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Creators/Authors contains: "Baabdullah, A."

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  1. ; ; ; ; ; ( , 2023 Annual Meeting of the American Educational Research Association)
    To use robots within early childhood education requires the preparation of early childhood teachers to use and teach block-based programming. We used a hierarchical linear model approach to address our research question: How can study cohort, cognitive challenge types, and motivational challenge types be used to predict lesson plan quality? Positive motivational challenge predictors were task value of programming, task value of teaching, mastery goals of programming, belonging in teaching, and autonomy in robotics. Negative motivational challenge predictors were mastery goals of teaching, belonging in robotics, self-efficacy in teaching, autonomy in programming, and autonomy in teaching. Positive cognitive challenge predictors were technical issues, problem solving - higher-order skills, and lesson design - other issues. 
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  2. ; ; ; ; ; ( , 2022 IUSE summit)
    Accepted Manuscript Full Text Available
  3. ; ; ; ; ; ( , Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022)
    Chinn, C. ; Tan, E. ; Chan, C. ; Kali, Y (Ed.)
    Accepted Manuscript Full Text Available
  4. ; ; ; ; ( , Annual meeting program American Educational Research Association)
    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. 
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    Accepted Manuscript Full Text Available