Student self-efficacy in computing at the high school level

Many existing AI-focused educational programs for high school students are basic primers and lack technical depth. Can we design curricula such that high school students can learn the technical concepts underlying neural network design? A hypothesis is that research project scaffolds may be helpful towards that end. Another question is to study the effect of various kinds of teacher-scholar-mentor models on student self-efficacy in computing. For example, does a communication TA along with a "regular" TA enhance the educational output? What about learning assistants? There are two elements in this research project: experiments with high school programs, and data analysis of existing programs. For the first line of research, we need to devise strategies and collaborate with AI programs for high school students. For the second line of research, we need to develop mixed-methods for data analysis (student feedback, course evaluations, student reflections, etc.)


  1. S. Shailja, S. Yadav, A. Caetano, A. Pandey, "Scaffolding AI research projects increases self-efficacy of high school students in learning neural networks (Fundamental)" (accepted) American Society of Engineering Education (ASEE) Annual Conference and Exposition, 2024.

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