Forecasting Construction Engineering Students’ Learning Outcomes by Means of Computational Pedagogys

Abstract

Introduction. The prediction of learning outcomes plays an important role in professional training of the future civil engineers. The relevance of the article lies in the lack of a unified approach to predicting the formation of basic professional competencies among students of civil engineering universities. The purpose of the article is to describe the creation of a technology for predicting the formation of professional competencies of future civil engineers using modern computer technologies. Materials and Methods. The study was carried out on the basis of the results of the analysis of publications on the creation of social and pedagogical forecasts by computer methods, followed by the construction of “competence-based profiles”. To study the problem, empirical information from the results of passed examinations, tests performed by students of the academic programme 03/08/01 “Construction engineering” (102 students) was analysed. The data were presented in a 3D OLAP cube format. Results. As a result of the research, the author has created a step-by-step technology for quantitative forecasting of the formation of general professional, professional and universal competencies of future civil engineers, in accordance with the educational standard. A competence-based profile of a student enrolled with the construction engineering university has been built. Donbass National Academy of Civil Engineering and Architecture served as experimental facility. The analytical tool “Competence calculator of a future civil engineer” was developed. The optimal time for forecast development was revealed: making a forecast at the early stages of training while maintaining suf ficient accuracy. Discussion and Conclusion. The results of the study open a new theoretical direction in the study of the influence of various factors on the results of pedagogical forecasting: identifying the dynamics of achieving each of the educational results in each of the academic semesters; study of factors and indicators of the forecast background.