Prediction of Academic Grades in Higher Education Using Deconvolutional Density Networks-Reference-Cited by-同舟云学术

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Prediction of Academic Grades in Higher Education Using Deconvolutional Density Networks

Published:2024-07-05 Issue: Volume:41 Page:71-75
ISSN:
Container-title:ACM Turing Award Celebration Conference 2024
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Author:

Zhang Na¹^ORCID,Zhu Shenghui²^ORCID,Li Shuren³^ORCID,Wang Lin⁴^ORCID,Yang Bo⁴^ORCID,Cheng Yuhu⁵^ORCID

Affiliation:

1. China University of Mining and Technology, China and Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China

2. Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China

3. Office of Information Management, University of Jinan, China

4. Quan Cheng Laboratory, China and Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China

5. China University of Mining and Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3674399.3674429

Reference27 articles.

1. Higher education contributing to local, national, and global development: new empirical and conceptual insights

2. Undergraduate Grade Prediction in Chinese Higher Education Using Convolutional Neural Networks

3. Predicting student performance using sequence classification with time-based windows

4. Grades and Graduation: A Longitudinal Risk Perspective to Identify Student Dropouts

5. The relationship of self-esteem to grades, achievement scores, and other factors critical to school success;Wiggins D;The School Counselor,1994

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