首页    期刊浏览 2024年09月21日 星期六
登录注册

文章基本信息

  • 标题:Cognitive Factors in Students' Academic Performance Evaluation using Artificial Neural Networks
  • 本地全文:下载
  • 作者:Etebong Isong ; Udonyah Kingsley ; Godwin Ansa
  • 期刊名称:Information and Knowledge Management
  • 印刷版ISSN:2224-5758
  • 电子版ISSN:2224-896X
  • 出版年度:2018
  • 卷号:8
  • 期号:5
  • 页码:57-71
  • 语种:English
  • 出版社:International Institute for Science, Technology Education
  • 摘要:Performance evaluation based on some cognitive factors especially Students’ Intelligent Quotient rating (IQR), Confidence Level (CoL) and Time Management ability gives an equal platform for better evaluation of students’ performance using Artificial Neural Network. Artificial Neural Networks (ANN) models, which has the advantage of being trained, offers a more robust methodology and tool for predicting, forecasting and modeling phenomena to ascertain conformance to desired standards as well as assist in decision making. This work employs Machine Learning and cognitive science which uses Artificial Neural networks (ANNs) to evaluated students’ academic performance in the Department of Computer Science, Akwa Ibom State University. It presents a survey of the design, building and functionalities of Artificial Neural Network for the evaluation of students’ academic performance using cognitive factors that could affect student’s performances.
  • 关键词:Cognitive; Intelligent Quotient Rating; Machine Learning; Artificial Neural Network.
国家哲学社会科学文献中心版权所有