Building a Competency Model Student Training

Abstract

Decision-making in the field of education is a complex, multi-faceted process, in which a large circle of stakeholders is involved. Of no small importance for making a correct decision is the analysis of information coming from participants in the educational process at its various stages. The article proposes a methodology for constructing and applying a competency-based training direction model. The technique is based on the use of developed algorithms for building competency models. Due to the use of the Bayesian network, an assessment of the formation of the level of competence is possible even with missing data, i.e. with unknown results of competency-based tasks. The technique bridges the gap between strictly subject structuring of assessment tools, which does not fully correspond to the competency-building model of constructing the main educational program, and activity-based structuring. The article describes the conduct of two experiments conducted to verify the algorithms proposed in the theoretical part. Experimental testing showed that the developed algorithms, method and methodology are suitable for constructing a competency-based model of discipline and the direction of training. The models built according to the methodology, make it possible to make informed judgments regarding the level of students' competency levelling, as well as to predict student performance. Thus, using the methods of intellectual analysis of educational data, the tasks of decision support are solved.