## 2 Materials and Methods
### Learning and Forgetting Phenomena
#### 2.2.2. LAF in Construction Industry  
The influence of the learning effect on the performance of groups of employees when performing repetitive activities has been studied in many articles. The article [58] presents the problem of the increase in efficiency observed during the research on efficiency in the construction of 15 multi-story reinforced concrete buildings located in Italy. The obtained research results allowed for the assessment of the learning rate at the level of 85% to 95%, which makes it possible to determine the costs and times of carrying more accurately out similar works in this country. The publication [59] investigated the impact of the learning effect on the efficiency of installing slab formworks for building construction. The observed learning rates ranged from 95% to over 99%. Such high learning rates, according to the authors, could have been caused by the volatility of the conditions of the works: a change in the number of working groups, a change in the duration of working shifts or a change in the remuneration incentive system. The problem of establishing a learning curve model for the efficiency of works in the implementation of prefabricates in construction was presented in the article [60]. The authors, based on data from the period of 5 years, for 90% of works related to the production of prefabricated elements, determined a learning curve model based on exponential functions. According to the authors' research, the obtained model has a satisfactory degree of fit and allows for a very accurate ability to predict future performance. The issue of determining the learning curve was also tackled in the paper [61]. This time, the authors dealt with repetitive and complex activities that occur when making prefabricated floating caissons. They used a simulation method to predict future performance outcomes generated by the generated learning curve. Another type of repetitive works in which the influence of the learning effect can be noticed are insulation renovation works during the construction of roofs of buildings [62]. Based on the questionnaire survey, the authors checked which of the known mathematical models better reflects the learning phenomenon for this type of works. The presented literature review on taking into account the learning phenomenon for repetitive activities in construction shows a very wide range of types of construction works in which this phenomenon occurs. The research is currently being continued in order to find the best possible understanding of this phenomenon in construction. The second problem faced by researchers is the inclusion of the phenomenon of learning, as well as learning and forgetting, in scheduling projects with repetitive activities. Figure 1: Sample learning and forgetting process. The best-known methods of scheduling such projects in construction are the LOB method and many other techniques based on it [1]. An article [6] presented research on including the learning effect during the calculation of parameters calculated for schedules created with the use of the LOB method. The following factors are taken into account: the number of activities in one facility/unit, the complexity of activities, and working and management conditions. When considering the learning process, there may be certain and uncertain information, which is why the fuzzy sets theory was used for this purpose. The problem of taking into account learning and forgetting curves when setting the dates of commencement and completion of construction activities planned with the LOB method was presented in the article [7]. The authors stated that the use of such curves for the LOB method allows for more realistic schedules of repetitive undertakings. The article [8] presents an original learning curve developed by the authors for monitoring the improvement of employee performance as a result of learning. Additionally, the authors present an improved LOB method that takes into account the new learning curve and is based on the mechanism of optimal allocation of resources.