Early prediction of student performance in CS1 programming courses

Article Properties
  • Language
    English
  • DOI (url)
    10.7717/peerj-cs.1655
  • Publication Date
    2023/10/31
  • Journal
    PeerJ Computer Science
  • Indian UGC (journal)
  • Refrences
    55
  • Jose Llanos School of Systems Engineering and Computing, Universidad del Valle Colombia, Cali, Valle del Cauca, Colombia
  • Víctor A. Bucheli School of Systems Engineering and Computing, Universidad del Valle Colombia, Cali, Valle del Cauca, Colombia
  • Felipe Restrepo-Calle Department of Systems and Industrial Engineering, Universidad Nacional de Colombia, Bogotá, D.C., Colombia
Abstract
Cite
Llanos, Jose, et al. “Early Prediction of Student Performance in CS1 Programming Courses”. PeerJ Computer Science, vol. 9, 2023, p. e1655, https://doi.org/10.7717/peerj-cs.1655.
Llanos, J., Bucheli, V. A., & Restrepo-Calle, F. (2023). Early prediction of student performance in CS1 programming courses. PeerJ Computer Science, 9, e1655. https://doi.org/10.7717/peerj-cs.1655
Llanos J, Bucheli VA, Restrepo-Calle F. Early prediction of student performance in CS1 programming courses. PeerJ Computer Science. 2023;9:e1655.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Computer software
Science
Science (General)
Cybernetics
Information theory
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Computer engineering
Computer hardware
Refrences
Title Journal Journal Categories Citations Publication Date
Using learning analytics in the Amazonas: understanding students’ behaviour in introductory programming

 British Journal of Educational Technology
  • Education: Theory and practice of education
  • Education
  • Social Sciences
 31 2020
Construction of a model for predicting students’ performance in a programming exercise lecture 2020
Analyzing Student Performance in Programming Education Using Classification Techniques

 International Journal of Emerging Technologies in Learning (iJET)
  • Education: Theory and practice of education
 16 2020
Data-driven tool for monitoring of students performance IFAC-PapersOnLine 2 2019
CS1: how will they do? How can we help? A decade of research and practice Computer Science Education
  • Education: Theory and practice of education
 11 2019