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Title: The impact of PISA on students' learning : a Chinese perspective
Author: Ding, Huiming
ISNI:       0000 0004 9356 316X
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2020
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This thesis investigates PISA’s impact on students’ learning in a local context, Fangshan District of Beijing, in China. PISA’s growing influence on educational policymaking in domestic education systems has been widely discussed, but concerns about policy borrowing and PISA’s governing power on education have been raised. However, these discussions rarely look further into local contexts to investigate PISA’s impact on students’ learning. Through mixed methods research, this thesis presents an investigation into the impact PISA has had on students’ learning and how this impact occurs. A conceptual framework employing theories about washback effect and ecological systems theory was developed to underpin the research. Sixteen local educational policymakers and practitioners were interviewed to identify how PISA is used in the local context, and to gather their views on the perceived impact of PISA on students’ learning. Fangshan PISA data were used to triangulate their perceptions, and also to expand the understanding of their use and translation of PISA data in policymaking. Thematic analysis of interview data reveals that PISA is perceived as a new perspective, which is different from domestic assessment in some aspects, for benchmarking the quality of local education. PISA is also used as an impetus motivating local initiatives to improve educational quality, in which some PISA concepts are integrated. The mechanism of PISA’s impact on students’ learning was conceptualised via making the factors of different contextual layers which negotiate PISA’s impact explicit. Interviewees perceived that through school enactment of the local PISA-motivated initiatives, and reforms of national curriculum and assessment, to some extent, students’ learning has been gradually fostered. These perceptions are largely supported by the trend analysis and multilevel modelling of PISA data. Research findings also indicate the challenges that the local PISA data users face for appropriately interpreting and translating PISA data to inform educational policymaking.
Supervisor: Homer, Matt ; Tasara, Innocent Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available