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MODELING THE PSYCHOLOGICAL FACTORS AFFECTING COMPUTER PROGRAMMING SELF-EFFICACY / BİLGİSAYAR PROGRAMLAMA ÖZ-YETERLİLİĞİNİ ETKİLEYEN PSİKOLOJİK FAKTÖRLERİN İNCELENMESİ

Year 2017, Volume: 5 Issue: 1, 17 - 27, 30.06.2017

Abstract

We live in such an age that computer technologies and machines are one
of the most crucial parts of human beings lives that our need and
dependency to them growing exponentially day by day. This leads to
increased need of more human power and involvement in programming
computers and machines. Despite the increasing need however, studies
indicate that number of students that prefers departments regarding
computer and machine programming, software developing and engineering is
declining. In this direction, it is necessary to examine the factors
that are related to computer programming and to investigate the reasons
of developments mentioned earlier. Therefore, this study aimed to
examine the psychological factors that are thought to be related to
computer programming self-efficacy. In order to do that, relationships
between computer programming self-efficacy, attitude toward computer
programming, psychological resilience and problem solving were
investigated by using correlation test and structural equation modeling.
Students from four different departments and state universities filled
out a questionnaire that contains Computer Programming Self-Efficacy
Scale (CPSES), Attitude Scale Toward Computer Programming (ATCP), Brief
Resilience Scale (BRS), Social Problem Solving Inventory-Short Form
(SPSI-SF) voluntarily and anonymously. As a result of the analyses, it
was observed that computer programming self-efficacy was related
positively to confidence and motivation in learning computer
programming, psychological resilience, positive problem orientation and
rationale problem solving, and also it was negatively related to
negative problem orientation. The findings were discussed in the light
of existing literature.

References

  • Altun, A., & Mazman, S. G. (2012). [Validity and reliability analysis of Turkish form of computer programming self-efficacy scale]. Journal of Measurement and Evaluation in Education and Psychology, 3(2), 297-308.
  • Askar, P., & Davenport, D. (2009). An investigation of factors related to self-efficacy for java programming among engineering students. TOJET: The Turkish Online Journal of Educational Technology, 8(1).
  • Başer, M. (2013). Developing attitude scale toward computer programming. The Journal of Academic Social Science Studies, 6(6), 199-215.
  • Coşkun, Y. D., Garipağaoğlu, Ç., & Tosun, Ü. (2014). Analysis of the relationship between the resiliency level and problem solving skills of university students. Procedia-Social and Behavioral Sciences, 114, 673-680.
  • Charters, P., Lee, M. J., Ko, A. J., & Loksa, D. (2014, March). Challenging stereotypes and changing attitudes: the effect of a brief programming encounter on adults' attitudes toward programming. In Proceedings of the 45th ACM technical symposium on Computer science education (pp. 653-658). ACM.
  • Criss, M. M., Pettit, G. S., Bates, J. E., Dodge, K. A., & Lapp, A. L. (2002). Family adversity, positive peer relationships, and children’s externalizing behavior: A longitudinal perspective on risk and resilience. Child development, 73(4), 1220-1237.
  • Çekici, F. (2009). The effects of skills enhancement group program which is based on problem solving therapy on college students’ social problem solving skills, anger related behaviours and cognitions, trait-anxiety levels (Doctoral Dissertation). Çukurova University, Department of Educational Sciences, Adana.
  • Davidsson, K., Larzon, L., & Ljunggren, K. (2010). Self-efficacy in programming among STS students. Retrieved August, 12, 2013.
  • Doğan, T. (2015). Adaptation of the Brief Resilience Scale into Turkish: A validity and reliability study. The Journal of Happiness & Well-Being, 3 (1), 93-102.
  • D’ Zurilla, T.J., A.M., Nezu, A, Maydeu-Olivares (2004), Social Problem Solving: Theory and Assessment. Chang, E.C., D’ Zurilla, T.J., Sanna, L.J. (Editors), Social Problem Solving: Theory, Research and Training, American Psychological Association, Washington, DC.
  • Fisher, A., & Margolis, J. (2002). Unlocking the clubhouse: the Carnegie Mellon experience. ACM SIGCSE Bulletin, 34(2), 79-83.
  • Gizir, C. A. (2007). Psikolojik Sağlamlık, risk faktörleri ve koruyucu faktörler üzerine bir derleme çalışması. Türk Psikolojik Danışma ve Rehberlik Dergisi, 3(28), 113-128.
  • Gökalp, S., & Aydın, T. (2013). Teknik program öğrencilerinin bilgisayar ve internet kullanımına yönelik tutumlarının analizi. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 2(2).
  • Gökdaş, İ. (2008). Bilgisayara Yönelik Tutumlar. (Editör: D. Deryakulu). Bilişim Teknolojileri Öğretiminde Sosyo-Psikolojik Değişkenler içinde (ss.125- 150). Ankara: Maya Akademi.
  • Habibi, A., & Milani, M. M. R. A. (2014). Rates associated problem-solving ability with programming in computer students. ICEMST 2014, 854.
  • Hu, L. T. & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structural analysis: Conventional criteria versus new alternatives, Structural Equation Modelling, 6 (1), 1-55.
  • Kelleher, C., & Pausch, R. (2005). Lowering the barriers to programming: A taxonomy of programming environments and languages for novice programmers. ACM Computing Surveys (CSUR), 37(2), 83-137.
  • Korkmaz, Ö. (2012). The impact of critical thinking and logical-mathematical intelligence on algorithmic design skills. Journal of Educational Computing Research, 46(2), 173-193.
  • Kukul, V., & Gökçearslan, Ş. (2014). Scratch Ile Programlama Eğitimi Alan Öğrencilerin Problem Çözme Becerilerinin Incelenmesi Investigating The Problem Solving Skills Of Students Attended Scratch Programming Course.
  • Kurland, D. M., Pea, R. D., Clement, C., & Mawby, R. (1986). A study of the development of programming ability and thinking skills in high school students. Journal of Educational Computing Research, 2(4), 429-458.
  • Li, M. H., Eschenauer, R., & Yang, Y. (2013). Influence of efficacy and resilience on problem solving in the United States, Taiwan, and China. Journal of Multicultural Counseling and Development, 41(3), 144-157.
  • Fisher, A., & Margolis, J. (2002). Unlocking the clubhouse: the Carnegie Mellon experience. ACM SIGCSE Bulletin, 34(2), 79-83.
  • Özyurt, Ö., & Özyurt, H. (2015). Bilgisayar Programcılığı Öğrencilerinin Programlamaya Karşı Tutum ve Programlama Öz Yeterliklerinin Belirlenmesine Yönelik Bir Çalışma. Eğitimde Kuram ve Uygulama, 11(1), 51-67.
  • Pears, A., Seidman, S., Malmi, L., Mannila, L., Adams, E., Bennedsen, J., ... & Paterson, J. (2007). A survey of literature on the teaching of introductory programming. ACM SIGCSE Bulletin, 39(4), 204-223.
  • Ramalingam, V., & Wiedenbeck, S. (1998). Development and validation of scores on a computer programming self-efficacy scale and group analyses of novice programmer self-efficacy. Journal of Educational Computing Research, 19(4), 367-381.
  • Saeli, M., Perrenet, J., Jochems, W. M., & Zwaneveld, B. (2011). Teaching programming in secondary school: a pedagogical content knowledge perspective. Informatics in Education-An International Journal, (Vol 10_1), 73-88.
  • Shashaani, L. (1997). Gender differences in computer attitudes and use among college students. Journal of Educational Computing Research, 16(1), 37-51.
  • Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P., & Jennifer Bernard, J. (2008). The brief resilience scale: Assessing the ability to bounce back. International Journal of Behavioral Medicine, 15, 194–200.
  • Şad, S. N., & Demir, O. (2015). Computer and Internet Use Self-Efficacy Scale for Elementary School Teachers: Validity and Reliability Studies. Elementary Education Online, 14(2), 489-510.
  • Tabanao, E. S., Rodrigo, M. M. T., & Jadud, M. C. (2011, August). Predicting at-risk novice Java programmers through the analysis of online protocols. In Proceedings of the seventh international workshop on Computing education research (pp. 85-92). ACM.
  • Utting, I., Cooper, S., Kölling, M., Maloney, J., & Resnick, M. (2010). Alice, greenfoot, and scratch – a discussion. ACM TOCE, 10(4), 17.
  • Wikipedia, 2016. Programming. Retrieved from https://tr.wikipedia.org/wiki/Programlama
  • Yöndem Z. D., Bahtiyar M. (2016) Ergenlerde Psikolojik Dayanıklılık ve Stresle Baş Etme. The Journal Of Academic Social Science Studies, 45, 53-62.
Year 2017, Volume: 5 Issue: 1, 17 - 27, 30.06.2017

Abstract

References

  • Altun, A., & Mazman, S. G. (2012). [Validity and reliability analysis of Turkish form of computer programming self-efficacy scale]. Journal of Measurement and Evaluation in Education and Psychology, 3(2), 297-308.
  • Askar, P., & Davenport, D. (2009). An investigation of factors related to self-efficacy for java programming among engineering students. TOJET: The Turkish Online Journal of Educational Technology, 8(1).
  • Başer, M. (2013). Developing attitude scale toward computer programming. The Journal of Academic Social Science Studies, 6(6), 199-215.
  • Coşkun, Y. D., Garipağaoğlu, Ç., & Tosun, Ü. (2014). Analysis of the relationship between the resiliency level and problem solving skills of university students. Procedia-Social and Behavioral Sciences, 114, 673-680.
  • Charters, P., Lee, M. J., Ko, A. J., & Loksa, D. (2014, March). Challenging stereotypes and changing attitudes: the effect of a brief programming encounter on adults' attitudes toward programming. In Proceedings of the 45th ACM technical symposium on Computer science education (pp. 653-658). ACM.
  • Criss, M. M., Pettit, G. S., Bates, J. E., Dodge, K. A., & Lapp, A. L. (2002). Family adversity, positive peer relationships, and children’s externalizing behavior: A longitudinal perspective on risk and resilience. Child development, 73(4), 1220-1237.
  • Çekici, F. (2009). The effects of skills enhancement group program which is based on problem solving therapy on college students’ social problem solving skills, anger related behaviours and cognitions, trait-anxiety levels (Doctoral Dissertation). Çukurova University, Department of Educational Sciences, Adana.
  • Davidsson, K., Larzon, L., & Ljunggren, K. (2010). Self-efficacy in programming among STS students. Retrieved August, 12, 2013.
  • Doğan, T. (2015). Adaptation of the Brief Resilience Scale into Turkish: A validity and reliability study. The Journal of Happiness & Well-Being, 3 (1), 93-102.
  • D’ Zurilla, T.J., A.M., Nezu, A, Maydeu-Olivares (2004), Social Problem Solving: Theory and Assessment. Chang, E.C., D’ Zurilla, T.J., Sanna, L.J. (Editors), Social Problem Solving: Theory, Research and Training, American Psychological Association, Washington, DC.
  • Fisher, A., & Margolis, J. (2002). Unlocking the clubhouse: the Carnegie Mellon experience. ACM SIGCSE Bulletin, 34(2), 79-83.
  • Gizir, C. A. (2007). Psikolojik Sağlamlık, risk faktörleri ve koruyucu faktörler üzerine bir derleme çalışması. Türk Psikolojik Danışma ve Rehberlik Dergisi, 3(28), 113-128.
  • Gökalp, S., & Aydın, T. (2013). Teknik program öğrencilerinin bilgisayar ve internet kullanımına yönelik tutumlarının analizi. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 2(2).
  • Gökdaş, İ. (2008). Bilgisayara Yönelik Tutumlar. (Editör: D. Deryakulu). Bilişim Teknolojileri Öğretiminde Sosyo-Psikolojik Değişkenler içinde (ss.125- 150). Ankara: Maya Akademi.
  • Habibi, A., & Milani, M. M. R. A. (2014). Rates associated problem-solving ability with programming in computer students. ICEMST 2014, 854.
  • Hu, L. T. & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structural analysis: Conventional criteria versus new alternatives, Structural Equation Modelling, 6 (1), 1-55.
  • Kelleher, C., & Pausch, R. (2005). Lowering the barriers to programming: A taxonomy of programming environments and languages for novice programmers. ACM Computing Surveys (CSUR), 37(2), 83-137.
  • Korkmaz, Ö. (2012). The impact of critical thinking and logical-mathematical intelligence on algorithmic design skills. Journal of Educational Computing Research, 46(2), 173-193.
  • Kukul, V., & Gökçearslan, Ş. (2014). Scratch Ile Programlama Eğitimi Alan Öğrencilerin Problem Çözme Becerilerinin Incelenmesi Investigating The Problem Solving Skills Of Students Attended Scratch Programming Course.
  • Kurland, D. M., Pea, R. D., Clement, C., & Mawby, R. (1986). A study of the development of programming ability and thinking skills in high school students. Journal of Educational Computing Research, 2(4), 429-458.
  • Li, M. H., Eschenauer, R., & Yang, Y. (2013). Influence of efficacy and resilience on problem solving in the United States, Taiwan, and China. Journal of Multicultural Counseling and Development, 41(3), 144-157.
  • Fisher, A., & Margolis, J. (2002). Unlocking the clubhouse: the Carnegie Mellon experience. ACM SIGCSE Bulletin, 34(2), 79-83.
  • Özyurt, Ö., & Özyurt, H. (2015). Bilgisayar Programcılığı Öğrencilerinin Programlamaya Karşı Tutum ve Programlama Öz Yeterliklerinin Belirlenmesine Yönelik Bir Çalışma. Eğitimde Kuram ve Uygulama, 11(1), 51-67.
  • Pears, A., Seidman, S., Malmi, L., Mannila, L., Adams, E., Bennedsen, J., ... & Paterson, J. (2007). A survey of literature on the teaching of introductory programming. ACM SIGCSE Bulletin, 39(4), 204-223.
  • Ramalingam, V., & Wiedenbeck, S. (1998). Development and validation of scores on a computer programming self-efficacy scale and group analyses of novice programmer self-efficacy. Journal of Educational Computing Research, 19(4), 367-381.
  • Saeli, M., Perrenet, J., Jochems, W. M., & Zwaneveld, B. (2011). Teaching programming in secondary school: a pedagogical content knowledge perspective. Informatics in Education-An International Journal, (Vol 10_1), 73-88.
  • Shashaani, L. (1997). Gender differences in computer attitudes and use among college students. Journal of Educational Computing Research, 16(1), 37-51.
  • Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P., & Jennifer Bernard, J. (2008). The brief resilience scale: Assessing the ability to bounce back. International Journal of Behavioral Medicine, 15, 194–200.
  • Şad, S. N., & Demir, O. (2015). Computer and Internet Use Self-Efficacy Scale for Elementary School Teachers: Validity and Reliability Studies. Elementary Education Online, 14(2), 489-510.
  • Tabanao, E. S., Rodrigo, M. M. T., & Jadud, M. C. (2011, August). Predicting at-risk novice Java programmers through the analysis of online protocols. In Proceedings of the seventh international workshop on Computing education research (pp. 85-92). ACM.
  • Utting, I., Cooper, S., Kölling, M., Maloney, J., & Resnick, M. (2010). Alice, greenfoot, and scratch – a discussion. ACM TOCE, 10(4), 17.
  • Wikipedia, 2016. Programming. Retrieved from https://tr.wikipedia.org/wiki/Programlama
  • Yöndem Z. D., Bahtiyar M. (2016) Ergenlerde Psikolojik Dayanıklılık ve Stresle Baş Etme. The Journal Of Academic Social Science Studies, 45, 53-62.
There are 33 citations in total.

Details

Journal Section Makaleler
Authors

Kağan Kırcaburun

İbrahim Baştuğ This is me

Muhammed Bahtiyar

Publication Date June 30, 2017
Submission Date September 28, 2017
Published in Issue Year 2017 Volume: 5 Issue: 1

Cite

APA Kırcaburun, K., Baştuğ, İ., & Bahtiyar, M. (2017). MODELING THE PSYCHOLOGICAL FACTORS AFFECTING COMPUTER PROGRAMMING SELF-EFFICACY / BİLGİSAYAR PROGRAMLAMA ÖZ-YETERLİLİĞİNİ ETKİLEYEN PSİKOLOJİK FAKTÖRLERİN İNCELENMESİ. Anadolu Eğitim Liderliği Ve Öğretim Dergisi, 5(1), 17-27.

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