Research Article
BibTex RIS Cite

Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye

Year 2026, Volume: 21 Issue: 1 , 235 - 251 , 30.03.2026
https://doi.org/10.55525/tjst.1812503
https://izlik.org/JA98PP78FP

Abstract

Despite global efforts to improve gender equity in STEM, gender disparities persist in Computer Science (CS) education, particularly in Türkiye, where cultural and institutional factors shape academic pathways. This embedded mixed-methods study investigates how high school experiences, mentorship, role models, extracurricular activities, and social influences relate to first-year university students' intentions to continue their studies in CS, with a specific focus on gender-based differences. Survey data from 369 students across Türkiye reveal no statistically significant association between continuation intention and variables such as prior programming experience, mentorship, or extracurricular engagement. Qualitative findings underscore the importance of familial and cultural expectations, with both encouragement and discouragement from family playing a central role. Students frequently cited family members as both their strongest supporters and primary sources of pressure to pursue more socially prestigious fields like medicine. These findings highlight the limited impact of formal support and the strong influence of social norms in shaping CS persistence. The study contributes to the literature by centering student voices across gender identities and offering culturally contextualized insights into educational equity in Türkiye. Implications include the need for inclusive pedagogies, early CS exposure, and targeted outreach to families to broaden participation in computing education.

References

  • Abbate, J. (2012). Recoding gender: Women's changing participation in computing. MIT Press.
  • Akram, B., Fisk, S., Yoder, S., Hunt, C., Price, T., Battestilli, L., & Barnes, T. (2022, July). Increasing students' persistence in computer science through a lightweight scalable intervention. In Proceedings of the 27th ACM Conference on Innovation and Technology in Computer Science Education Vol. 1 (pp. 526–532). https://doi.org/10.1145/3502718.3524815
  • Altin, R., & Mühling, A. (2024). Why female students are dropping out of cs programs. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1 (pp. 304-310).
  • Aycan, Z., & Fikret-Pasa, S. (2003). Career choices, job selection criteria, and leadership preferences in a transitional nation: The case of Turkey. Journal of Career Development, 30(2), 129–144. https://doi.org/10.1177/089484530303000203
  • Dönmez, İ. (2023). Breaking gender stereotypes: How interacting with STEM professionals changed female students' perceptions. Journal of Baltic Science Education, 22(6), 974-990. https://doi.org/10.33225/jbse/23.22.974
  • Billings, J. (2024). Beyond the Binary: Multimodal Oral Histories of Navigating Gender and Finding Identity from Gender-Diverse and Cisgender Students. : Oregon State University.https://ir.library.oregonstate.edu/concern/honors_college_theses/x059ch40n?locale=en#:~:text=https%3A//ir.library.oregonstate.edu/concern/honors_college_theses/x059ch40n
  • Bragg, S., Renold, E., Ringrose, J., & Jackson, C. (2018). ‘More than boy, girl, male, female’: exploring young people’s views on gender diversity within and beyond school contexts. Sex Education, 18(4), 420–434. https://doi.org/10.1080/14681811.2018.1439373
  • Chavatzia, T. (2017). Cracking the code: Girls’ and women’s education in science, technology, engineering and mathematics (STEM). Paris, France: United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000260079.locale=en
  • Cheryan, S., Master, A., & Meltzoff, A. N. (2015). Cultural stereotypes as gatekeepers: Increasing girls’ interest in computer science and engineering by diversifying stereotypes. Frontiers in Psychology, 6, 49. https://doi.org/10.3389/fpsyg.2015.00049
  • Cheryan, S., Ziegler, S. A., Montoya, A. K., & Jiang, L. (2017). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143(1), 1–35. http://dx.doi.org/10.1037/bul0000052
  • Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
  • Çatı, K., İştar, E., & Özcan, H. (2016). Investigating the factors that influence the university preference: A countrywide field research in Turkey. Yükseköğretim ve Bilim Dergisi [Journal of Higher Education and Science], 6(2), 163–177. https://dergipark.org.tr/tr/pub/higheredusci/issue/61490/918093
  • Dasgupta, N., & Stout, J. G. (2014). Girls and women in science, technology, engineering, and mathematics: STEMing the tide and broadening participation in STEM careers. Policy Insights from the Behavioral and Brain Sciences, 1(1), 21-29.
  • Eckstein, D., Belongia, M., & Elliott-Applegate, G. (2000). The four directions of encouragement within families. The Family Journal, 8(4), 406–415. https://doi.org/10.1177/1066480700084015
  • Eraslan Yalçın, M., & Gülseçen, S. (2023). Undergraduate dropout intentions in Turkey: A systematic review of factors and implications. Eğitim ve Toplum Araştırmaları Dergisi [Journal of Education and Society Research], 10(2), 237–252. https://doi.org/10.51725/etad.1347987
  • Erümit, S. F., & Keles, E. (2023). Examining computer science education of Asia-Pacific countries successful in the PISA. Journal of Educational Technology and Online Learning, 6(1), 82–104. https://doi.org/10.31681/jetol.1154913
  • Falkner, K., Szabo, C., Michell, D., Szorenyi, A., & Thyer, S. (2015). Gender gap in academia: Perceptions of female computer science academics. In Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '15) (pp. 111–116). Association for Computing Machinery. https://doi.org/10.1145/2729094.2742595
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). SAGE Publications.
  • Goode, J. (2008). Increasing diversity in K–12 computer science: Strategies from the field. In Proceedings of the 39th SIGCSE Technical Symposium on Computer Science Education (SIGCSE '08) (pp. 362–366). Association for Computing Machinery. https://doi.org/10.1145/1352135.1352259
  • Graneheim, U. H., & Lundman, B. (2004). Qualitative content analysis in nursing research: Concepts, procedures and measures to achieve trustworthiness. Nurse Education Today, 24(2), 105–112. https://doi.org/10.1016/j.nedt.2003.10.001
  • Holanda, M., Mourão, R. N., von Borries, G., Ramos, G. N., Araujo, A., & Walter, M. E. (2020). What do female students in middle and high schools think about computer science majors in Brasilia, Brazil? A survey in 2011 and 2019. In 2020 IEEE Frontiers in Education Conference (FIE) (pp. 1–7). IEEE. https://doi.org/10.1109/FIE44824.2020.9274257
  • Hooshangi, S., Ellis, M., & Edwards, S. H. (2022). Factors influencing student performance and persistence in CS2. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education – Volume 1 (SIGCSE 2022) (pp. 286–292). Association for Computing Machinery. https://doi.org/10.1145/3478431.3499272
  • Howell, D. C. (2006). Statistical methods for psychology (6th ed.). Thomson Wadsworth.
  • İçen, M. (2022). The future of education utilizing artificial intelligence in Turkey. Humanities and Social Sciences Communications, 9(1), 1–10. https://doi.org/10.1057/s41599-022-01284-4
  • Jaccheri, L., Cutrupi, C. M., Diaconu, M. G., Szlavi, A., Takaoka, A. J. W., & Lenarduzzi, V. (2022). Where are the female professors in STEM? Preprint on TechRxiv. https://doi.org/10.36227/techrxiv.21760532.v1
  • Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33(7), 14–26. https://doi.org/10.3102/0013189X033007014
  • Kahveci, A., Sahin, N., & Genc, S. (2011). Computer perceptions of secondary school teachers and impacting demographics: A Turkish perspective. Turkish Online Journal of Educational Technology-TOJET, 10(1), 71–80. https://eric.ed.gov/?id=EJ926555
  • Katz, S., Allbritton, D., Aronis, J., Wilson, C., & Soffa, M. L. (2006). Gender, achievement, and persistence in an undergraduate computer science program. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 37(4), 42–57. https://doi.org/10.1145/1185335.1185344
  • Keane, T., Molnar, A., & Stockdale, R. (2021). Identifying Australian high school intervention programs that influence 1st year female students to choose ICT degrees. Proceedings of the 2021 ACM Conference on Innovation and Technology in Computer Science Education. https://doi.org/10.1145/3456565.3460004
  • Kelly, R., & Allen, M. (2023). Exploring engagement and self-efficacy in an introductory computer science course. In Proceedings of the 2023 ACM SIGPLAN International Symposium on SPLASH-E (SPLASH-E 2023) (pp. 60–68). Association for Computing Machinery. https://doi.org/10.1145/3622780.3623649
  • Kert, S., Kalelioglu, F., & Gulbahar, Y. (2019). A holistic approach for computer science education in secondary schools. Informatics in Education, 18(1), 105–121. https://doi.org/10.15388/infedu.2019.06
  • Mamat, N. J. Z., & Mazelan, F. F. (2011). Learning encouragement factors and academic performance. Procedia-Social and Behavioral Sciences, 18, 307–315. https://doi.org/10.1016/j.sbspro.2011.05.044
  • Margolis, J., & Fisher, A. (2002). Unlocking the clubhouse: Women in computing. MIT Press.
  • Master, A., Meltzoff, A. N., & Cheryan, S. (2021). Gender stereotypes about interests start early and cause gender disparities in computer science and engineering. Proceedings of the National Academy of Sciences, 118(48), e2100030118. https://doi.org/10.1073/pnas.2100030118
  • Master, A., Tang, D., Forsythe, D., Alexander, T. M., Cheryan, S., & Meltzoff, A. N. (2023). Gender equity and motivational readiness for computational thinking in early childhood. Early Childhood Research Quarterly, 64, 242–254. https://doi.org/10.1016/j.ecresq.2023.03.004
  • NCWIT. (2023). Women in tech by the numbers. National Center for Women & Information Technology. https://ncwit.org/resource/bythenumbers
  • Rosson, M. B., Carroll, J. M., & Sinha, H. (2011). Orientation of undergraduates toward careers in the computer and information sciences: Gender, self-efficacy, and social support. ACM Transactions on Computing Education, 11(3), Article 14, 1–23. https://doi.org/10.1145/2037276.2037278
  • Schmader, T. (2023). Gender inclusion and fit in STEM. Annual Review of Psychology, 74(1), 219–243. https://doi.org/10.1146/annurev-psych-032420-031902
  • Spieler, B., & Girvan, C. (2025). The PECC framework: Promoting gender sensitivity and gender equality in computer science education. Computers, 14(7), 249. https://doi.org/10.3390/computers14070249
  • Şahin, A., & Waxman, H. C. (2021). Factors affecting high school students’ STEM career interest: Findings from a 4-year study. Journal of STEM Education: Innovations and Research, 22(3).
  • Şimşek, H. (2013). University students’ tendencies toward and reasons behind dropout. Journal of Theoretical Educational Science, 6(2), 242–271. https://dergipark.org.tr/en/pub/akukeg/issue/29349/314064
  • Tari, M., Hua, V., Ng, L., & Annabi, H. (2021). How Asian women’s intersecting identities impact experiences in introductory computing courses. In Diversity, divergence, dialogue: 16th International Conference, iConference 2021, Beijing, China, March 17–31, 2021, Proceedings, Part I (pp. 603–617). Springer-Verlag. https://doi.org/10.1007/978-3-030-71292-1_47

Türkiye’de Öğrencilerin Bilgisayar Bilimleri Alanında Eğitimlerine Devam Etme Niyetini Etkileyen Faktörler: Cinsiyete Bağlı Farklılıklar

Year 2026, Volume: 21 Issue: 1 , 235 - 251 , 30.03.2026
https://doi.org/10.55525/tjst.1812503
https://izlik.org/JA98PP78FP

Abstract

Küresel ölçekte STEM alanlarında toplumsal cinsiyet eşitliğini artırmaya yönelik çabalara rağmen, özellikle Türkiye’de kültürel ve kurumsal dinamiklerin akademik yönelimleri şekillendirdiği Bilgisayar Bilimleri (BB) eğitiminde toplumsal cinsiyet temelli eşitsizlikler devam etmektedir. Bu gömülü karma yöntemli çalışma, lise dönemi deneyimleri, mentorluk, rol modeller, ders dışı etkinlikler ve sosyal etkilerin, üniversite birinci sınıf öğrencilerinin BB alanında eğitimlerine devam etme niyetleriyle olan ilişkisini incelemekte ve bu bağlamda toplumsal cinsiyet farklılıklarına özel bir vurgu yapmaktadır. Türkiye genelinde 369 öğrenciden toplanan anket verileri, devam etme niyeti ile önceki programlama deneyimi, mentorluk veya ders dışı etkinliklere katılım gibi değişkenler arasında istatistiksel olarak anlamlı bir ilişki bulunmadığını göstermektedir. Nitel bulgular ise ailevi ve kültürel beklentilerin belirleyici rolünü vurgulamaktadır. Katılımcılar, aile üyelerini hem en güçlü destek kaynakları hem de tıp gibi toplumsal olarak daha prestijli görülen alanlara yönlendiren baskı unsurları olarak tanımlamıştır. Bulgular, biçimsel destek mekanizmalarının sınırlı etkisini ve toplumsal normların BB alanında devamlılık üzerinde güçlü bir etkisi olduğunu ortaya koymaktadır. Çalışma, öğrencilerin toplumsal cinsiyet kimlikleri bağlamında deneyimlerini merkeze alarak, Türkiye’deki eğitim eşitliğine ilişkin kültürel olarak bağlamsallaştırılmış bir bakış açısı sunmaktadır. Bulgular, kapsayıcı pedagojilerin geliştirilmesi, erken dönemde BB ile tanışma fırsatlarının artırılması ve ailelere yönelik hedefli farkındalık çalışmalarının, bilişim alanında katılımın genişletilmesi açısından önemini ortaya koymaktadır.

References

  • Abbate, J. (2012). Recoding gender: Women's changing participation in computing. MIT Press.
  • Akram, B., Fisk, S., Yoder, S., Hunt, C., Price, T., Battestilli, L., & Barnes, T. (2022, July). Increasing students' persistence in computer science through a lightweight scalable intervention. In Proceedings of the 27th ACM Conference on Innovation and Technology in Computer Science Education Vol. 1 (pp. 526–532). https://doi.org/10.1145/3502718.3524815
  • Altin, R., & Mühling, A. (2024). Why female students are dropping out of cs programs. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1 (pp. 304-310).
  • Aycan, Z., & Fikret-Pasa, S. (2003). Career choices, job selection criteria, and leadership preferences in a transitional nation: The case of Turkey. Journal of Career Development, 30(2), 129–144. https://doi.org/10.1177/089484530303000203
  • Dönmez, İ. (2023). Breaking gender stereotypes: How interacting with STEM professionals changed female students' perceptions. Journal of Baltic Science Education, 22(6), 974-990. https://doi.org/10.33225/jbse/23.22.974
  • Billings, J. (2024). Beyond the Binary: Multimodal Oral Histories of Navigating Gender and Finding Identity from Gender-Diverse and Cisgender Students. : Oregon State University.https://ir.library.oregonstate.edu/concern/honors_college_theses/x059ch40n?locale=en#:~:text=https%3A//ir.library.oregonstate.edu/concern/honors_college_theses/x059ch40n
  • Bragg, S., Renold, E., Ringrose, J., & Jackson, C. (2018). ‘More than boy, girl, male, female’: exploring young people’s views on gender diversity within and beyond school contexts. Sex Education, 18(4), 420–434. https://doi.org/10.1080/14681811.2018.1439373
  • Chavatzia, T. (2017). Cracking the code: Girls’ and women’s education in science, technology, engineering and mathematics (STEM). Paris, France: United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000260079.locale=en
  • Cheryan, S., Master, A., & Meltzoff, A. N. (2015). Cultural stereotypes as gatekeepers: Increasing girls’ interest in computer science and engineering by diversifying stereotypes. Frontiers in Psychology, 6, 49. https://doi.org/10.3389/fpsyg.2015.00049
  • Cheryan, S., Ziegler, S. A., Montoya, A. K., & Jiang, L. (2017). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143(1), 1–35. http://dx.doi.org/10.1037/bul0000052
  • Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
  • Çatı, K., İştar, E., & Özcan, H. (2016). Investigating the factors that influence the university preference: A countrywide field research in Turkey. Yükseköğretim ve Bilim Dergisi [Journal of Higher Education and Science], 6(2), 163–177. https://dergipark.org.tr/tr/pub/higheredusci/issue/61490/918093
  • Dasgupta, N., & Stout, J. G. (2014). Girls and women in science, technology, engineering, and mathematics: STEMing the tide and broadening participation in STEM careers. Policy Insights from the Behavioral and Brain Sciences, 1(1), 21-29.
  • Eckstein, D., Belongia, M., & Elliott-Applegate, G. (2000). The four directions of encouragement within families. The Family Journal, 8(4), 406–415. https://doi.org/10.1177/1066480700084015
  • Eraslan Yalçın, M., & Gülseçen, S. (2023). Undergraduate dropout intentions in Turkey: A systematic review of factors and implications. Eğitim ve Toplum Araştırmaları Dergisi [Journal of Education and Society Research], 10(2), 237–252. https://doi.org/10.51725/etad.1347987
  • Erümit, S. F., & Keles, E. (2023). Examining computer science education of Asia-Pacific countries successful in the PISA. Journal of Educational Technology and Online Learning, 6(1), 82–104. https://doi.org/10.31681/jetol.1154913
  • Falkner, K., Szabo, C., Michell, D., Szorenyi, A., & Thyer, S. (2015). Gender gap in academia: Perceptions of female computer science academics. In Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '15) (pp. 111–116). Association for Computing Machinery. https://doi.org/10.1145/2729094.2742595
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). SAGE Publications.
  • Goode, J. (2008). Increasing diversity in K–12 computer science: Strategies from the field. In Proceedings of the 39th SIGCSE Technical Symposium on Computer Science Education (SIGCSE '08) (pp. 362–366). Association for Computing Machinery. https://doi.org/10.1145/1352135.1352259
  • Graneheim, U. H., & Lundman, B. (2004). Qualitative content analysis in nursing research: Concepts, procedures and measures to achieve trustworthiness. Nurse Education Today, 24(2), 105–112. https://doi.org/10.1016/j.nedt.2003.10.001
  • Holanda, M., Mourão, R. N., von Borries, G., Ramos, G. N., Araujo, A., & Walter, M. E. (2020). What do female students in middle and high schools think about computer science majors in Brasilia, Brazil? A survey in 2011 and 2019. In 2020 IEEE Frontiers in Education Conference (FIE) (pp. 1–7). IEEE. https://doi.org/10.1109/FIE44824.2020.9274257
  • Hooshangi, S., Ellis, M., & Edwards, S. H. (2022). Factors influencing student performance and persistence in CS2. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education – Volume 1 (SIGCSE 2022) (pp. 286–292). Association for Computing Machinery. https://doi.org/10.1145/3478431.3499272
  • Howell, D. C. (2006). Statistical methods for psychology (6th ed.). Thomson Wadsworth.
  • İçen, M. (2022). The future of education utilizing artificial intelligence in Turkey. Humanities and Social Sciences Communications, 9(1), 1–10. https://doi.org/10.1057/s41599-022-01284-4
  • Jaccheri, L., Cutrupi, C. M., Diaconu, M. G., Szlavi, A., Takaoka, A. J. W., & Lenarduzzi, V. (2022). Where are the female professors in STEM? Preprint on TechRxiv. https://doi.org/10.36227/techrxiv.21760532.v1
  • Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33(7), 14–26. https://doi.org/10.3102/0013189X033007014
  • Kahveci, A., Sahin, N., & Genc, S. (2011). Computer perceptions of secondary school teachers and impacting demographics: A Turkish perspective. Turkish Online Journal of Educational Technology-TOJET, 10(1), 71–80. https://eric.ed.gov/?id=EJ926555
  • Katz, S., Allbritton, D., Aronis, J., Wilson, C., & Soffa, M. L. (2006). Gender, achievement, and persistence in an undergraduate computer science program. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 37(4), 42–57. https://doi.org/10.1145/1185335.1185344
  • Keane, T., Molnar, A., & Stockdale, R. (2021). Identifying Australian high school intervention programs that influence 1st year female students to choose ICT degrees. Proceedings of the 2021 ACM Conference on Innovation and Technology in Computer Science Education. https://doi.org/10.1145/3456565.3460004
  • Kelly, R., & Allen, M. (2023). Exploring engagement and self-efficacy in an introductory computer science course. In Proceedings of the 2023 ACM SIGPLAN International Symposium on SPLASH-E (SPLASH-E 2023) (pp. 60–68). Association for Computing Machinery. https://doi.org/10.1145/3622780.3623649
  • Kert, S., Kalelioglu, F., & Gulbahar, Y. (2019). A holistic approach for computer science education in secondary schools. Informatics in Education, 18(1), 105–121. https://doi.org/10.15388/infedu.2019.06
  • Mamat, N. J. Z., & Mazelan, F. F. (2011). Learning encouragement factors and academic performance. Procedia-Social and Behavioral Sciences, 18, 307–315. https://doi.org/10.1016/j.sbspro.2011.05.044
  • Margolis, J., & Fisher, A. (2002). Unlocking the clubhouse: Women in computing. MIT Press.
  • Master, A., Meltzoff, A. N., & Cheryan, S. (2021). Gender stereotypes about interests start early and cause gender disparities in computer science and engineering. Proceedings of the National Academy of Sciences, 118(48), e2100030118. https://doi.org/10.1073/pnas.2100030118
  • Master, A., Tang, D., Forsythe, D., Alexander, T. M., Cheryan, S., & Meltzoff, A. N. (2023). Gender equity and motivational readiness for computational thinking in early childhood. Early Childhood Research Quarterly, 64, 242–254. https://doi.org/10.1016/j.ecresq.2023.03.004
  • NCWIT. (2023). Women in tech by the numbers. National Center for Women & Information Technology. https://ncwit.org/resource/bythenumbers
  • Rosson, M. B., Carroll, J. M., & Sinha, H. (2011). Orientation of undergraduates toward careers in the computer and information sciences: Gender, self-efficacy, and social support. ACM Transactions on Computing Education, 11(3), Article 14, 1–23. https://doi.org/10.1145/2037276.2037278
  • Schmader, T. (2023). Gender inclusion and fit in STEM. Annual Review of Psychology, 74(1), 219–243. https://doi.org/10.1146/annurev-psych-032420-031902
  • Spieler, B., & Girvan, C. (2025). The PECC framework: Promoting gender sensitivity and gender equality in computer science education. Computers, 14(7), 249. https://doi.org/10.3390/computers14070249
  • Şahin, A., & Waxman, H. C. (2021). Factors affecting high school students’ STEM career interest: Findings from a 4-year study. Journal of STEM Education: Innovations and Research, 22(3).
  • Şimşek, H. (2013). University students’ tendencies toward and reasons behind dropout. Journal of Theoretical Educational Science, 6(2), 242–271. https://dergipark.org.tr/en/pub/akukeg/issue/29349/314064
  • Tari, M., Hua, V., Ng, L., & Annabi, H. (2021). How Asian women’s intersecting identities impact experiences in introductory computing courses. In Diversity, divergence, dialogue: 16th International Conference, iConference 2021, Beijing, China, March 17–31, 2021, Proceedings, Part I (pp. 603–617). Springer-Verlag. https://doi.org/10.1007/978-3-030-71292-1_47
There are 42 citations in total.

Details

Primary Language English
Subjects Computing Education, Engineering Education
Journal Section Research Article
Authors

Nehir Yasan Ak 0000-0003-4801-2740

Rukiye Altın 0000-0001-7593-2775

Submission Date October 28, 2025
Acceptance Date January 9, 2026
Publication Date March 30, 2026
DOI https://doi.org/10.55525/tjst.1812503
IZ https://izlik.org/JA98PP78FP
Published in Issue Year 2026 Volume: 21 Issue: 1

Cite

APA Yasan Ak, N., & Altın, R. (2026). Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye. Turkish Journal of Science and Technology, 21(1), 235-251. https://doi.org/10.55525/tjst.1812503
AMA 1.Yasan Ak N, Altın R. Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye. TJST. 2026;21(1):235-251. doi:10.55525/tjst.1812503
Chicago Yasan Ak, Nehir, and Rukiye Altın. 2026. “Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye”. Turkish Journal of Science and Technology 21 (1): 235-51. https://doi.org/10.55525/tjst.1812503.
EndNote Yasan Ak N, Altın R (March 1, 2026) Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye. Turkish Journal of Science and Technology 21 1 235–251.
IEEE [1]N. Yasan Ak and R. Altın, “Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye”, TJST, vol. 21, no. 1, pp. 235–251, Mar. 2026, doi: 10.55525/tjst.1812503.
ISNAD Yasan Ak, Nehir - Altın, Rukiye. “Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye”. Turkish Journal of Science and Technology 21/1 (March 1, 2026): 235-251. https://doi.org/10.55525/tjst.1812503.
JAMA 1.Yasan Ak N, Altın R. Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye. TJST. 2026;21:235–251.
MLA Yasan Ak, Nehir, and Rukiye Altın. “Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye”. Turkish Journal of Science and Technology, vol. 21, no. 1, Mar. 2026, pp. 235-51, doi:10.55525/tjst.1812503.
Vancouver 1.Nehir Yasan Ak, Rukiye Altın. Voice Across Gender: Factors Influencing Students’ Intention to Continue Studying Computer Science in Türkiye. TJST. 2026 Mar. 1;21(1):235-51. doi:10.55525/tjst.1812503