Process Mining in Learning Analytics: Benefits and Challenges

Running head: RESEARCH PROPOSAL
Research proposal on "Process Mining in Learning Analytics: Benefits and challenges"
Name of the Student:
Name of the University:
Author note:

1
RESEARCH PROPOSALIntroduction
This research proposal aims to explore and evaluate the impact of process mining on the
learning analytics and investigate its benefits and challenges in the learning analytics. Process
mining has a crucial role in the digital transformation and it is a set of techniques in process
management. Process mining refers to the analysis methods of processes in the systems of a
business based on the data extracted from the event logs in the present information system of an
organization [1]. This system goes beyond the key data of the system or process and it
recognizes the contextual relationships of the business processes collected from the event logs,
which are presented in the form of graphics for diagnosing problems in the business system and
formulating improvement measures. Hence, process mining helps in detecting or diagnosing
problems in the business processes on the basis of the facts and not on the basis of intuition [2].
On the other hand, learning analytics refers to the measurement, collection, analysis and
reporting of the data regarding the learners and the learning contexts in order to understand and
optimize the learning process and the environment. Thus, learning analytics is based on the
above mentioned steps and it includes measures to observe the learners and process of learning,
reflect and improve the process and environment of learning and teaching [3]. Thus, it can be
said that the techniques of process mining include steps that are implemented to improve the
systems based on the knowledge gathered from the event logs and the system of learning
analytics includes steps to improve the learning process and organization on the basis of the data
measured, collected, analyzed and reported. Hence, there can be a potential positive outcome if
process mining can be implemented in learning analytics. Through this research study, the
benefits and challenges of incorporating process mining in the learning analytics will be
investigated and evaluated.

2
RESEARCH PROPOSALLiterature review
"A general process mining framework for correlating, predicting and clustering dynamic
behavior based on event logs." By Massimiliano De Leoni, Wil MP van der Aalst, and
Marcus Dees.
The above article describes the framework of a general process mining for the purpose of
correlation, prediction and clustering the dynamic business behavior on the basis of event logs.
The authors stated that process mining acts as a missing link between the data oriented analysis
techniques and model based process analysis. The organization put much effort on process
discovery, to replay the techniques for checking conformance and for analyzing the bottlenecks
in the systems. The organizations can address the compliances and performance issues by using
these techniques in a much easier manner. By applying the process mining framework, the
organizations can address various processes in a more systematic manner. The authors suggested
that process and data mining techniques should be implemented alongside to have a better
knowledge of the system performances and the defects by correlating the information gathered
from the processes and it helps in addressing those issues in a more precise and faster manner
[4].
"e‐Research and learning theory: What do sequence and process mining methods
contribute?." By Peter Reimann, Lina Markauskaite, and Maria Bannert.
In the above article written by Reimann, Markauskaite, and Bannert (2014), sequence and
process mining methods are highly useful in the leaning theories and e-research as these are