The influence of in-service computer science teachers’ demographic characteristics on their self-efficacy

In the digital age, computer science (CS) has become a vital component of the education system. Grounded in social cognitive theory, this study examines the demographic characteristics of in-service CS teachers. Although teacher self-efficacy has garnered increasing scholarly attention, the influence of demographic variables on CS teachers’ self-efficacy remains underexplored, particularly in Pakistan. A quantitative research design was adopted for this study. Data were collected from 325 in-service CS teachers through a standardized questionnaire adapted from the Teaching and Learning International Survey (TALIS, 2018), which was distributed electronically using Google Forms. Descriptive statistics, independent-sample t-test, and one-way analysis of variance (ANOVA) were used for data analysis. The findings revealed no significant differences in teacher self-efficacy based on gender, teaching experience, teaching level, and educational qualification. However, significant differences were observed in age, and school location. Younger CS teachers demonstrated higher self-efficacy than older ones, urban CS teachers reported greater confidence than rural ones, and those who viewed their profession as more important exhibited stronger self-efficacy. The results suggest that educational stakeholders should design professional development programs that support older and rural CS teachers, strengthen teachers’ professional identity, and promote equitable access to resources so as to build a confident, motivated, and capable teaching workforce for the digital age.

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Publication Details

Journal
Cogent Education
Published
2026-07-23
DOI
https://doi.org/10.1080/2331186x.2026.2696655
Primary Topic
Gender and Technology in Education
Type
article
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article

The influence of in-service computer science teachers’ demographic characteristics on their self-efficacy

Bin Jing, Nasir Ali, Tanveer Ahmad, Fen Gao
Cogent Education
Gender and Technology in Education
article

The influence of in-service computer science teachers’ demographic characteristics on their self-efficacy

Bin Jing, Nasir Ali, Tanveer Ahmad, Fen Gao
article en

Abstract

In the digital age, computer science (CS) has become a vital component of the education system. Grounded in social cognitive theory, this study examines the demographic characteristics of in-service CS teachers. Although teacher self-efficacy has garnered increasing scholarly attention, the influence of demographic variables on CS teachers’ self-efficacy remains underexplored, particularly in Pakistan. A quantitative research design was adopted for this study. Data were collected from 325 in-service CS teachers through a standardized questionnaire adapted from the Teaching and Learning International Survey (TALIS, 2018), which was distributed electronically using Google Forms. Descriptive statistics, independent-sample t-test, and one-way analysis of variance (ANOVA) were used for data analysis. The findings revealed no significant differences in teacher self-efficacy based on gender, teaching experience, teaching level, and educational qualification. However, significant differences were observed in age, and school location. Younger CS teachers demonstrated higher self-efficacy than older ones, urban CS teachers reported greater confidence than rural ones, and those who viewed their profession as more important exhibited stronger self-efficacy. The results suggest that educational stakeholders should design professional development programs that support older and rural CS teachers, strengthen teachers’ professional identity, and promote equitable access to resources so as to build a confident, motivated, and capable teaching workforce for the digital age.

Cogent EducationVol. 13(1)
Shaanxi Normal University (CN)
Openalex Percentile: Top 5%
Gender and Technology in Education
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