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Culture or Teacher Bias? Racial and Ethnic Variation in Student–Teacher Effort Assessment Match/Mismatch

Abstract

Three leading theories of racial achievement gaps in education include cultural capital match/mismatch, oppositional culture, and teacher bias. Cultural capital match/mismatch theory suggests that students and teachers do not share the same understanding of the standards, norms, and expectations required for achievement. Oppositional culture theory suggests that students may resist the standards, norms, and expectations of achievement, and teacher bias theory suggests that teachers have standards, norms, and expectations that privilege some students, but not others. The unifying thread in all three of these theories is how teachers and students perceive and execute the standards, norms, and expectations of schooling. This study offers a unique way of operationalizing whether and how cultural capital, oppositional culture, and/or teacher bias occur in everyday classroom practice and behavior by examining racialized patterns of student–teacher effort assessment match/mismatch. Using data from the Educational Longitudinal Study (Base Year 2002), I find no evidence for oppositional culture; net of other background characteristics, black students are less, and Hispanic students are no more likely than white students to agree with their teachers that they have low effort. Black and Hispanic students are more likely than white students to believe they are working hard when their teacher disagrees, but, consistent with cultural capital theory, socioeconomic background and academic skills account for all of their effort misalignment. Lastly, white and Asian students seem to benefit from positive teacher bias; net of background and skill, black and Hispanic students are less likely than white and Asian students to receive positive teacher effort assessment when they admit to not working hard.

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Fig. 1

Notes

  1. 1.

    Involuntary minorities are those who did not immigrate out of free will to their host country, whereas voluntary minorities are those who choose to immigrate to their host country (Fordham and Ogbu 1986).

  2. 2.

    There are other reasons why a student may describe himself or herself as exhibiting low levels of effort. For example, a student may resist schooling because of persistent failure. We cannot know from these data exactly why a student refuses to work hard, but Ogbu (1987) would suggest that if involuntary minority students exhibit this behavior more than white students, it may be indicative of oppositional culture.

  3. 3.

    The codebook did not specify the race with which the race-specified Hispanics identified. Because there was a large (n = 1,229) number of race-specified Hispanics, I combined them with non-race-specified Hispanics rather than eliminate them from analysis.

  4. 4.

    The IRT scores are preferable to the other standardized test scores available in the data set—standardized T (theta) scores. T-scores refer to students’ achievement level relative to the population of test takers, rather than a mastery of academic skill, which is better represented by the IRT scores.

  5. 5.

    Because it is likely that any effect seen in the regression models could be due to sampling design rather than an overall population characteristic, all multinomial logistic regression analyses adjust for individual student and school weights.

  6. 6.

    Test scores do not account for all minority students’ overrepresentation in the “student yes, teacher no” for English teacher-student combinations, though the magnitude of the coefficient for ethnicity is drastically reduced.

  7. 7.

    Gender and college prep track placement are also significant in this model. However, these two variables do not seem to attenuate black or Hispanic students’ overrepresentation in the category. When I ran a model (not shown) with only student race, SES, and school controls, SES was the only significant variable in the model, Hispanic students were no longer significantly overrepresented in the category, and the odds ratio for black students was consistent with the odds ratio presented in Model 3 of Table 4.

  8. 8.

    A Wald test of significance confirms that the interaction between student and teacher race is significant in Models 4 and 5 at 0.002.

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Correspondence to Karen Phelan Kozlowski.

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Kozlowski, K.P. Culture or Teacher Bias? Racial and Ethnic Variation in Student–Teacher Effort Assessment Match/Mismatch. Race Soc Probl 7, 43–59 (2015). https://doi.org/10.1007/s12552-014-9138-x

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Keywords

  • Education
  • Effort
  • Students
  • Teachers
  • Cultural capital
  • Discrimination