数学教育
科学教育
教育学
内容(测量理论)
心理学
教学方法
数学
数学分析
作者
Ernest Nkosingiphile Mazibe,Estelle Gaigher,Coréne Coetzee
标识
DOI:10.1080/02635143.2023.2296434
摘要
BACKGROUND :
\n
\nIt is commonly understood that teachers’ effectiveness is reflected by the performances of their students. On the other hand, teachers’ effectiveness is commonly associated with pedagogical content knowledge (PCK).
\nPURPOSE :
\n
\nThis paper reports a mixed method study exploring the relationship between teachers’ PCK and evidence of student learning in fundamental concepts of electrostatics.
\nSAMPLE :
\n
\nTwo in-service and two pre-service teachers as well as 133 students participated in the present study.
\nDESIGN AND METHODS :
\n
\nData reflecting teachers’ PCK was collected using classroom observations and interviews whereas evidence of student learning was explored using a performance test designed for this research. The PCK and the evidence of student learning were studied in terms of the concepts of electrostatic force, electric field, and electric field strength. The refined consensus model of PCK served as the conceptual framework for the study while the components of the topic-specific PCK model served as the analytical framework. Guided by the components, we developed a rubric to score teachers’ PCK on a four-point scale, separately for each concept. Students’ performance was also separately averaged for each concept. Quantitatively, correlation coefficients were calculated for each concept. Qualitatively, in-depth analysis of students’ test responses in the fundamental concepts was conducted in relation to teachers’ engagements with the corresponding concepts.
\nRESULTS :
\n
\nThe results revealed moderate correlations in terms of the concepts of electrostatic force and electric field strength whereas the correlation was weak in terms of the electric field. Furthermore, we found that the test responses of students often matched the way they were taught by their teachers, supporting the quantitative results.
\nCONCLUSION :
\n
\nTeachers’ PCK and student learning showed weak and moderate correlations that were positive and significant, suggesting that there are other factors beyond PCK that influence student learning.
科研通智能强力驱动
Strongly Powered by AbleSci AI