Applying Process Mining Techniques to Learning Management Systems for Educational Process Model Discovery and Analysis

Etinger, Darko; Orehovački, Tihomir; Babić, Snježana

doi:10.1007/978-3-319-73888-8_65

Cited by 6 publications

(2 citation statements)

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“…This technique aimed to detect differences between two groups of students (passing and failing). In an earlier research [28] Moodle was used in order to assess the LMS usage behavior.…”

Section: Lms Lad and Online Coursesmentioning

confidence: 99%

Reviewing Process Mining Applications and Techniques in Education

Sypsas¹,

Kalles²

2022

IJAIA

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Process Mining (PM) emerged from business process management but has recently been applied to educational data and has been found to facilitate the understanding of the educational process. Educational Process Mining (EPM) bridges the gap between process analysis and data analysis, based on the techniques of model discovery, conformance checking and extension of existing process models. We present a systematic review of the recent and current status of research in the EPM domain, focusing on application domains, techniques, tools and models, to highlight the use of EPM in comprehending and improving educational processes.

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“…This technique aimed to detect differences between two groups of students (passing and failing). In an earlier research [28] Moodle was used in order to assess the LMS usage behavior.…”

Section: Lms Lad and Online Coursesmentioning

confidence: 99%

Reviewing Process Mining Applications and Techniques in Education

Sypsas¹,

Kalles²

2022

IJAIA

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“…An LTL-based model checking tool was used to analyze moodle logs. Etinger et al [41] aimed to discover frequent behavioral patterns in event logs. The discovered process model is the starting point for evaluating the usage behavior of Moodle LMS.…”

Section: B Process Mining In Universitiesmentioning

confidence: 99%

Akıllı Kampüs Konsepti Altında Dijital Süreçler İçin Süreç Madenciliği Metodolojisi

Doğan

TIRPAN

2022

Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi

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Digital transformation affects universities as well as many industries. Universities are increasingly using various digital resources and systems to manage their knowledge. The smart campus, on the other hand, supports informed decision-making by integrating these resources and systems. Process mining provides real insights for digital transformation, allowing processes to be examined more transparently. This study aims to examine the proposed project implementation processes related to the smart university with the process mining methodology. For this purpose, 32 completed projects submitted to İzmir Bakırçay University Scientific Research Projects Coordinatorship (BAPK) with the proposed methodology adapted from Deming's continuous improvement cycle were examined. The data are taken from two different pages in the project automation system. According to the research findings, Projects are grouped into three categories: Guided Projects (GDM, 5 projects), Graduate Thesis Projects (TEZ, 5 projects), and Career Start Support Projects (KBP, 22 projects). 40.6% (13 projects) of the applications went directly to the project review stage, while 19 (59.4%) needed procedural correction. Considering the time from the creation of the application of 32 projects to the signing of the contract, it is seen that the arithmetic average of the cycle time is 15.1 weeks, and the median average is 52.5 days. The notable difference between arithmetic and median mean is that very few projects are of long duration. Procedural adjustments affect project evaluation cycle time by an additional 14 days. The carelessness or lack of knowledge of the applicants extends the cycle time of the process from 15 days to 53 days. The total duration of unnecessary waiting time in the process is 17 days. This study primarily proposes that non-digital processes should be digitized as soon as possible.

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