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Browsing College of Education by Subject "AI-assisted grading, AI-assisted software development, secondary computer science education, evaluation automation, formative assessment, artificial intelligence in education, teacher-developed AI tools, instructional design, assessment integrity, AI-driven feedback, workflow efficiency, student engagement, Saskatchewan education, data privacy in education, local network security, educational AI ethics, scalable grading systems"

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    Enhancing Computer Science Assessment with AI-Assisted Software Development
    (University of Saskatchewan College of Education, 2025-04-02) Brett William Balon
    This project report examines the AI-assisted development and implementation of a software grading system designed to enhance efficiency, accuracy, and pedagogical integrity in secondary computer science (CSC) education. Developed by a CSC educator with no formal programming background, the project explores the viability of AI-assisted software creation for automating grading processes while maintaining data privacy, reducing instructor workload, and preserving human oversight in assessment. The software, constructed through iterative refinement with AI-generated code, demonstrates how educators can leverage emerging technologies to optimize instructional design (ID) and improve learning outcomes without compromising professional autonomy or ethical considerations. This report positions AI-enhanced grading within the broader discourse of automation in education, highlighting both opportunities and challenges associated with AI-driven instructional tools. Unlike commercially available grading software, which often relies on external data processing and proprietary algorithms, this system operates entirely within local networks, prioritizing transparency and security. The project addresses critical concerns such as trust in automated assessment, scalability, and the accessibility of AI tools for educators with limited programming experience. Beyond its technical contributions, this report examines the pedagogical implications of integrating AI into assessment design. Drawing from Rancière’s philosophy of intellectual emancipation, the development of this system reflects an iterative, inquiry-based learning process, wherein cycles of refinement and problem-solving parallel broader educational paradigms. AI is framed not as a replacement for human expertise, but as an augmentative tool that, when applied with intention and oversight, has the potential to enhance both teaching practices and student engagement. By approaching AI-driven instructional design from an educator’s perspective rather than a computer scientist’s, this report provides practical insights for teachers seeking to integrate AI-assisted tools into their workflow. It argues that AI, when implemented responsibly, can serve as a means of professional empowerment, supporting pedagogical goals while maintaining ethical and instructional integrity.