In this research, process mining methods are utilized for the analysis of the learning processes of fourth-year students. Multidimensional analysis is applied to gain a more comprehensive understanding of the data, and process cubes provide an overview of the data from various dimensions. Supported by Celonis tools, the learning process models are discovered from different perspectives such as time, courses, instructors, Course Learning Outcomes (CLO), and CLO scores. The application of these methods results in process models that provide insights from the perspective of different dimensions. Conformance checking is conducted to assess the alignment of the process models with the event log. The best conformance values for each process model are transformed into BPMN to facilitate information dissemination. The obtained information serves as recommendations for designing the optimal learning processes for fourth-year students in the subsequent semester.
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