BOOK-CHAPTER

Strategies to Reduce Attrition among First Year Computer Science Students

Juris BorzovsLaila NiedriteDarja Solodovnikova

Year: 2016 Advances in higher education and professional development book series Pages: 98-120   Publisher: IGI Global

Abstract

The observed trend to lose from one-third to half of students in the first year of computing studies at the University of Latvia served as the motivation to explore the causes of dropout and to find methods, how to determine potential dropouts in advance. The study investigates students enrolled in the year 2013 using integrated data from surveys, management information system and e-learning environment. Several factors that could affect attrition were studied: admission score, compensative course in high school mathematics, intermediate grades for core courses, prior knowledge in programming. The research revealed that the trend of non-beginning studies might indicate the wrong choice of the study field and possible lack of understanding of what is programming by enrolled students. An action plan is proposed to reduce dropout, which is based on the activities already conducted at the Faculty of Computing and is supplemented by one of the existing programming aptitude tests.

Keywords:
Attrition Dropout (neural networks) Affect (linguistics) Mathematics education Aptitude Field (mathematics) Medical education Computer science Psychology Medicine Mathematics Developmental psychology Machine learning

Metrics

6
Cited By
0.60
FWCI (Field Weighted Citation Impact)
24
Refs
0.57
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Online Learning and Analytics
Physical Sciences →  Computer Science →  Computer Science Applications
Teaching and Learning Programming
Physical Sciences →  Computer Science →  Computer Science Applications
Online and Blended Learning
Social Sciences →  Social Sciences →  Education

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