With the continual development of artificial intelligence and smart computing in recent years, quantitative approaches have become increasingly popular as an efficient modeling tool as they do not necessitate complicated mathematical models. Many nations have taken steps, such as transitioning to online schooling, to decrease the harm caused by coronaviruses. Inspired by the demand for technology in early education, the present research uses a radial basis function neural network modeling technique to predict preschool instructors’ technology usage in classes based on (...) recognized determinant characteristics of technology acceptance. In this regard, this study utilized the RBFNN approach to predict preschool teachers’ technology acceptance behavior, based on the theory of planned behavior, which states that behavioral achievement, in our case the actual technology use in class, depends on motivation, intention and ability, and behavioral control. Thus, this research design is based on an adapted version of the technology acceptance model with eight dimensions: D1. Perceived usefulness, D2. Perceived ease of use, D3. Perceived enjoyment, D4. Intention to use, D5. Actual use, D6. Compatibility, D7. Attitude, and D8. Self-efficacy. According to the TAM, actual usage is significantly predicted by the other seven dimensions used in this research. Instead of using the classical multiple linear regression statistical processing of data, we opted for a NN based on the RBF approach to predict the actual usage behavior. This study included 182 preschool teachers who were randomly chosen from a project-based national preschool teacher training program and who responded to our online questionnaire. After designing the RBF function with the actual usage as an output variable and the other seven dimensions as input variables, in the model summary, we obtained in the training sample a sum of squares error of 37.5 and a percent of incorrect predictions of 43.3%. In the testing sample, we obtained a sum of squares error of 14.88 and a percent of incorrect predictions of 37%. Thus, we can conclude that 63% of the classified data are correctly assigned to the models’ dependent variable, i.e., actual technology use, which is a significant rate of correct predictions in the testing sample. This high significant percentage of correct classification represents an important result, mainly because this is the first study to apply RBFNN’s prediction on psychological data, opening up a new interdisciplinary field of research. (shrink)

Due to digital transformation, technology advancements, telework, we can no longer pretend that traditional work offers high incentives and efficiency, but on the contrary, traditional work falls behind each year, deeming organizations and individuals to adopt the agile work. Rapid technological developments have altered the way businesses operate, with the goal of producing viable solutions in an environment fraught with unpredictability. This paper is a theoretical narrative review on the general topic of agile work. The present paper addresses the issue (...) of determining the best international practices for implementing agile methodology at work, carrying out a theoretical narrative review. Basing on literature on present-day theory the authors make an attempt to explain the implications of implementing agile methodologies into organizational culture, summarize existing approaches to classifying the main effects on implementing agile methodologies at work, consolidate and document best international practices for agile methodologies development among employers. After defining the concepts of agile method tailoring and agile maturity, the data obtained in the theoretical narrative analysis reveal that the implementing agile methodologies have a direct impact on management style, on teams, on learning environments, and on employee’s mental health. An overall conclusions and discussions section is presented along with the personal opinion of authors. This work is intended to open a post-pandemic agile work research methodology, since there are no systematic approaches to this topic. (shrink)