loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Gayane Sedrakyan 1 ; Stephan Braams 1 ; 2 ; Cosmin Ghiauru 1 ; Anton Tsankov 1 ; Stijn Schuurman 1 ; Matthijs Jansen op de Haar 1 ; Valeri Andreev 1 and Jos van Hillegersberg 1

Affiliations: 1 Department High-Tech Business and Entrepreneurship (HBE) Section, Industrial Engineering and Business Information Systems (IEBIS), University of Twente, Enschede, Overijssel, Netherlands ; 2 Cape Groep, Enschede, Overijssel, Netherlands

Keyword(s): Low-Code, Model-Based System Development, Business Models, Business Model Canvas, AI-Enabled Modeling, Requirements Engineering for Low-Code, Citizen Development.

Abstract: Low-code development platforms (LCDPs) are transforming business practices by shifting the focus from traditional, code-intensive approaches to business-centered modeling. These platforms enable citizen developers - non-technical employees within organizations - to build and manage applications that address specific business needs. This democratization accelerates time-to-market and encourages agile, co-participatory development. However, the rise of citizen development also introduces challenges, such as risks to quality, security, and governance, due to limited technical expertise among some users. This paper investigates ways to enhance current low-code practices by integrating AI-based support for text-to-model generation and established business frameworks, such as the Business Model Canvas (BMC). Incorporating BMC into low-code platforms reinforces their core strengths - minimizing code dependency while grounding development in business models. This integration can offer a stru ctured pathway for citizen developers to engage in meaningful learning while ensuring their projects align with organizational objectives. This approach positions low-code not only as a productivity tool aiming faster time to market, but as platforms for continuous learning and strategic alignment with business. The proposed integrations build on a novel feedback-inclusive approach, which received the innovative feedback nomination at the University of Leuven, Belgium1, and was informed by evidence-based learning experiences at the University of Twente, Netherlands. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.223.172.149

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Sedrakyan, G., Braams, S., Ghiauru, C., Tsankov, A., Schuurman, S., op de Haar, M. J., Andreev, V. and van Hillegersberg, J. (2025). Reinventing Low-Code: Value-Driven and Learning-Oriented Low-Code Development with SLLM-Integrated Approach. In Proceedings of the 13th International Conference on Model-Based Software and Systems Engineering - MBSE-AI Integration; ISBN 978-989-758-729-0; ISSN 2184-4348, SciTePress, pages 420-431. DOI: 10.5220/0013348200003896

@conference{mbse-ai integration25,
author={Gayane Sedrakyan and Stephan Braams and Cosmin Ghiauru and Anton Tsankov and Stijn Schuurman and Matthijs Jansen {op de Haar} and Valeri Andreev and Jos {van Hillegersberg}},
title={Reinventing Low-Code: Value-Driven and Learning-Oriented Low-Code Development with SLLM-Integrated Approach},
booktitle={Proceedings of the 13th International Conference on Model-Based Software and Systems Engineering - MBSE-AI Integration},
year={2025},
pages={420-431},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013348200003896},
isbn={978-989-758-729-0},
issn={2184-4348},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Model-Based Software and Systems Engineering - MBSE-AI Integration
TI - Reinventing Low-Code: Value-Driven and Learning-Oriented Low-Code Development with SLLM-Integrated Approach
SN - 978-989-758-729-0
IS - 2184-4348
AU - Sedrakyan, G.
AU - Braams, S.
AU - Ghiauru, C.
AU - Tsankov, A.
AU - Schuurman, S.
AU - op de Haar, M.
AU - Andreev, V.
AU - van Hillegersberg, J.
PY - 2025
SP - 420
EP - 431
DO - 10.5220/0013348200003896
PB - SciTePress