A Systematic Review on Student Failure Prediction

被引：2

作者：

Veloso, Bruno ^{[1
]}

Barbosa, Maria Araujo ^{[1
]}

Faria, Hugo ^{[1
]}

Marcondes, Francisco S. ^{[1
]}

Duraes, Dalila ^{[1
]}

Novais, Paulo ^{[1
]}

机构：

[1] Univ Minho, ALGORITMI Ctr, Braga, Portugal

来源：

METHODOLOGIES AND INTELLIGENT SYSTEMS FOR TECHNOLOGY ENHANCED LEARNING | 2023年 / 538卷

关键词：

Systematic review; Scholar failure; Predict; Machine learning; Artificial Intelligence; Deep Learning; LEAVING SCHOOL; ADOLESCENTS; SUPPORT;

D O I：

10.1007/978-3-031-20257-5_5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Today, students tend to drop out of school more easily. It is necessary to find out what causes students to have such school failure in order to try to help them succeed in their school life. For this purpose, it is necessary to acquire data about students, and the area of Educational Data Mining (EDM) appears. EDM aims to develop methods for exploring data recovered from educational environments, thus allowing us to try to understand and predict student success [1]. Early prediction of school failure may be cornerstone on the effort of avoiding it. This paper presents a systematic review of school failure prediction systems in students up to high school. The goal is identify the main methods developed and tested, as well as the algorithms used in this task. For that intent, six papers were identified in the SCOPUS repository as relevant for include in the review.

引用

页码：43 / 52

页数：10

共 19 条

[1] Not all school dropouts are the same: Ethnic differences in the relation between reason for leaving school and adolescent substance use [J].

Aloise-Young, PA ;

Chavez, EL .

PSYCHOLOGY IN THE SCHOOLS, 2002, 39 (05) :539-547

[2]

[Anonymous], UNIVERSAL DECLARATIO

[3]

2022, International Journal of Intelligent Engineering and Systems, V15, P316, DOI 10.22266/ijies2022.0430.29

[4] Characterizing attentive behavior in intelligent environments [J].

Duraes, Dalila ;

Carneiro, Davide ;

Jimenez, Amparo ;

Novais, Paulo .

NEUROCOMPUTING, 2018, 272 :46-54

[5] Towards an Adaptive Education through a Machine Learning Recommendation System [J].

Embarak, Ossama .

3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION (IEEE ICAIIC 2021), 2021, :187-192

[6] Long-Term Outcomes of Attention-Deficit/Hyperactivity Disorder and Conduct Disorder: A Systematic Review and Meta-Analysis [J].

Erskine, Holly E. ;

Norman, Rosana E. ;

Ferrari, Alize J. ;

Chan, Gary C. K. ;

Copeland, William E. ;

Whiteford, Harvey A. ;

Scott, James G. .

JOURNAL OF THE AMERICAN ACADEMY OF CHILD AND ADOLESCENT PSYCHIATRY, 2016, 55 (10) :841-850

[7] Associations between participation in family activities and adolescent school problems [J].

Goldfarb, S. S. ;

Locher, J. L. ;

Preskitt, J. ;

Becker, D. ;

Davies, S. L. ;

Sen, B. .

CHILD CARE HEALTH AND DEVELOPMENT, 2017, 43 (03) :361-368

[8]

Hajar M, 2021, Indian Journal of Computer Science and Engineering, V12, P1771, DOI [10.21817/indjcse/2021/v12i6/211206015, 10.21817/indjcse/2021/v12i6/211206015, DOI 10.21817/INDJCSE/2021/V12I6/211206015]

[9] Drug use in adolescents in relation to social support and reactive and proactive aggressive behavior [J].

Jesus Gazquez, Jose ;

del Carmen Perez-Fuentes, Ma ;

del Mar Molero, Ma ;

Barragan Martin, Ana B. ;

Martos Martinez, Africa ;

Sanchez-Marchan, Cristina .

PSICOTHEMA, 2016, 28 (03) :318-322

[10]

Jiayan Wang, 2021, 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE), P93, DOI 10.1109/ICBAIE52039.2021.9389887

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