Purpose-Learning as the way in which labor acquire new knowledge and skills has important strategic implications for the competitive advantage of an organization. The purpose of this paper is to present an agent-based modeling (ABM) approach to investigate the learning behavior of workers. The effect of interactions among different workers as well as the factors affecting the workers' learning behavior is assessed using the proposed ABM approach. Design/methodology/approach-For this purpose, the processes through which the competency value of worker is changed are understood and the workers' learning behavior is modeled, taking account of various influencing factors such as knowledge flow, social ability to teach and forgetting factor. Findings-The proposed model is implemented on a real steel structure project to evaluate its applicability and performance. The variation in the competency value of different workers involved in the project is simulated over time taking account of all the influencing factors using the proposed ABM approach. Practical implications-In order to assess the effect of interactions among welders as well as the welders' characteristics on their learning behavior, the competence value of different welders is evaluated. Originality/value-This research presents an ABM approach to investigate the workers' learning behavior. To evaluate the performance of the proposed ABM approach, it was implemented on a real steel structure project. The learning behavior of different welders (agents) was simulated taking account of their interactions as well as the factors affecting the welders' learning behavior. The project involved the welding of a 240-ton steel structure. The initial project duration was estimated as 100 days. In this project, it has been planned to execute the welding process using three different welders namely welder A, B and C.