A Study on the Learning Early Warning Prediction Based on Homework Habits: Towards Intelligent Sustainable Evaluation for Higher Education

Wenkan Wen, Yiwen Liu (), Zhirong Zhu and Yuanquan Shi
Additional contact information
Wenkan Wen: School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China
Yiwen Liu: School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China
Zhirong Zhu: School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China
Yuanquan Shi: School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China

Sustainability, 2023, vol. 15, issue 5, 1-15

Abstract: Teachers need a technique to efficiently understand the learning effects of their students. Early warning prediction mechanisms constitute one solution for assisting teachers in changing their teaching strategies by providing a long-term process for assessing each student’s learning status. However, current methods of building models necessitate an excessive amount of data, which is not conducive to the final effect of the model, and it is difficult to collect enough information. In this paper, we use educational data mining techniques to analyze students’ homework data and propose an algorithm to extract the three main features: Degree of reliability, degree of enthusiasm, and degree of procrastination. Building a predictive model based on homework habits can provide an individualized evaluation of students’ sustainability processes and support teachers in adjusting their teaching strategies. This was cross-validated using multiple machine learning algorithms, of which the highest accuracy was 93.34%.

Keywords: sustainable evaluation; educational prediction; early warning; homework habits; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/5/4062/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/5/4062/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:5:p:4062-:d:1077859

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().