On the quest for validity: Testing the factor structure and measurement invariance of the technology-dimensions in the Technological, Pedagogical, and Content Knowledge (TPACK) model

Abstract

Highlights  A general TPACK factor and a specific TK can be disentangled.  The T-dimensions in the TPACK are highly correlated (ρ > .80).  Measurement invariance across gender and educational track can be established.  Significant gender differences in the T-dimensions exist.  In conclusion, the TK factor stands out among all T-dimensions.

Self-reported TPACK of teacher educators across six countries in Asia and Europe

“…Koh et al (2010) revealed the importance of the gender factor in the TPACK perceptions of pre-service students. This study is consistent with other studies like that of Markauskaite (2006), who showed that male teachers are more confident in using computers than their female colleagues; Lin et al (2013), who found higher PK for female teachers but lower TK; and Scherer et al (2017), who found that for all the T-factors, males report higher competency than females. However, thinking gender as predictor of TPACK can be interpreted as an essentialist view of the knowledge determinants.…”

Course‐level modeling of preservice teacher learning of technology integration

“…Empirically, Abbitt () found statistically significant correlations between preservice teachers' TPACK subscale scores (TK, PK, TPK, TCK, TPCK), collected from Schmidt et al 's survey, and their self‐efficacy beliefs, collected from Wang et al 's survey. Moreover, researchers have viewed Schmidt et al 's survey as capturing teachers' self‐efficacy beliefs related to TPACK domains (Scherer et al , ). In addition, technology integration researchers have found positive correlations between preservice teachers' technology integration self‐efficacy beliefs and their intentions to use technology in future classrooms (Banas & York, ; Celik & Yesilyurt, ; Lee & Lee, ; Sang, Valcke, van Braak, & Tondeur, ).…”

“…Empirical evidence has suggested the need to pay extra attention to technology‐related knowledge (TK, TCK, TPK, TPCK) when examining preservice teachers' TPACK (Chai et al , ; Mouza et al , ). More recently, Scherer and colleagues () explored factor structures with TK, TCK, TPK and TPCK data from preservice teacher in Flanders and found that a nested factor structure performed the best. In particular, all items loaded on one general factor (TPACK‐general) and the TK items additionally loaded on another (TK), highlighting TK as the unique dimension to be captured apart from the other technology‐related knowledge (TCK, TPK, TPCK), which failed to be empirically disentangled.…”

“…For example, Drummond and Sweeney () proposed inclusion of objective indices of TPACK (ie, items that allow respondents' determination of truth‐hood) to supplement preservice teachers' TPACK assessment. On the other hand, Scherer and colleagues () explored factor structures in the T‐dimensions (TCK, TPK, TPCK and TK) and found that the data best supported a nested factor structure consisting of general TPACK factor and specific TK factor. Their finding was based on a correlated traits approach, as opposed to a structural relations approach; however, after finding high correlations between the T‐dimension factors, the authors recommended also examining potential structural relations.…”

“…As of 2012, over 141 TPACK measurements had been developed (Koehler, Shin, & Mishra, ), and scholars are still continuing to use TPACK to understand preservice teacher knowledge and learning (eg, Baran, Canbazoglu Bilici, Albayrak Sari, & Tondeur, ; Tseng, Cheng, & Yeh, ). In particular, recent studies have focused on technology‐related dimensions (TK, TCK, TPK, TPCK) to examine preservice teacher learning of technology integration (eg, Scherer, Tondeur, & Siddiq, ).…”