Exploration and Visualization of Learning Behavior Patterns From the Perspective of Educational Process Mining

Abstract

The data in modern educational information systems are not given enough attention and are not fully utilized. Therefore, the motivations of our study are to preliminarily explore learning behavior patterns by applying process mining to educational datasets, and construct prediction models based on previous learning behavior. The data in modern educational information systems can be used by teaching managers to analyze various aspects of the educational process from different perspectives. We prepare to choose three datasets randomly which include student number, courses and grades attributes from a university's educational information systems. This paper firstly applies system clustering to give an overview of students' academic performance, and roughly determines clustering number. In order to ensure the accuracy which is relevant to the analysis of students' learning behavior patterns, a semi-biased statistic is proposed to quantitatively determine clustering number. Then, the data are clustered by fast clustering algorithm, and the clustering effect is cross-validated which is aimed at accurately analyzing the behavior patterns of student groups and using data visualization technology to visualize different student groups. Finally, the support vector machine is used to construct a classifier for predicting the learning behavior pattern, and the parameters in the support vector machine are optimized by Bayesian optimization, genetic algorithm optimization and whale optimization respectively. The research found that: 1) In the equal test of the group mean, when the significance of most courses is less than 0.05, it means that there is a significant difference among different categories. In this case, using the semi-biased statistic proposed in the paper is helpful to improve clustering effect. 2) The better the students learn, the better the clustering effect of the category which they belong to is. 3) Whale optimization algorithm works best.INDEX TERMS Educational process mining, learning behavior patterns, student profiles, support vector machines, system clustering, the semi-biased statistic.

A Text Mining and Statistical Approach for Assessment of Pedagogical Impact of Students’ Evaluation of Teaching and Learning Outcome in Education

“…The several studies have shown that a lot of the time, the higher institutions of learning (HEIs) greatly rely on the outcomes of the SET not only for improving or refining the various learning activities and curriculum, but also, are used to define the academic performance of the teachers [48], [53], [55], [58]. In this current study, we note that an important key aspect of the SET should be on its coalition with the educational ecosystem, and how such (educational) dataset can be used to understand the teaching/learning practices, including the identification of steps that can be taken to improve the dynamics of the teaching/learning processes [27], [40]. In this vein, there is a necessity to tenaciously study the concealed benefits of SET in education, and how the underlying information that are derived from such tools can be used to support the decision-making processes, and drive the educational ecosystem forward.…”

“…The authors believe and prove that studying the comments provided by the students when completing the SET instruments can allow educators to identify the students' learning pathways, experiences, and expectations towards an enhanced learning and teaching practices. This can be didactically done by transliterating the extracted sentiments and emotions expressed by the students in the completed SET into meaningful insights in connection to the teachinglearning process, and to discover the prominent factors that influences the way they rate their teachers and learning outcomes [40], [57], [58].…”

“…Consequentially, we note that the aforenoted issues and challenges is an indicator for the development of educational models or methods that supports provision of ''innovative pedagogies'' for teaching and learning, that not only integrates the TEL-based initiatives, but can be instructionally used to bridge the gap between the modern and traditional models of teaching, whilst paying attention to the new mechanisms or practices for achieving the much-needed ''flexibility, scalability and sustainability of education''. Indeed, one of the most pertinent ways through which the said goals can be achieved is through conceptual analysis and leveraging of the insights drawn from the readily available educational datasets that explores the learning patterns and performance of the teachers and students [40], [41], for an improved educational practice as done in this study.…”

Educational Data Mining in European Union – Achievements and Challenges: A Systematic Literature Review

“…Thus emerged the interdisciplinary field of Educational Data Mining (EDM), which focuses on obtaining hidden but potentially valuable information in the context of education and learning through specific data mining methods applied to data collected from these processes. It establishes a connection between two distinct fields: education, on the one hand, and computer science, specifically data mining, on the other [2] combining elements from artificial intelligence, machine learning, statistics, expert systems, databases, and visualization to investigate and optimize educational processes.…”

Methods of Overcoming Data Waste in Education: A Systematic Review

“…Abdelkader et al, 2022;Prabowo et al, 2021;Feng et al, 2022;Nabil et al, 2021;Priyambada et al, 2021;Du et al, 2020a;Ghorbani and Ghousi, 2020;Qu et al, 2022;Zeng et al, 2020;Wen et al, 2020;Li et al, 2020). ‫ان،‬ ‫إير‬ ‫بنجالدش،‬ ‫إيطاليا،‬ ‫إستونيا،‬ ‫و‬ ‫أنه‬ ‫باملالحظة،‬ ‫الجدير‬ ‫من‬ ‫قد‬ ‫أمريكية،‬ ‫كانت‬ ‫النشر‬ ‫أوعية‬ ‫أغلب‬ ‫أن‬ ‫إال‬ ‫األبحاث‬ ‫اء‬ ‫إجر‬ ‫أماكن‬ ‫تنوع‬ ‫رغم‬ ‫إ‬ ‫ذلك‬ ‫يشير‬ ‫بهذا‬ ‫األمريكية‬ ‫العلمية‬ ‫واملجالت‬ ‫البيانات‬ ‫قواعد‬ ‫اهتمام‬ ‫لى‬ ‫البيانات‬ ‫عن‬ ‫التنقيب‬ ‫ملجال‬ ‫النشر‬ ‫خطوط‬ ‫توجه‬ ‫إلى‬ ‫أدى‬ ‫مما‬ ‫املجال،‬ ‫التعليمية‬ Mengash, 2020; Prabowo et al, 2021; Nabil et al, 2021; Wen et al, 2020; Iqbal et al, 2020).…”