Educational Process Intelligence: A Process Mining Approach and Model Analysis

Okoye, Kingsley; Hosseini, Samira

doi:10.1007/978-3-030-49339-4_21

Search citation statements

Order By: Relevance

Paper Sections

Select...

Moocs1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to study dropout prediction in MOOCs process and sequence mining techniques were applied by Deeva et al [48] on event data gathered from the edX platform. EdX platform was also used to study educational process intelligence (EPI) [49] providing a contextual-based and informed learning process analysis and decision making through the PM approach. A FutureLearn MOOC was utilized as data resource, in order to investigate variation in learning processes [50].…”

Section: Moocsmentioning

confidence: 99%

Reviewing Process Mining Applications and Techniques in Education

Sypsas¹,

Kalles²

2022

IJAIA

View full text Add to dashboard Cite

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.

show abstract

Section: Moocsmentioning

confidence: 99%