Performance Impact of Computer Science Course Load and Transfer Status: (Abstract Only).

SIGCSE '18: The 49th ACM Technical Symposium on Computer Science Education Baltimore Maryland USA February, 2018(2018)

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摘要
A recent 2017 study from HigherEd.com, shows that roughly 35% of students transfer colleges during their academic career. While much research has focused on the impact of undergraduate student success factors such as flipped classrooms, hybrid learning, and technology usage, we found no studies comparing transfer students versus non-transfer (native). In our research, we measure impact based on CS course load per semester related to pass/fail rates and contrast student status of transfer versus non-transfer (native). We show that transfer students tend to enroll in more CS courses per semester, beyond the department's recommended two. We also show that their performance is consistently different than that of native students, namely higher CS course fail rates and lower CS GPA scores. The detrimental effects and realization in this study is reason for further investigation. More features will be gathered to be used in our continued analysis and we see the need to examine the difficulty of CS courses taken to indicate why one cohort performs poorly and one does not. We conjecture that most transfer students tend to complete their core classes and are left with only CS courses to complete upon transfer. This results in the transfer students taking a heavier CS load and thus impacting their performance negatively, as compared to native students. Considering that many transfer students start their path way in 2-year institutions, it is imperative that better advising strategies are developed to enable the students to succeed upon their transition.
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关键词
CS Education,Education Data Mining,Transfer versus Native
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