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Entropy and the Second Law of Thermodynamics

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Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

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Students' Learning Behaviour in Programming Education Analysis: Insights from Entropy and Community Detection.

Tai Tan Mai^1,2, Martin Crane^1,2, Marija Bezbradica^1,2

¹School of Computing, Dublin City University, Collins Ave Ext, Whitehall, D09 Y074 Dublin, Ireland.

Entropy (Basel, Switzerland)

|August 26, 2023

Summary

Entropy metrics reveal distinct learning behaviors in programming students. Higher-performing students exhibit lower learning volatility and achieve stable engagement faster, aiding educators in early intervention strategies.

Keywords:

community detection educational data mining entropy learning analytics learning behaviours random matrix theory

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Published on: June 10, 2021

Area of Science:

Educational Technology
Computer Science Education
Learning Analytics

Background:

High dropout rates in programming courses necessitate better student engagement monitoring.
Learning Management System (LMS) data offers insights into student behaviors and performance.
High dimensionality of LMS data presents analysis and interpretability challenges.

Purpose of the Study:

To introduce entropy-based metrics for representing student learning behaviors.
To analyze learning behaviors in higher- and lower-performing student communities.
To examine the impact of the COVID-19 pandemic on student learning behaviors.

Main Methods:

Utilized entropy-based metrics to quantify student learning behaviors.
Applied a community detection method to analyze student groups.
Analyzed empirical data from 391 Software Engineering students across three academic years.

Main Results:

Higher-performing student communities demonstrated lower entropy volatility.
Students in top-performing groups reached stable learning states earlier.
The study identified shifts in learning behaviors potentially linked to the COVID-19 pandemic.

Conclusions:

Entropy serves as a valuable, interpretable metric for educators to monitor student progress.
Entropy metrics can enhance understanding of student engagement and facilitate timely interventions.
This approach offers a novel way to analyze complex learning behaviors in educational settings.