Work

Integrating agile methodologies and AI-assisted learning in web programming education: a theoretical framework for CS curriculum transformation

Year: 2026

Type: article

Abstract: This paper proposes a conceptual framework integrating agile methodologies with artificial intelligence tools to transform web programming education. Through design science research methodology combining systematic literature synthesis with thematic analysis of published implementation studies, we derive a three-pillar architecture combining iterative learning cycles, AI-augmented scaffolding, and continuous assessment. The framework addresses critical gaps between traditional educational approaches and contemporary professional practices while providing strategies for managing AI over-reliance, ensuring accessibility for diverse learners including neurodiverse and multilingual students, and maintaining assessment integrity. We position this work as a theoretical contribution requiring empirical validation, offering testable propositions and implementation guidance for future research.

Source: Discover Education

DOI: 10.1007/s44217-026-01179-5

Authors: Pavlo V. Zahorodko, Serhiy O. Semerikov

Institutions: Kryvyi Rih State Pedagogical University, Zhytomyr Polytechnic State University, Institute for Digitalisation of Education of the NAES of Ukraine, Academy of Cognitive and Natural Sciences

Language: English

Topic: Teaching and Learning Programming

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,390