The Impact of Prior Knowledge and Gender on Preservice Teachers' Computational Thinking and Problem-Solving

• In Event: Models for Digital Learning in Computational and Game-Based Contexts

Abstract

Computational thinking (CT) and problem-solving (PS) are two key competencies that every individual should master in the 21st century. Prior knowledge and gender could affect the acquisition of CT and PS. This study developed a programming activity for 93 pre-service teachers. The participants’ CT skills, CT dispositions, PS skills, and perceived PS were measured before and after this activity. Results showed that the low prior knowledge (LPK) group had a significant increase in CT skills, while the high prior knowledge (HPK) group has a significant decrease. Also, the improvement of PS skills of HPK participants was significantly higher than that of LPK participants. The gender difference was only identified in attitudes, including CT disposition and perceived PS skills.

Authors

• Hao-Yue Jin, University of Alberta
  Presenting Author

• Maria Cutumisu, McGill University
  Non-Presenting Author