The longitudinal effects of teacher judgement and different teacher treatment on students’ academic outcomes

Abstract

The self-fulfilling prophecy model of Brophy and Good was applied to the area of teacher judgement in order to disclose the processes of how teacher judgement of student achievement influences students’ future academic outcomes. It was assumed that achievement and achievement motivation might be affected through the mediating processes of student-perceived positive and negative teacher treatment, which represents students’ perceptions of teachers’ actions towards them. A sample of 294 Chinese fifth-grade students and their eleven English language teachers were tracked over one school year. Structural equation modelling showed that after controlling for prior achievement and achievement motivation, teacher judgement was directly related to students’ future achievement, expectancy for success and level of aspiration. These relations were partially mediated by perceived negative teacher treatment. Teacher judgement was related to students’ academic self-concept and pride in English learning, and fully mediated by both perceived positive and negative teacher treatment. The study supported the model of Brophy and Good and identified the specific processes of how teacher judgements can become self-fulfilled. Positive and negative teacher treatment had different mediating effects. Compared with positive teacher treatment, perceived negative treatment was related to student academic outcomes more extensively.

Keywords:

• Teacher judgement
• teacher behaviour
• academic achievement
• achievement motivation
• self-fulfilling prophecy

Acknowledgements

The authors would like to thank Prof. Jiannong Shi from the Institute of Psychology, Chinese Academy of Sciences, and Dr. Chenghong Jing from the Cadres Training Department, Chaoyang Branch, Beijing Institute of Education, for the great support to the data collection work, Prof. Dr. Anne Frenzel from Department of Psychology, the University of Munich, for providing valuable advice on structural equation modelling analysis, Christian Förtsch from Institute for Biology Education, the University of Munich for helping with Rasch analysis.