A Study of Predictors for Debugging Quality Among Preservice, Early Childhood Teachers

• In Event: AERA Poster Session 10
  In Poster Session: Learning and Communities in Online Education

Abstract

While there has been much progress in the meaningful integration of computer science within K-12 classrooms, there is a need to promote more equitable participation and to improve teacher preparation. One area in which this is needed is in early childhood education. In this paper, we investigated predictors of debugging quality among 19 pre-service early childhood teachers as they engaged in debugging supported by scaffolding. Bayesian regression indicated the following variables predicted debugging quality: debugging process score, English domain identification, performance approach goals, and sentiment analysis scores applied to what students wrote in response to scaffold prompts.

Authors

• Brian R. Belland, The Pennsylvania State University

• ChanMin Kim, Pennsylvania State University

• Eunseo Lee, The Pennsylvania State University

• Afaf Baabdullah, The Pennsylvania State University

• Yinqi Zhang, The Pennsylvania State University