2015 Conference Archive (Archived)
Session Format
Brief Report (15 minutes)
Copyright
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Location
Room 2904B
Abstract for the conference program
This research introduces the notion of predicting academic performance using 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 the student future academic success. To achieve this goal, a two-year study of the correlation between accumulative grade point averages and Computational Thinking course grades was conducted. The performance of 982 students was assessed over the two-year period. It was concluded that the students’ academic performance is strongly correlated to their Computational Thinking skills assessed at the freshman-level. This proves the viability of using Computational Thinking skills as a predictor of students’ academic success which can be used as an early intervention method to improve the students’ retention, progression, and graduation rates in STEM related disciplines.
Proposal Track
Research Project
Start Date
3-6-2015 10:15 AM
End Date
3-6-2015 11:00 AM
Recommended Citation
source:http://digitalcommons.georgiasouthern.edu/stem/2015/2015/18/
Archived Content
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Can Computational Thinking Predict Academic Performance?
Room 2904B
This research introduces the notion of predicting academic performance using 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 the student future academic success. To achieve this goal, a two-year study of the correlation between accumulative grade point averages and Computational Thinking course grades was conducted. The performance of 982 students was assessed over the two-year period. It was concluded that the students’ academic performance is strongly correlated to their Computational Thinking skills assessed at the freshman-level. This proves the viability of using Computational Thinking skills as a predictor of students’ academic success which can be used as an early intervention method to improve the students’ retention, progression, and graduation rates in STEM related disciplines.
