Dispositions of Technological Knowledge in Teacher Candidates – An Analysis of Predictors

Proceedings of The 4th World Conference on Research in Teaching and Education

Year: 2022



Dispositions of Technological Knowledge in Teacher Candidates – An Analysis of Predictors

Frederick Johnson, Joanna Koßmann, Christoph Schneider, Lothar Müller



In this paper, the impact of broader and more specific dispositions on technological knowledge (TK) is analyzed. TK is the fundament on which the technological pedagogical and content knowledge (TPACK) model is built on. According to contemporary behavioral competence theory, the predictors will be tested as cognitive, affective and conative dispositions for TK. Thus, multiple regression models are utilized to test according predictors of performance based and self-reported TK as criteria (N = 460). In the first model, broader sense predictors such as general self-efficacy, basic motives, intelligence and personality are introduced as predictors. The second model adds more specific predictors such as technology commitment, motives, attitudes concerning information and communications technology (ICT). The third model adds private and study related technology use with different devices. A precedent base model controls for gender and age. For performance-based TK as dependent measure, the third model (R2 = .261) indicates that intelligence (β = .197; p = .002), extraversion (β = -.143; p = .032), negative attitudes towards ICT (β = -.152; p = .033) and the private use of a PC (β = .176; p = .009) function as the most powerful predictors. In explaining self-reported TK, the second model (R2 = .280) indicates that technology commitment (β = .330; p = .000) and negative attitudes towards ICT (β = -.142; p = .036) are predictors. In conclusion, the prediction pattern between performance-based and self-reported TK differs. An explanation might be a practice effect from actual technology use.

keywords: competence; ICT attitudes; ICT motives; teacher candidates; TPACK.