A Technological Pedagogical Content Knowledge (TPACK) Scale for Geography Teachers in Senior High School
Authors
Xiaobing Su
East China Normal University, Faculty of Education, School of Teachers’ Education
Author
Xiaorui Huang
East China Normal University, Faculty of Education, Institute of Curriculum and Instruction
Author
Chun Zhou
East China Normal University, School of Foreign Languages
Author
Maiga Chang
Athabasca University, School of Computing and Information Systems
Author
Keywords:
TPACK, Geography teachers, Development of measurement scales, Senior high school, Mainland China
Abstract
With information technology being employed extensively in school education,the TPACK (Technological Pedagogical Content Knowledge) theoretical framework is adopted by a growing number of researchers to study, assess and advance teachers’ ability to integrate IT into course teaching. However, there is no measurement instrument designed specifically to assess Geography teachers’ TPACK competences in Mainland China so far. In this study, based on the currently available TPACK measurement instruments, we attempt to develop, following the 7-factor TPACK model, a measurement scale for senior high school Geography teachers in Mainland China. Invitation emails were sent to target teachers and a total of 869 valid responses were received from 9 Mainland provinces. Confirmatory factor analysis was administered on the collected data to attest convergent validity and discriminant validity of the scale, as well as the 7-factor TPACK model. As demonstrated with our research findings, the TPACK knowledge structure of senior high school Geography teachers in Mainland China accords with the 7-factor model, with factor loadings of the 37 measured variables all distributed between 0.57 and 0.94, and composite validity values of each factor ranging between 0.87 and 0.93, which indicates the scale has good convergent validity; after the seven factors being paired with each other, the chi-square value differences between constrained and unconstrained models all reach the significant level of 0.05, which indicates the scale has good discriminant validity.