Work

Automating the Assessment of Technical Writing Skills Via Ai-powered Tools in It Education

Year: 2026

Type: dataset

Abstract: This article investigates the potential of AI-powered tools for automating the assessment of technical writing skills in IT education. The study reviews current developments in automated writing assessment, identifies key competencies required for technical communication in computing disciplines, and proposes an AI-based framework for evaluating student submissions. The framework integrates NLP techniques, machine learning algorithms, and rubric-based assessment methods to evaluate grammar, coherence, structure, technical accuracy, and readability. The article further discusses the reliability, validity, and educational implications of automated assessment systems. The findings suggest that AI-powered assessment can significantly reduce instructor workload, provide timely feedback, and support personalized learning experiences while maintaining acceptable levels of assessment accuracy. However, challenges related to transparency, fairness, and ethical implementation remain important considerations for educational institutions.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.20530238

Authors: Adila Tadjibayeva, Zilola Yahyoqulova, Worldly Knowledge Publishing Centre

Institution: Fergana State Technical University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7163402633

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