Treffer: Engaging Girls in Computer Science: Gender Differences in Attitudes and Beliefs about Learning Scratch and Python

Title:
Engaging Girls in Computer Science: Gender Differences in Attitudes and Beliefs about Learning Scratch and Python
Language:
English
Authors:
Zdawczyk, Christina (ORCID 0000-0002-9651-0229), Varma, Keisha (ORCID 0000-0001-7915-793X)
Source:
Computer Science Education. 2023 33(4):600-620.
Availability:
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed:
Y
Page Count:
21
Publication Date:
2023
Sponsoring Agency:
National Science Foundation (NSF)
Contract Number:
00039202
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Research
Education Level:
Junior High Schools
Middle Schools
Secondary Education
Elementary Education
DOI:
10.1080/08993408.2022.2095593
ISSN:
0899-3408
1744-5175
Entry Date:
2023
Accession Number:
EJ1404342
Database:
ERIC

Weitere Informationen

Background and Context: A continued gender disparity has driven a need for effective interventions for recruiting girls to computer science. Prior research has demonstrated that middle school girls hold beliefs and attitudes that keep them from learning computer science, which can be mitigated through classroom design. Objective: This study investigated whether programming environment design has a similar effect, to assess the potential utility of block-based programming (Scratch) for recruiting girls to computer science compared to traditional text-based programming (Python). Method: One hundred and eighty-seven upper elementary and middle school students were surveyed to understand stereotype concern, sense of belonging, interest, and self-efficacy at baseline and after being shown each programming environment. Findings: Results indicated that stereotype concern was high for girls across all three conditions. Significantly more girls than boys showed interest in learning computer science in Scratch compared to Python. Belonging, interest, and self-efficacy were inter-correlated for both genders. Implications: Although girls demonstrated low self-efficacy across all conditions, more girls showed interest in learning to program through Scratch. Additionally, both girls and boys demonstrated higher self-efficacy in Scratch than in Python. This suggests that using block-based programming languages may be effective for recruiting girls to study computer science.

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