Mixed Method Study of Experiences of Non-Computer Science Majors in Introductory Computer Science Courses

With the unprecedented growth of the Computer Science field, there is an underlying assumption that undergraduate students would naturally gravitate towards Computer Science courses or acquire related skills, irrespective of their career interests. However, this research challenged that assumption, focusing on the experiences and attitudes of Non-Computer Science majors enrolled in Computer Science courses. The objective of this study is to gain a comprehensive understanding of the experiences and attitudes of Non-Computer Science majors taking Computer Science courses. The research questions seek to uncover the factors influencing their engagement in Computer Science. This research employs a mixed-method study, starting with a quantitative phase followed by a qualitative one. Quantitative data is analyzed using factor analysis and inferential statistics, followed by thematic analysis on the qualitative data. The findings reveal that stereotypes associated with the Computer Science field are established as early as high school. These stereotypes, particularly affecting females, sometimes act as barriers, discouraging further pursuit of Computer Science. Addressing these stereotypes becomes crucial for fostering inclusivity in the field. To counteract these stereotypes, it is proposed that Computer Science and its applications should be promoted as early as freshmen year of high school. By introducing students to the field early, we can potentially mitigate the impact of stereotypes and encourage a diverse range of individuals to pursue Computer Science. Further exploration into the experiences of Computer Science majors is recommended to deepen our understanding and inform targeted interventions.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science and Applications

Department dc:contributor.department

Computer Science and Applications

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2024

Author dc:creator

• Parajuli, Khushi

Chair dc:contributor.committeechair

• Hooshangi, Sara

Committee members dc:contributor.committeemember

• Seyam, Mohammed Saad Mohamed Elmahdy
• Weiss, Brandi A.

• Mixed-Methods Study
• Factor Analysis
• Qualitative Analysis
• Thematic Analysis
• Stereotypes
• Inclusion

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:39206

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/117304