Konferenzbeitrag

Predicting Students’ Success Using Neural Networks

Fast technological changes and constant growth of knowledge in many areas have led to an increasing importance of different approach to education. Efficient education is the foundation of modern society and it has the most important role in preparing students for a very flexible labour market. Education is key for development and progress. The goal of this paper is to present a model for predicting students’ success using Neural networks. The model is based on students’ enrolment data that consisted of demographic and economic data and information about previous education. Students’ efficacy is measured by grade point average in college, and students are divided into two groups: with grade point average below and above 3.5. This model can help educators to prepare students who are classified below average with additional classes to overcome the more difficult courses and, thus, reduce the percentage of students leaving the college because of insufficient prior knowledge.

Sprache
Englisch

Erschienen in
In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019 ; Year: 2019 ; Pages: 58-66 ; Zagreb: IRENET - Society for Advancing Innovation and Research in Economy

Klassifikation
Wirtschaft
Neural Networks and Related Topics
Analysis of Education
Thema
neural networks
educational data mining
student success

Ereignis
Geistige Schöpfung
(wer)
Bilal Zorić, Alisa
Ereignis
Veröffentlichung
(wer)
IRENET - Society for Advancing Innovation and Research in Economy
(wo)
Zagreb
(wann)
2019

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Konferenzbeitrag

Beteiligte

  • Bilal Zorić, Alisa
  • IRENET - Society for Advancing Innovation and Research in Economy

Entstanden

  • 2019

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