Mathematics, Vol. 12, Pages 2810: Causal Modeling of Academic Activity and Study Process Management

Mathematics, Vol. 12, Pages 2810: Causal Modeling of Academic Activity and Study Process Management

Mathematics doi: 10.3390/math12182810

Authors: Saulius Gudas Vitalijus Denisovas Jurij Tekutov

This article presents a causal modeling approach for analyzing the processes of an academic institution. Academic processes consist of activities that are considered self-managed systems and are defined as management transactions (MTs). The purpose of this article is to present a method of causal modeling of organizational processes, which helps to determine the internal model of the current process under consideration, its activities, and the processes’ causal dependencies in the management hierarchy of the institution, as well as horizontal and vertical coordination interactions and their content. Internal models of the identified activities were created, corresponding to the MT framework. In the second step, based on the causal model, a taxonomy of characteristics is presented, which helps to systematize the process quality assessment and ensures the completeness of the characteristics and indicators. Predefined structures of characteristic types are the basis of activity content description templates. Based on the proposed method, two causal models are created: the “to-be” causal model of the target study process (based on expert knowledge) and the “as-is” documented (existing) model of the study process used to evaluate the study process’s quality. The principles and examples of comparing the created “to-be” causal model with the existing study process monitoring method are presented, enabling the detection of the shortcomings in the existing method for assessing academic performance. Causal modeling allows for the rethinking of existing interactions and the identification of necessary interactions to improve the quality of studies. The comparison based on causal modeling allows for a systematic analysis of regulations and the consistent identification of new characteristics (indicators) that evaluate relevant aspects of academic processes and activities.