International Journal of Mathematical Education in Science and Technology· 2026Q1
A systematic framework for designing second-order linear ordinary differential equation problems with controlled analytic complexity
- 0citations
- Q1SCImago
- 2026year
Short summary
A new framework systematically designs second-order linear ODE problems by controlling the analytic complexity of integrals in variation of parameters solutions.
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Key points
- Presents a systematic framework for designing second-order linear ODE problems.
- Controls analytic complexity by focusing on integrals in variation of parameters.
- Enables instructors to predetermine integral forms via characteristic roots and auxiliary functions.
- Facilitates the creation of problems with tractable solutions and controlled computational demands.
AI-generated from the title and abstract; the full text is not read.
Abstract
Designing assessment problems for second-order linear ordinary differential equations (ODEs) often requires instructors to anticipate the analytic complexity of the solution process, particularly the integrals arising in general solution methods such as variation of parameters. However, this selection process is frequently based on intuition and trial-and-error rather than on a systematic construction procedure. This paper addresses this gap by presenting a systematic and reproducible framework for designing second-order linear ODE problems with controlled analytic complexity based on the structural form of the integrals arising in the variation of parameters formula. By prescribing the characteristic roots and selecting suitable auxiliary functions, the framework enables instructors to determine in advance the integrals involved in the solution process. The proposed approach allows the construction of problems with analytically tractable solution procedures, predetermined structural features, and explicit control over the computational demands encountered during the solution process.
The authors' abstract, as published at the source. International Journal of Mathematical Education in Science and Technology, 2026 · DOI ↗
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Field: Modeling and Simulation
Modeling and SimulationMathematics