making sense of data to improve teacher selection (aera)

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Making Sense of Empirical Data to Improve Teacher Selection April 2011 AERA Symposium Tracy Brisson, Founder and CEO The Opportunities Project

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My presentation as part of the Teacher Pathways presentation on April 11, 2011 at the American Educational Research Association (AERA) conference in New Orleans.

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Page 1: Making Sense of Data to Improve Teacher Selection (AERA)

Making Sense of Empirical Data to Improve Teacher Selection

April 2011

AERA SymposiumTracy Brisson, Founder and CEO

The Opportunities Project

Page 2: Making Sense of Data to Improve Teacher Selection (AERA)

Research Questions

How can school districts use data to improve the recruitment and hiring of effective teachers?

Do school districts have a role in assisting teacher applicants in the hiring process to make them more

effective and desirable employees?

Page 3: Making Sense of Data to Improve Teacher Selection (AERA)

Conceptual Framework and Relevance

• Narrative inquiry and reflective practice of time as Director of Teacher Recruitment for New York City Public Schools

• Consumer AND gatekeeper for graduates of education schools

• Public impatience with local politics, education and teachers

Page 4: Making Sense of Data to Improve Teacher Selection (AERA)

The “Scary” Facts about Teaching

• Decreasing public money for schools

• Decreasing enrollment

• Out of 16 majors tracked in the class of 2010, education graduates had the lowest job offer rate- 23.7%

Source: National Association of Colleges and Employers (NACE)

Page 5: Making Sense of Data to Improve Teacher Selection (AERA)

Sense-making of Multiple Roles

Director of Teacher Recruitment

Leader

Implementer

Researcher

Subordinate

Page 6: Making Sense of Data to Improve Teacher Selection (AERA)

Sense-making Steps

Synthesize Information

Develop Model

Implement Model

Evaluate and

Reflect on Model

Change Model

Applicant Support

Page 7: Making Sense of Data to Improve Teacher Selection (AERA)

Synthesize Information

ResearchPolicy Demands

Best Practices

Principals

Page 8: Making Sense of Data to Improve Teacher Selection (AERA)

Develop and Implement Model

Competencies

• Instructional Knowledge & Skills

• Content Knowledge

• Communication Skills

• Four non-instructional competencies

Align tools to competencies

• Application questions

• Application screening

• Interview questions

Page 9: Making Sense of Data to Improve Teacher Selection (AERA)

Evaluate and Reflect

Evaluating value-add model results

1. Match scores to beliefs2. Discuss best and worst guesses3. Discuss actual “best” performing

teachers4. Discuss other reflections

Page 10: Making Sense of Data to Improve Teacher Selection (AERA)

Change Model

• Changed competencies• Combined, Added and Removed

• Added better evaluation tools• Math assessment and role plays

• Provided candidate job search support

Page 11: Making Sense of Data to Improve Teacher Selection (AERA)

Applicant Support

Introduced webinars on resumes, interviews, job search, and related topics• 40% of applicants attended a webinar• 90% of participants reported they’d recommend service

Questions: • Where does this responsibility lie? Colleges?• What will happen if the district can’t provide these

services?

Page 12: Making Sense of Data to Improve Teacher Selection (AERA)

Questions for Faculty

What is your responsibility to your students in today’s economy?

How do you make sense of your different roles as a faculty member in teacher preparation?

What does a rigorous research line in this inquiry area look like?

Page 13: Making Sense of Data to Improve Teacher Selection (AERA)

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Contact

Thank You!

Questions