understand

3) Research questions are meaningful—there is a rationale for why I should care

Page 7: Data Analysis for Subgroups of Students

© Relay Graduate School of Education. All rights reserved. 7

Strong Features of the Rationale for Research Qs?

1) Rationale is clear—it uses everyday language and directly addresses the research question

2) Rationale is compelling—it is written from a perspective of “the answer to this question matters”.

3) Rationale leaves the reader eager to review the analysis

Page 8: Data Analysis for Subgroups of Students

© Relay Graduate School of Education. All rights reserved. 8

Strong Features of Disaggregation and Analysis?

1) Analysis is clear—the framing and sequence of the analysis is easy to follow

2) Analysis is compelling—it digs deep to address the research question (even if he hits some walls)

3) Analysis is correct—the data, the inference, and the final take-away are right

Page 9: Data Analysis for Subgroups of Students

© Relay Graduate School of Education. All rights reserved. 9

Why Does the Rubric Say “Address,” not “Answer?”

Page 10: Data Analysis for Subgroups of Students

© Relay Graduate School of Education. All rights reserved. 10

Why Does the Rubric Say “Address,” not “Answer?”

We want you to clearly,

compellingly, and correctly address

the question.

The aim here is not to “answer” a

simple question.

The aim is to “address” a

minable question.