The impact of high-stakes testing on the teaching and learning processes of mathematics

Autor: Özlem Kaplan Keleş, Cennet Göloğlu Demir
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Journal of Pedagogical Research, Vol 5, Iss 2, Pp 119-137 (2021)
ISSN: 2602-3717
Popis: The impacts of high-stakes testing administered within the framework of accountability policies concern all the stakeholders in the field of education, particularly the policymakers. As such, in the present study, which is specific to the mathematics course, the aim was to examine the impacts of high-stakes testing on teaching and learning processes, measurement and evaluation, communication, and motivation based on teacher perceptions. The study employed one of the qualitative research designs, namely phenomenology. The participants of the study were comprised of 13 middle school mathematics teachers identified via the maximum sampling technique. The data in the study were collected through the semi-structured interview technique and analyzed by using the content analysis method. The results of the study revealed that the teachers were inclined to use the traditional teaching method and solve multiple-choice tests, that the questions they used for the measurement of performance resembled those in high-stakes testing, and that the motivation of both teachers and the students were negatively affected. These findings were all similar to those frequently reported in the literature. Moreover, it was revealed that high-stakes testing prevented the consideration of individual differences and the teaching of values, that high-stakes testing was the focal point in communication, and that the impacts of high-risk testing showed a widespread impact upon different grades ranging from grade 8, during which the testing was done, down onto lower grades. Within the scope of these results, policymakers were recommended to take action toward improving the teaching process by acting together with the teachers to minimize the negative impacts of high-stakes testing on the process. 
Databáze: OpenAIRE