(Biased) Grading of Students’ Performance: Students’ Names, Performance Level, and Implicit Attitudes

Abstract

Biases in pre-service teachers’ evaluations of students’ performance may arise due to stereotypes (e.g., the assumption that students with a migrant background have lower potential). This study examines the effects of a migrant background, performance level, and implicit attitudes toward individuals with a migrant background on performance assessment (assigned grades and number of errors counted in a dictation). Pre-service teachers (N = 203) graded the performance of a student who appeared to have a migrant background statistically significantly worse than that of a student without a migrant background. The differences were more pronounced when the performance level was low and when the pre-service teachers held relatively positive implicit attitudes toward individuals with a migrant background. Interestingly, only performance level had an effect on the number of counted errors. Our results support the assumption that pre-service teachers exhibit bias when grading students with a migrant background in a third-grade level dictation assignment.

Informing the development of an E-platform for monitoring wellbeing in schools: involving young people in a co-design process

“…In the role of informant, young people contribute to the design process through offering insight and feedback on existing technologies, or on prototypes/early design ideas. Once the technology is developed, children may again offer input and feedback [ 31 ]. This cyclical framework informing the development and direction of digital tools has been thought to increase feelings of ownership and levels of engagement with participants [ 32 ].…”

Ethnic and Social Class Discrimination in Education: Experimental Evidence from Germany

“…Interestingly, 385 both van Ewijk (2011) and Sprietsma (2013) use a set of essays with varying quality but do not investigate the corresponding interaction effect. Bonefeld & Dickhäuser (2018) report a discriminatory bias against immigrants for a subset of teachers when performance was poor but not average. While investigating them is straightforward, predicting heterogeneous ef-390 fects across the competence distribution is less so.…”

“…Regarding sampling, only few experimental studies in the field of discrimination in education rely on random samples from a clearly defined population (e.g., van Ewijk, 2011;Sprietsma, 2013). Many experimental studies rely on convenience samples, often drawn from populations such as university students in education programs or preservice teachers (e.g., Schulze & Schiener, 2011;Glock et al, 2015;Bonefeld & Dickhäuser, 2018). In their sample, Glock et al (2015) even mix teachers from one European country with preservice teachers from another.…”

“…A model featuring interaction effects of essay quality and student background reveals that there is indeed discrimination on the basis of both social class and 720 ethnicity but only for the better of two essays (cf. Bonefeld & Dickhäuser, 2018). This can be interpreted as evidence for differential returns to essay quality: returns are lowest and not statistically significant for Turkish students, higher for German lower class students, and highest for German upper middle class students.…”

Rassismus und psychische Gesundheit

“…Aber auch für Deutschland zeigen Studien für diverse Lebensbereiche Ungleichheiten, die sich entlang der Zuschreibungen einer anderen ethnischen Herkunft, Hautfarbe oder Religion ergeben. Aktuelle empirische Studien weisen darauf hin, dass entsprechend kategorisierte Gruppen rassistischer Diskriminierung auf dem Wohnungsmarkt [1], im Bildungsbereich [9,11], auf dem Arbeitsmarkt [50] und im Gesundheitssystem [5] ausgesetzt sind.…”