A Two-Step Clustering Approach for Improving Educational Process Model Discovery

Abstract

Process mining refers to the extraction of process models from event logs. As real-life processes tend to be less structured and more flexible, clustering techniques are used to divide traces into clusters, such that similar types of behavior are grouped in the cluster. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to better understand students' learning habits and the factors influencing their performance. However, the obtained models, usually, cannot fit well to the general students' behaviour and can be too large and complex for use or analysis by an instructor. These models are called spaghetti models. In the present work, we propose to use a two steps-based approach of clustering to improve educational process mining. The first step consist of creating clusters based employability indicators and the second step consist on clustering the obtained clusters using the AXOR algorithm which is based on traces profils in order to refine the obtained results from the first step. We have experimented this approach using the tool ProM Framework and we have found that this approach optimizes at the same time, both the performance/suitability and comprehensibility/size of the obtained model.

Motivations for Obtaining and Redeeming Coupons from a Coupon App: Customer Value Perspective

“…Recently, the spaghetti model issues have been solved by traditional clustering methods such as k-means [4], [7], [87] and hierarchical clustering algorithms [38]. Clustering methods are employed to determine the scope of a process in a way that the discovered model does not contain unnecessary traces and cases [38].…”

A survey on educational process mining

“…Professional training Cairns et al 32 To analyze social networks Cairns et al 31 To discover learning flows Doleck et al 2016 41 To gain a better understanding of the underlying educational process and detect learning difficulties Vahdat et al 42 Ariouat et al, 2016 43 To gain a better understanding of the underlying educational process Curriculum mining Trcka and Pechenizkiy 7 To gain a better understanding of the underlying educational process…”

“…Southavilay et al 39 To gain a better understanding of the underlying educational process and detect learning difficulties To gain a better understanding of the underlying educational process and detect learning difficulties Vahdat et al 42 Ariouat et al, 2016 43 To gain a better understanding of the underlying educational process…”

“…In order to do that, they measured the understandability of their process models through a complexity metric. Additionally, Ariouat et al 43 tried to identify the best training paths in real-world professional training databases from a global consulting company.…”

Profile-Based Cluster Evolution Analysis: Identification of Migration Patterns for Understanding Student Learning Behavior

“…The result of trace clustering produces homogeneous sets of traces from a full event log and constructs simpler process models [9]- [12]. Some works have used clustering to group students based on specific indicators (i.e., performance and activity) to obtain more specific and accurate models of students' behavior [13], [14]. In the domain of EPM, the event log can be partially cut in accordance with the timestamp (i.e., period of study or semester).…”