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Hybrid E-Assessment in Higher Education: Semi-Automated Grading of Paper-Based Written Examinations

● high · 2026-06-10automated-grading, assessment, higher-ed, generative-ai, formative-assessment, llm, student-experience, ai-literacy, scaffolding, stem-education

Hartwig Grabowski, Michael Canz — cs.AI, cs.CV, cs.CY

This paper identifies the didactic narrowing caused by fully digital e-assessment (overuse of closed question formats) and proposes a hybrid approach that retains paper-based, problem-oriented examination tasks while enabling semi-automated grading. The core technical innovation is applying vision-capable LLMs to recognize handwritten characters in structured answer fields under realistic exam conditions, combined with a two-pass validation principle and comparison against a solution key to reduce misclassifications. The approach addresses organizational, technical, and legal constraints that become relevant in large student cohorts. This work connects Automated Grading research to real-world assessment practice by acknowledging that fully digital assessment often degrades assessment quality, even as institutions push for scalability. The hybrid approach could inform Formative Assessment redesign in large-enrollment STEM courses.

Connected Concepts

  • Automated Grading
  • Formative Assessment

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    • Citation

    Grabowski, H., & Canz, M. (2026). Hybrid E-Assessment in Higher Education: Semi-Automated Grading of Paper-Based Written Examinations. arXiv:2606.08855.