TY - GEN
T1 - Navigating the Challenges of Large Language Models in Construction Education in South Africa
T2 - Future Technologies Conference, FTC 2025
AU - Gyadu-Asiedu, Nana Akua Asabea
AU - Aigbavboa, Clinton
AU - David, Moloisi Malesela
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Digital technologies such as Large Language Models (LLMs) have transformed the construction industry, from design, planning, project management, execution, and building operations, with many processes now conducted remotely. However, integrating Large Language Models (LLMs) into construction education amidst rapid technological innovation presents significant challenges. The industry’s skills gap hampers productivity and innovation, while declining interest in construction-related university courses further underscores the need for innovative educational strategies. The study, therefore, explores the practical challenges of seamlessly integrating LLMs into construction education. Identifying such challenges emphasises the importance of understanding potential obstacles to ensure effective and responsible LLM adoption. This study explores these potential challenges through a comprehensive literature review and empirical findings from data collected via Google Forms from construction students, educators, and industry practitioners in Johannesburg, Gauteng. Convenience sampling was used, and data were analysed using inferential statistics such as the Kruskal-Wallis H test, an alternative to the one-way ANOVA, T-tests and Exploratory Factor Analysis. The findings reveal three clusters, which highlight the challenges as foundational challenges, context and ethical issues, and technical integration and usability issues. These findings make a case for the obstacles to LLM adoption in South African Construction Education. By investigating these challenges from industry and educational perspectives, the study concludes by recommending strategies to facilitate LLM integration, maximise benefits, and promote innovative, interactive, and skills-driven learning environments. It further emphasises the need to balance technological innovation with responsible integration to ensure positive outcomes for students, educators, and industry professionals.
AB - Digital technologies such as Large Language Models (LLMs) have transformed the construction industry, from design, planning, project management, execution, and building operations, with many processes now conducted remotely. However, integrating Large Language Models (LLMs) into construction education amidst rapid technological innovation presents significant challenges. The industry’s skills gap hampers productivity and innovation, while declining interest in construction-related university courses further underscores the need for innovative educational strategies. The study, therefore, explores the practical challenges of seamlessly integrating LLMs into construction education. Identifying such challenges emphasises the importance of understanding potential obstacles to ensure effective and responsible LLM adoption. This study explores these potential challenges through a comprehensive literature review and empirical findings from data collected via Google Forms from construction students, educators, and industry practitioners in Johannesburg, Gauteng. Convenience sampling was used, and data were analysed using inferential statistics such as the Kruskal-Wallis H test, an alternative to the one-way ANOVA, T-tests and Exploratory Factor Analysis. The findings reveal three clusters, which highlight the challenges as foundational challenges, context and ethical issues, and technical integration and usability issues. These findings make a case for the obstacles to LLM adoption in South African Construction Education. By investigating these challenges from industry and educational perspectives, the study concludes by recommending strategies to facilitate LLM integration, maximise benefits, and promote innovative, interactive, and skills-driven learning environments. It further emphasises the need to balance technological innovation with responsible integration to ensure positive outcomes for students, educators, and industry professionals.
KW - Challenges
KW - Construction education
KW - Digital adoption
KW - Large language models
KW - Technological innovation
UR - https://www.scopus.com/pages/publications/105021841540
U2 - 10.1007/978-3-032-07992-3_16
DO - 10.1007/978-3-032-07992-3_16
M3 - Conference contribution
AN - SCOPUS:105021841540
SN - 9783032079916
T3 - Lecture Notes in Networks and Systems
SP - 227
EP - 244
BT - Proceedings of the Future Technologies Conference, FTC 2025, Volume 4
A2 - Arai, Kohei
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 6 November 2025 through 7 November 2025
ER -