Vol. 5 No. 1 (2025): Issue 5
Articles

Identifications of Active Explorers and Passive Learners Among Students: Gaussian Mixture Model-Based Approach

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  • Zhiqiang Zhao,
  • Ping Ren
Zhiqiang Zhao
Beijing PhD Village Education Technology Co., Ltd; Beijing 100871, China
Ping Ren
Chengdu Ding Yi Education Consulting Co., Ltd, Chengdu 610023, China

Published 2025-05-02

Keywords

  • Active Explorers,
  • Passive Learners,
  • Learning Outcomes,
  • Instructional Strategies,
  • Student Engagement

How to Cite

Zhao, Z., & Ren, P. (2025). Identifications of Active Explorers and Passive Learners Among Students: Gaussian Mixture Model-Based Approach. Bulletin of Education and Psychology, 5(1). Retrieved from https://ojs.mri-pub.com/index.php/BEP/article/view/115

Abstract

In the realm of education research, the distinction between active explorers and passive learners among students plays a pivotal role in understanding and enhancing learning outcomes. By identifying and characterizing these two distinct groups, educators can tailor instructional strategies to better cater to individual learning preferences, ultimately fostering a more engaging and effective educational experience. However, existing methodologies for discerning between active explorers and passive learners face significant challenges, primarily stemming from the complexity and variability of student behaviors. In light of this, this paper proposes a novel Gaussian Mixture Model-based approach to accurately classify students into these two categories. The innovative aspect of this work lies in its ability to effectively capture the nuances of student engagement and learning styles, thereby providing a more nuanced understanding of student dynamics in educational settings.

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