Name: Jagadeesh R
Country: India

Year: 2026
Volume: Vol-16, issue-1, Year-2026 (JUNE special issue ) Special Issue: Ai, Ethics and Human Values : Shaping the Future of Higher Education
Page Number: 37-45
DOI: https://doi.org/10.5281/zenodo.21490333

ABSTRACT
Undergraduate mathematics students in Indian colleges can now compute topological indices, eigenvalues, and various graph energy formulations by entering a few lines of code into freely available packages. When a student can obtain the minimum dominating distance energy of a crown graph or the hyper-Zagreb index of a graphene sheet in seconds, the pedagogical question shifts from ―how do we teach the computation?‖ to ―what should we assess, and how?‖ This paper reports on a structured teaching experiment conducted across two academic semesters with final-year B.Sc. Mathematics students at a government college in Karnataka. In the control cohort, students solved graph energy and topological index problems entirely by hand. In the treatment cohort, students were given access to an opensource Python-based graph computation tool and were instead assessed on formulating conjectures, interpreting spectral properties, and constructing proof sketches. A comparison of pre-test and pos