• DocumentCode
    711612
  • Title

    Can computational thinking predict academic performance?

  • Author

    Haddad, Rami J. ; Kalaani, Youakim

  • Author_Institution
    Georgia Southern Univ., Statesboro, GA, USA
  • fYear
    2015
  • fDate
    7-7 March 2015
  • Firstpage
    225
  • Lastpage
    229
  • Abstract
    This paper introduces the notion of predicting academic performance based on Computational Thinking. The integral role that Computational Thinking modalities play in engineering disciplines can serve as an accurate indicator of the student future academic success. Therefore, this study investigated the students´ performance in a Computational Thinking course offered at the freshman level to predict student academic success. To achieve this goal, a two-year study of the correlation between the students´ accumulative grade point averages and their grades obtained in this course was conducted. The performance of nine hundred and eighty two students in forty sections was assessed over the two-year period. It was concluded that the students´ future academic performance is strongly correlated to their Computational Thinking skills assessed at the freshman level. This clearly suggests the viability of using Computational Thinking skills as a fairly accurate predictor of students´ academic success. These results have also implied that the assessment of Computational Thinking can be used as an early intervention tool to improve the students´ retention, progression, and graduation rates in STEM related disciplines.
  • Keywords
    computer science education; educational courses; academic performance prediction; computational thinking course; student academic success; Computational modeling; Computers; Conferences; Correlation; Education; Electrical engineering; Programming; Academic performance; Computational Thinking; Prediction of performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Integrated STEM Education Conference (ISEC), 2015 IEEE
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    978-1-4799-1828-7
  • Type

    conf

  • DOI
    10.1109/ISECon.2015.7119929
  • Filename
    7119929