[Correction Notice: An Erratum for this article was reported in Vol 63(5) of (see record 2016-33161-001). The name of author Erika Feinauer was misspelled as Erika Feinhauer. All versions of this article have been corrected.] Individuals' strength of ethnic identity has been linked with multiple positive indicators, including academic achievement and overall psychological well-being. The measure researchers use most often to assess ethnic identity, the Multigroup Ethnic Identity Measure (MEIM), underwent substantial revision in 2007. To inform scholars investigating ethnic identity, we performed a reliability generalization analysis on data from the revised version (MEIM-R) and compared it with data from the original MEIM. Random-effects weighted models evaluated internal consistency coefficients (Cronbach's alpha). Reliability coefficients for the MEIM-R averaged α = .88 across 37 samples, a statistically significant increase over the average of α = .84 for the MEIM across 75 studies. Reliability coefficients for the MEIM-R did not differ across study and participant characteristics such as sample gender and ethnic composition. However, consistently lower reliability coefficients averaging α = .81 were found among participants with low levels of education, suggesting that greater attention to data reliability is warranted when evaluating the ethnic identity of individuals such as middle-school students. Future research will be needed to ascertain whether data with other measures of aspects of personal identity (e.g., racial identity, gender identity) also differ as a function of participant level of education and associated cognitive or maturation processes. (PsycINFO Database Record

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This study builds on previous work to examine parent reasons for enrolling their children in a two-way immersion (TWI) charter school. This work goes beyond ethno linguistic background variables (language, ethnicity), to include other key variables such as education level, income, religion, household distance from school, and family structure. This study takes place in one school-wide TWI program in a charter school where parents must choose and actively pursue enrollment. These highly motivated parents articulate, in their own voice, their reasons for choosing to enroll their children in this school. Using open-coding strategies, six overarching categories emerged from parent responses about their reasons for enrollment: Bilingualisms/Biliteracy, Educational Experiences, Future and Career Opportunities, Cultural Immersion/Diversity, Preserving Heritage, and Proximity to Home. Chi-square statistics are used to compare demographic characteristics across these six reasons. Our findings show that parents from many different background characteristics share a desire for their child to participate in TWI education. Additionally, there are many factors outside of language dominance that are relevant to parental decisions for enrollment. These data clearly showcase a highly motivated and diverse parent population who report various reasons for choosing the school for their children.

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In this article, the authors provide a methodological critique of the current standard of value-added modeling forwarded in educational policy contexts as a means of measuring teacher effectiveness. Conventional value-added estimates of teacher quality are attempts to determine to what degree a teacher would theoretically contribute, on average, to the test score gains of any student in the accountability population (i.e., district or state). Everson, Feinauer, and Sudweeks suggest an alternative statistical methodology, propensity score matching, which allows estimation of how well a teacher performs relative to teachers assigned comparable classes of students. This approach more closely fits the appropriate role of an accountability system: to estimate how well employees perform in the job to which they are actually assigned. It also has the benefit of requiring fewer statistical assumptions—assumptions that are frequently violated in value-added modeling. The authors conclude that this alternative method allows for more appropriate and policy-relevant inferences about the performance of teachers.