Automated Generation of Individualized Electrical Circuit Exercises Using Python and LTspice: Reducing Instructor Preparation Time

This study presents a methodology for the automatic generation of individualized electrical circuit exercise booklets using Python and LTspice and examines the academic outcomes observed after its implementation and its estimated effect on instructor preparation time. The methodology begins with the design of circuit theory exercises, which are subsequently parameterized and automatically simulated through Python scripts integrated with LTspice. Based on the simulation results, the system generates individualized exercise booklets, solution templates, and simulation files for each student while simultaneously collecting quantitative data to assess academic performance. The proposed approach enables both formative training and individualized assessment without substantially increasing the instructors’ workload. Descriptive comparison with previous academic years indicates no deterioration in academic outcomes, although the cohorts compared are not concurrent and no inferential testing was performed, so no causal claim about learning can be made. Combining measured execution times with estimated manual preparation times indicates a reduction of more than 95% in the time required to prepare individualized exercises for a cohort of 70 students, making it feasible to generate new individualized materials even for large classes. The methodology is also designed to strengthen the connection between theoretical concepts and practical laboratory activities, as the generated exercises are solved during lectures and later validated experimentally. Overall, the proposed system provides a scalable approach for generating and managing individualized educational resources while reducing instructors’ repetitive workload.