Predicting computer science students' online help-seeking tendencies

Qiang HAO, Bradley BARNES, Robert Maribe BRANCH, Ewan Thomas Mansell WRIGHT

Research output: Contribution to journalArticles

5 Citations (Scopus)

Abstract

This study investigated how computer science students seek help online in their learning and what factors predict their online help-seeking behaviors. Online help-seeking behaviors include online searching, asking teachers online for help, and asking peers online for help. 207 students from a large university in the southeastern United States participated in the study. It was revealed that computer science students tended to search online more frequently than ask people online for help. Five factors, including epistemological belief, interest, learning proficiency level, prior knowledge of the learning subject, and problem difficulty, were explored as potential predictors in this study. It was found that learning proficiency level and problem difficulty were significant predictors of three types of online help-seeking behaviors, and other factors influenced online help seeking to different extents. The study provides evidence to support that online searching should be considered as an integrated part of online help seeking, and gives guidelines for practice of facilitating online help seeking and future studies. Copyright © 2017 Laboratory for Knowledge Management & E-Learning, The University of Hong Kong.
Original languageEnglish
Pages (from-to)19-32
JournalKnowledge Management and E-Learning
Volume9
Issue number1
Publication statusPublished - Mar 2017

Citation

Hao, Q., Barnes, B., Branch, R. M., & Wright, E. (2017). Predicting computer science students' online help-seeking tendencies. Knowledge Management & E-Learning, 9(1), 19-32. Retrieved from http://www.kmel-journal.org/ojs/index.php/online-publication/article/view/361

Keywords

  • Online help seeking
  • Online searching
  • Epistemological belief
  • Learning proficiency level

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