Design and Implementation of a Module for the Alpha Algorithm in the Learning Platform eTutor++

F. Görner
Master Thesis
MT2302 (February, 2023)
Supervised by
Assoz.-Prof. Mag. Dr. Christoph Schütz
Instructed by
Simon Staudinger, MSc
Accomplished at
University Linz, Institute of Business Informatics - Data & Knowledge Engineering

Abstract (English)

The expansion of distance learning at universities, accelerated and amplified by the COVID 19 pandemic, has made the provision of e-learning platforms an integral component of teaching. In order to support this development, this master’s thesis introduces a new learning module. To better understand the concept of process mining, a learning module for the alpha algorithm was designed and implemented for the e-learning platform eTutor++. Students can use the learning module to enter the required steps of the alpha algorithm into a user interface based on a provided event log and receive automatically generated feedback and grading on their input. The learning module is integrated into the already existing eTutor++ framework and comprises the algorithm implementation, student submission evaluation logic, and back and front end implementation. In order to give students tasks, event logs must be generated to which the algorithm can be applied. This is accomplished by employing a process log generator that has been implemented and adapted specifically for this reason.