Tag: teaching

Analytics
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What makes educator preparation effective?

As states build systems to evaluate the effectiveness of educator preparation programs, they must first know what “effectiveness” looks like. Are the characteristics of the candidates in the program, such as high school GPA, ACT or SAT score, or other admissions criteria, the most important indicators? What about the curriculum

Analytics | Students & Educators
Jennifer Bell 0
From compliance to commitment: The power of student growth data

As teachers, we lean into our experience. We trust our judgment about students and our instruction. We trade teaching stories with colleagues. And increasingly, we examine student growth data that illuminates our practice and occasionally suggests we refine our approach to individual students. In the past decade, states and districts

Students & Educators
Ada Lopez 0
Six Secrets Savvy Teachers Know

While successful teachers have different styles and personalities, they all have one thing in common: high-quality teacher-student relationships. Today, we have a wealth of information about teaching and learning. You can find entire books addressing specific classroom concerns. In the tips below, I’ll discuss the key elements that helped me

Students & Educators
Jennifer Bell 0
School, teacher, student data: Where do we grow from here?

Over the past few months, many US states and districts have received data about student growth and teacher effectiveness. Some educators experience the excitement of outstanding scores and, most importantly, the success of their students’ growth.  Some quietly plug along, satisfied to be meeting growth targets and deciding if it isn’t broken,

Students & Educators
Jennifer Bell 0
"March madness" of student course enrollment gets assist from value-added assessment

As teachers head into the madness of student course registration, the madness of college basketball reinforces a critical point: Data is crucial to making the picks that lead to a winning bracket, and student growth. Value-added assessment has proven reliable in determining which students are ready for their "one shining moment". This

Students & Educators
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Value-added myth busting, Part 4: Value-added models cannot measure growth of students who have missing data or are highly mobile

Students with missing test scores are often highly mobile students and are more likely to be low-achieving students. It is important to include these students in any growth/value-added model to avoid selection bias, which could provide misleading growth estimates to districts, schools and teachers that serve higher populations of these

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