Projects per year
Abstract
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.
| Original language | English |
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| Supervisors/Reviewers |
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| Publication status | Published - Feb 2023 |
Fields of science
- 102 Computer Sciences
- 102010 Database systems
- 102015 Information systems
- 102016 IT security
- 102025 Distributed systems
- 102027 Web engineering
- 102028 Knowledge engineering
- 102030 Semantic technologies
- 102033 Data mining
- 102035 Data science
- 509026 Digitalisation research
- 502050 Business informatics
- 502058 Digital transformation
- 503008 E-learning
JKU Focus areas
- Digital Transformation
Projects
- 1 Finished
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eTutor++ - An adaptive e-learning system with personalized exercising tailored to students’ individual learning curves
Ernst, F. (Researcher), Mühleder, C. (Researcher), Plösch, R. (Researcher), Schrefl, M. (Researcher), Schuhmann, D. (Researcher), Schütz, K. (Researcher) & Schütz, C. G. (PI)
01.06.2020 → 28.02.2022
Project: Funded research › Other mainly public funds