Sun, J., Ma, H., Zeng, Y., Han, D., & Jin, Y. (2023). Promoting the AI teaching competency of K-12 computer science teachers: A TPACK-based professional development approach. Education and Information Technologies, 28(2), 1509–1533. https://doi.org/10.1007/s10639-022-11256-5

Abstract:

“With the rapid development of artificial intelligence (AI), the demand for K-12 computer science (CS) education continues to grow. However, there has long been a lack of trained CS teachers. To promote the AI teaching competency of CS teachers, a professional development (PD) program based on the technological pedagogical content knowledge (TPACK) framework was intentionally designed in this research. A quasi-experimental design with a 25-day (75-h) intervention was conducted among 40 in-service CS teachers to examine its impact on AI teaching competency, including AI knowledge, AI teaching skills, and AI teaching self-efficacy. The quantitative data were collected via a pretest and posttest, and qualitative data were collected via artifact analysis and semistructured interviews. The results indicated that the TPACK-based PD program a) significantly improved CS teachers’ AI knowledge, especially in representation and reasoning, interaction, and social impact; b) developed CS teachers’ AI teaching skills, including their AI lesson plan ability and AI programming skills; and c) significantly improved CS teachers’ AI teaching self-efficacy, both in AI teaching efficacy beliefs and AI teaching outcome expectancy. These findings revealed the effectiveness of the TPACK-based PD program in improving the AI teaching competency of K-12 CS teachers and could help to expand the design of effective PD for CS teachers.”