Generative AI, Large Language Models, and ChatGPT in Construction Education, Training, and Practice DOI Creative Commons
Mostafa Babaeian Jelodar

Buildings, Journal Year: 2025, Volume and Issue: 15(6), P. 933 - 933

Published: March 15, 2025

The rapid advancement of generative AI, large language models (LLMs), and ChatGPT presents transformative opportunities for the construction industry. This study investigates their integration across education, training, professional practice to address skill gaps inefficiencies. While AI’s potential in has been highlighted, limited attention given synchronising academic curricula, workforce development, industry practices. research seeks fill that gap by evaluating AI adoption through a mixed multi-stage methodology, including theoretical conceptualisation, case studies, content analysis application strategic frameworks such as scenario planning, SWOT analysis, PESTEL frameworks. findings show tools enhance foundational learning critical thinking education but often fail develop job-ready skills. Training programmes improve task-specific competencies with immersive simulations predictive analytics neglect leadership Professional benefits from AI-driven resource optimisation collaboration faces barriers like regulatory interoperability challenges. By aligning practical training this highlights create future-ready workforce. provides actionable recommendations integrating domains. These contribute understanding role construction, offering baseline effective responsible adoption.

Language: Английский

Integrating text parsing and object detection for automated monitoring of finishing works in construction projects DOI

Jai‐Ho Oh,

Sungkook Hong, Byungjoo Choi

et al.

Automation in Construction, Journal Year: 2025, Volume and Issue: 174, P. 106139 - 106139

Published: March 23, 2025

Language: Английский

Citations

2
Ramasc: A Retrieval-Augmented Multi-Agent Framework for Automated Structural Calculation of Precast Concrete Floor Panels DOI
M. S. Jeong, Taegeon Kim, Kichang Choi

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
An assessment of record keeping practices at construction sites: Nepalese perspectives DOI

Uttam Neupane,

Bhupendra Prasad Jaisi

Records Management Journal, Journal Year: 2025, Volume and Issue: unknown

Published: April 30, 2025

Purpose This paper aims to present research findings that describe the current scenario of record keeping practices at construction sites and suggest possible measures. Design/methodology/approach Thirty ongoing projects were studied using a structured questionnaire survey. Sixty Web-based questionnaires distributed 30 clients/consultants contractors’ representatives through purposive sampling. The data was analyzed MS Excel Relative Importance Index (RII). Findings study reveals significant gaps in site records management, negatively impacting project efficiency success. Key issues include reliance on outdated paper-based documentation, lack awareness regarding management frameworks, insufficient training absence automated systems. Poor contribute delays, disputes, miscommunication cost overruns. Organizational cultural factors, including inadequate leadership regulatory awareness, exacerbate these challenges. align with global literature, highlighting need for digitalization, standardized practices, capacity building stronger policy enforcement. Research limitations/implications study’s focus Surkhet small sample size may limit its generalizability. It also does not assess financial feasibility digital adoption. However, offer useful insights policymakers, firms researchers improving record-keeping infrastructure, reforms. Practical implications To enhance Nepal’s industry, comprehensive programs are essential legislative frameworks modern tools. Companies should prioritize systems replace methods, ensuring accessibility integration These measures will address challenges, effectiveness reduce such as disputes projects. Social Improved industry can transparency, corruption promote accountability. Efficient lead better infrastructure quality, benefiting society safer more reliable public services. Originality/value offers new into Nepal, contributing knowledge developing countries where millions dollars spent construction.

Language: Английский

Citations

0
Tailored Vision-Language Framework for Automated Hazard Identification And Report Generation in Construction Sites DOI
Q. H. Chen, Xianfei Yin

Published: Jan. 1, 2025

Language: Английский

Citations

0
Generative AI, Large Language Models, and ChatGPT in Construction Education, Training, and Practice DOI Creative Commons
Mostafa Babaeian Jelodar

Buildings, Journal Year: 2025, Volume and Issue: 15(6), P. 933 - 933

Published: March 15, 2025

The rapid advancement of generative AI, large language models (LLMs), and ChatGPT presents transformative opportunities for the construction industry. This study investigates their integration across education, training, professional practice to address skill gaps inefficiencies. While AI’s potential in has been highlighted, limited attention given synchronising academic curricula, workforce development, industry practices. research seeks fill that gap by evaluating AI adoption through a mixed multi-stage methodology, including theoretical conceptualisation, case studies, content analysis application strategic frameworks such as scenario planning, SWOT analysis, PESTEL frameworks. findings show tools enhance foundational learning critical thinking education but often fail develop job-ready skills. Training programmes improve task-specific competencies with immersive simulations predictive analytics neglect leadership Professional benefits from AI-driven resource optimisation collaboration faces barriers like regulatory interoperability challenges. By aligning practical training this highlights create future-ready workforce. provides actionable recommendations integrating domains. These contribute understanding role construction, offering baseline effective responsible adoption.

Language: Английский

Citations

0