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Makine Mühendisliği ve Ekonometri Öğrencilerinin Programlamaya İlişkin Öz Yeterlik Algılarının İncelenmesi

Yıl 2016, Cilt: 17 Sayı: 2, 509 - 525, 01.05.2016

Öz

Bilgisayar programlama, bilişim sektöründe yaşanan hızlı değişimler sayesinde sektörün önemli bir dalı haline gelmiştir. Yükseköğretimde Bilgisayar ve Yazılım Mühendisliği bölümlerinin yanı sıra, farklı mühendislik bölümleri ile matematik ve fen bilimlerine dayalı diğer bölümlerde de bilgisayar programcılığına verilen önem artmaktadır. Bilgisayar bilimleri haricindeki bölümlerde akademik başarı ve öğrenci memnuniyeti açısından bilgisayar programlama öğretiminde bir takım sıkıntılar ile karşılaşılmaktadır. Bu sıkıntılar ve öz yeterlik algısının akademik başarı üzerindeki rolünden yola çıkarak, bu çalışmanın amacı Türkiye’de bir devlet üniversitesinin makine mühendisliği ve ekonometri bölümlerinde öğrenim gören lisans öğrencilerinin bilgisayar programlamaya ilişkin öz yeterlik algılarını incelemektir. Altun ve Mazman 2012 tarafından Türkçeye uyarlanan Programlamaya İlişkin Öz Yeterlik Algısı Ölçeği’nin veri toplama aracı olarak kullanıldığı ve toplam 138 öğrencinin katıldığı çalışmada, veriler betimsel istatistikler ve bağımsız örneklem t-testi ile analiz edilmiştir. Araştırmanın bulguları, öğrencilerin programlamaya ilişkin öz yeterlik algılarının düşük olduğunu göstermektedir. Öğrenciler basit programlama görevlerini algılayabilmekte, ancak karmaşık programlama görevlerini algılamada sorun yaşamaktadırlar. Araştırmanın diğer bulgularına göre, erkek öğrencilerin kız öğrencilere, Makine Mühendisliği öğrencilerinin Ekonometri öğrencilerine kıyasla programlamaya yönelik öz yeterlik algılarının yüksek olduğu görülmektedir. Öğrencilerin bilgisayar programlamaya ilişkin öz yeterlik algılarının yanı sıra hem tutum hem de önceki programlama deneyimine ek olarak öğrencilerin temel düzeyde programlama bilgisi içeren derslerdeki problem çözme yeteneklerinin ve yansıtıcı düşünme, algoritmik düşünme gibi üst düzey beceriler ile arasındaki ilişkilerin araştırılması faydalı olacaktır. Bilgisayar programlama ile ilgili yapılacak tüm çalışmalar, günümüzde son derece önemli bir yere sahip bu becerinin en etkin şekilde kazanılmasını sağlamaya ışık tutacaktır.

Kaynakça

  • Akkoyunlu B. ve Orhan F. (2003). Bilgisayar ve Öğretim Teknolojileri Eğitimi (BÖTE) Bölümü Öğrencilerinin Bilgisayar Kullanma Öz Yeterlik İnancı ile Demografik Özellikleri Arasındaki İlişki. The Turkish Online Journal of Educational Technology, 2(3), 86-93.
  • Altun, A. ve Mazman, S.G. (2012). Programlamaya ilişkin öz yeterlik algısı ölçeğinin Türkçe formumun geçerlilik ve güvenirlik çalışması. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 3(2), 297- 308.
  • Alvarado, C., Dodds, Z., & Libeskind-Hadas, R. (2012). Increasing women's participation in computing at Harvey Mudd College. ACM Inroads, 3(4), 55-64.
  • Ambrosio, A. P., Costa, F. M., Almeida, L., Franco, A., & Macedo, J. (2011,October). Identifying cognitive abilities to improve CS1 outcome. Paper presented by Frontiers in Education Conference (FIE)., Rapid City, South Dakota.
  • Aşkar, P., & Davenport, D. (2009). An investigation of factors related to self-efficacy for Java programming among engineering students. The Turkish Online Journal of Educational Technology (TOJET). 8(1), 26-32.
  • Balanskat, A. & Engelhardt, K. (2014). Computing our Future: Computer programming and coding - Priorities, school curricula, and initiatives across Europe. European Schoolnet http://www.eun.org/c/document_library/get_ file?uuid=521cb928-6ec4- 4a86-b522-9d8fd5cf60ce&groupId=43887
  • Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioural change. Psychological Review. 84(2), 191-215.
  • Barchino, R., Gutiérrez, J. M., De-Marcos, L., Martínez, J. J., Jiménez, L., Otón, S., Hilera, J. R. Et al. (2012). Experiences in the use of Mobile Games to improve Programming Skills in Computer Engineering. International Journal of Innovative Computing, Information and Control, 8(2), 1167-1174.
  • Başer, M. (2013). Developing attitude scale toward computer programming. International Journal of Social Science, 6(6), 199-215.
  • Bell, T., Andreae, P., & Robins, A. (2014). A case study of the introduction of computer science in NZ schools. Transactions on Computing Education (TOCE), 14(2), 10.
  • Bergersen, G. R., & Gustafsson, J.-E. (2011). Programming Skill, Knowledge, and Working Memory Among Professional Software Developers from an Investment Theory Perspective. Journal of Individual Differences, 32(4), 201-209. doi: 10.1027/1614-0001/a000052
  • Brown, N. C., Sentance, S., Crick, T., & Humphreys, S. (2014). Restart: The resurgence of computer science in UK schools. Transactions on Computing Education (TOCE), 14(2), 9.
  • Byrne, P., & Lyons, G. (2001). The Effect of Student Attributes on Success in Programming. SIGCSE Bulletin, 33(3), 49-52.
  • Carter, J., & Jenkins, T. (1999). Gender and programming: What's going on? SIGCSE Bulletin, 31(3), 1-4.
  • Davidson, K., Larzon, L. & Ljunggren, K. (2010). Self-Efficacy in Programming among STS Students. Technical Reports from Computer Science Education course of Upssala University.http://www.it.uu.se/edu/course/homepage/datadidaktik/ht10/reports adresinden 11.02.2016 tarihinde erişilmiştir.
  • Doyle, E., Stamouli, I., & Huggard, M. (2005). Computer anxiety, self-efficacy, computer experience: An investigation throughout a computer science degree. Proceedings of the 35th Annual Frontiers in Education Conference , FIE'05. S2H-3
  • Erdoğan, B. (2005). Programlama başarısı ile akademik basarı, genel yetenek, bilgisayara karsı tutum, cinsiyet ve lise türü arasındaki ilişkilerin incelenmesi. Yüksek lisans, Marmara Üniversitesi İstanbul.
  • Evans, G. E., & Mark G. S. (1989). What best predicts computer proficiency?. Communications of the ACM, 32(11), 1322-1327.
  • Fang, X. (2012). Application of the participatory method to the computer fundamentals course, Affective Computing and Intelligent Interaction. Advances in Intelligent and Soft Computing, 137, 185-189.
  • Fatin, A.P., Mohamad, B.A., Bakar, M.N., Noor,F.A.R., Lilia, E.M., Normah, M.G. (2010,April). Engineering elements profile among first- and final-year engineering students in Malaysia. Paper presented at IEEE Global Engineering Education Conference (EDUCON) , Amman, Jordan.
  • Feldgen, M., & Clua, O.(2004). Games as a Motivation for Freshman to Learn Programming. Proceedings of the 34th ASEE/IEEE Frontiers in Education Conference, 3, S1H/11–S1H/16
  • Goadrich, M. (2014). Incorporating tangible computing devices into CS1.Journal of Computing Sciences in Colleges, 29(5), 23-31.
  • Gomes, A. & Mendes, A. (2007). Learning to program – difficulties and solutions. Paper presented at International Conference on Education – ICEE 2007, Coimbra, Portugal.
  • Gouws, L. A., Bradshaw, K., & Wentworth, P. (2013, July). Computational thinking in educational activities: an evaluation of the educational game light-bot. Proceedings of the 18th ACM Conference On Innovation And Technology İn Computer Science Education ,10-15.
  • Guzdial, M., Ericson, B., Mcklin, T., & Engelman, S. (2014). Georgia computes An intervention in a US state, with formal and informal education in a policy context. ACM Transactions on Computing Education (TOCE), 14(2), 13.
  • Hawi, N. (2010). Causal attributions of success and failure made by undergraduate students in an introductory-level computer programming course. Computers & Education. 54, 1127–1136.
  • Hernane B., P., Gilney F., Z., & Marcelo A., M.(2010). Learning computer programming: Implementing a fractal in a Turing machine. Computers & Education. 55,767-776
  • Horzum, M. B., & Çakır, Ö. (2009). The validity and reliability study of the Turkish version of the online technologies self-efficacy scale. Educational Sciences: Theory & Practice, 9(3), 1343-1356.
  • Işık F. (2016, Ocak 17). Milli Eğitim Bakanlığımızla yapacağımız çalışma ile Kodlama dersini https://twitter.com/TCSanayi/status/688646739834843136 ‘dan erişildi. ve Liselerde Müfredata alacağız.
  • Jegede, P. O. (2009). Predictors of java programming self-efficacy among engineering students in a Nigerian university. International Journal of Computer Science and Information Security, 4(1&2).
  • Jenkins, T. (2002). On the difficulty of learning to program. Paper presented at 3rd annual Conference of LTSN-ICS, Loughbrorough University, Leicestershire, UK
  • Jones, S. J., & Burnett, G. (2008). Spatial Ability and Learning to Program. Human Technology, 4(1), 47-61.
  • Karasar, N. (2005). Bilimsel Araştırma Yöntemi, Ankara: Nobel Kitabevi.
  • 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.
  • Korkmaz, Ö. (2013). Prospective CITE teachers' self-efficacy perceptions on programming. Proceeding of the 2nd World Conference on Educational Technology Researches (WCETR-2012). 83, 639-643
  • Korkmaz, Ö., & Altun, H. (2013). Mühendislik ve BÖTE Öğrencilerinin Bilgisayar Programlama Öğrenmeye Dönük Tutumları. International Journal of Social Science, 6(2), 1169-1185.
  • Korkmaz, Ö., & Altun, H. (2014). Adapting Computer Programming Self-Efficacy Scale and Engineering Students’ Self-Efficacy Perceptions. Participatory Educational Research (PER), 1(1), 20-31.
  • Lahtinen, E., Ala-Mutka, K., & Järvinen, H.M. (2005). A study of the difficulties of novice programmers. in inroads - ACM SIGCSE Bulletin, 37, 14–18. ACM Press.
  • Lau, W. W. F., & Yuen, A. H. K. (2009). Exploring the effects of gender and learning styles on computer programming performance: implications for programming pedagogy. British Journal of Educational Technology, 40(4), 696-712.
  • Light-Bot (2015), Hour of code, https://lightbot.com/hour-of-code-2015.html adresinden 11.02.2016 tarihinde alınmıştır.
  • Mancy, R., & Reid, N. (2004). Aspects of Cognitive Style and Programming. Paper presented at the 16 th Workshop of the Psychology of Programming Interest Group (PPIG 16). Carlow, Ireland.
  • Mazman, S.G. (2013). Programlama Performansını Etkileyen Faktörlerin Bilişsel Tabanlı Bireysel Farklılıklar Temelinde Modellenmesi. Doktora Tezi, Hacettepe Üniversitesi, Ankara.
  • Mazman, S.G., ve Altun, A. (2013). Programlama–I Dersinin BÖTE Bölümü Öğrencilerinin Programlamaya İlişkin Öz Yeterlik Algıları Üzerine Etkisi. Journal of Instructional Technologies & Teacher Education, 2(3),24-29
  • Milne, I., & Rowe, G. (2002). Difficulties in learning and teaching programming views of students and tutors. Education and Information Technologies. 7(1), 55-66
  • Özyurt, Ö., & Özyurt, H. (2015). Bilgisayar programcılığı öğrencilerinin programlamaya karşı tutum ve programlama öz-yeterliklerinin belirlenmesine yönelik bir çalı. Eğitimde Kuram ve Uygulama. 11(1), 51-67.
  • Pereira, H. B. D. B., Zebende, G. F., & Moret, M. A. (2010). Learning computer programming: Implementing a fractal in a Turing Machine. Computers & Education, 55(2), 767-776.
  • Pillay N., & Jugoo V. R. (2005). An Investigation into Student Characteristics Affecting Novice Programming Performance, in inroads - ACM SIGCSE Bulletin. 37(4), 107-110, ACM Press.
  • Ramalingam, V. & Wiedenbeck, S. (1998). Development and validation of scores on a computer programming self-efficacy scale and group analysis of novice programmer self-efficacy. Journal of Educational Computing Research, 19(4), 367-381.
  • Ramalingam, V., LaBelle, D., & Wiedenbeck, S. (2004, June). Self-efficacy and mental models in learning to program. SIGCSE Bulletin 36(3), 171-175.
  • Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., ... & Kafai, Y. (2009). Scratch: programming for all.Communications of the ACM, 52(11), 60-67.
  • Robins, A. Rountree, J., & Rountree, N. (2003). Learning and Teaching Programming: A Review and Discussion. Computer Science Education, 13( 2), 137–172.
  • Rubio, M. A., Romero-Zaliz, R., Mañoso, C., & Angel, P. (2015). Closing the gender gap in an introductory programming course. Computers & Education,82, 409-420.
  • Saeli, M.,Perrenet, J., Jochems, W. M. G. ve Zwaneveld, B. (2011). Teaching programming in secondary school: A pedagogical content knowledge perspective.Informatics in Education, 10(1), 73-88.
  • Sebetci, Ö., & Aksu, G. (2014). Öğrencilerin mantıksal ve analitik düşünme becerilerinin programlama dilleri başarısına etkisi. Journal of Educational Sciences & practices, 13(25).
  • Sue J., & Gary B. (2008). Spatial Ability and Learning to Program. Interdisciplinary Journal on Humans in ICT Environments ,4 (1), 47–61.
  • Wiedenbeck S., LaBelle D., & Kain V. N.R. (2004). Factors Affecting Course Outcomes in Introductory Programming. 16th Annual Workshop of the Psychology of Programming Interest Group (PPIG16), 97-109.
  • Wolber, D., Abelson, H., Spertus, E., & Looney, L. (2011). App Inventor. O'Reilly Media, Inc.
  • Tan, P. H., Ting, C. Y., & Ling, S. W. (2009). Learning difficulties in programming courses: Undergraduates’ perspective and perception. International Conference on Computer Technology and Development, Kota Kinabalu, Malaysia.
  • Wang, Y., Liu, H., Feng, Y., Jiang, Y., & Liu, Y. (2012). Assessment of programming language learning based on peer code review model: Implementation and experience report. Computers & Education, 59,412–422.
  • Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82-91.

An Investigation of Perceived Self Efficacy of Engineering and Econometrics Students on Computer Programming

Yıl 2016, Cilt: 17 Sayı: 2, 509 - 525, 01.05.2016

Öz

Computer programming has come to the fore of the sector due to unprecedented pace of developments in information and communication technologies. Besides computer and software engineering, other engineering programmes and the programmes based on mathematics and natural sciences also give significant importance to programming. In view of the problems encountered in teaching computer programming in terms of academic achievement and student satisfaction for programmes other than computer sciences, and based on the role of perceived self-efficacy on academic achievement, this study aims to investigate perceived computer programming self-efficacy of undergraduate students of mechanical engineering and econometrics at a Turkish state university. Data were collected from 138 students through a Programming Self-Efficacy Scale, adapted by Altun and Mazman 2012 and analysed using descriptive statistics and independent sample t-test. Findings from the study indicates a low level of perceived self-efficacy for computer programming. Despite understanding simple programming tasks, students tend to encounter problems in understanding complex tasks. Other findings indicate that male students have a higher level of programming self-efficacy compared to female students; similarly, mechanical engineering students’ perceived self-efficacy is higher compared to econometrics students. It is important to continue to advance research studies on perceived self-efficacy for computer programming, and investigating relationship between self-efficacy, attitude, prior programming experience, and ownership of higher order thinking skills. Studies on computer programming will shed light and contribute to efforts for acquiring this very important skill of 21st century in the most efficient manner

Kaynakça

  • Akkoyunlu B. ve Orhan F. (2003). Bilgisayar ve Öğretim Teknolojileri Eğitimi (BÖTE) Bölümü Öğrencilerinin Bilgisayar Kullanma Öz Yeterlik İnancı ile Demografik Özellikleri Arasındaki İlişki. The Turkish Online Journal of Educational Technology, 2(3), 86-93.
  • Altun, A. ve Mazman, S.G. (2012). Programlamaya ilişkin öz yeterlik algısı ölçeğinin Türkçe formumun geçerlilik ve güvenirlik çalışması. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 3(2), 297- 308.
  • Alvarado, C., Dodds, Z., & Libeskind-Hadas, R. (2012). Increasing women's participation in computing at Harvey Mudd College. ACM Inroads, 3(4), 55-64.
  • Ambrosio, A. P., Costa, F. M., Almeida, L., Franco, A., & Macedo, J. (2011,October). Identifying cognitive abilities to improve CS1 outcome. Paper presented by Frontiers in Education Conference (FIE)., Rapid City, South Dakota.
  • Aşkar, P., & Davenport, D. (2009). An investigation of factors related to self-efficacy for Java programming among engineering students. The Turkish Online Journal of Educational Technology (TOJET). 8(1), 26-32.
  • Balanskat, A. & Engelhardt, K. (2014). Computing our Future: Computer programming and coding - Priorities, school curricula, and initiatives across Europe. European Schoolnet http://www.eun.org/c/document_library/get_ file?uuid=521cb928-6ec4- 4a86-b522-9d8fd5cf60ce&groupId=43887
  • Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioural change. Psychological Review. 84(2), 191-215.
  • Barchino, R., Gutiérrez, J. M., De-Marcos, L., Martínez, J. J., Jiménez, L., Otón, S., Hilera, J. R. Et al. (2012). Experiences in the use of Mobile Games to improve Programming Skills in Computer Engineering. International Journal of Innovative Computing, Information and Control, 8(2), 1167-1174.
  • Başer, M. (2013). Developing attitude scale toward computer programming. International Journal of Social Science, 6(6), 199-215.
  • Bell, T., Andreae, P., & Robins, A. (2014). A case study of the introduction of computer science in NZ schools. Transactions on Computing Education (TOCE), 14(2), 10.
  • Bergersen, G. R., & Gustafsson, J.-E. (2011). Programming Skill, Knowledge, and Working Memory Among Professional Software Developers from an Investment Theory Perspective. Journal of Individual Differences, 32(4), 201-209. doi: 10.1027/1614-0001/a000052
  • Brown, N. C., Sentance, S., Crick, T., & Humphreys, S. (2014). Restart: The resurgence of computer science in UK schools. Transactions on Computing Education (TOCE), 14(2), 9.
  • Byrne, P., & Lyons, G. (2001). The Effect of Student Attributes on Success in Programming. SIGCSE Bulletin, 33(3), 49-52.
  • Carter, J., & Jenkins, T. (1999). Gender and programming: What's going on? SIGCSE Bulletin, 31(3), 1-4.
  • Davidson, K., Larzon, L. & Ljunggren, K. (2010). Self-Efficacy in Programming among STS Students. Technical Reports from Computer Science Education course of Upssala University.http://www.it.uu.se/edu/course/homepage/datadidaktik/ht10/reports adresinden 11.02.2016 tarihinde erişilmiştir.
  • Doyle, E., Stamouli, I., & Huggard, M. (2005). Computer anxiety, self-efficacy, computer experience: An investigation throughout a computer science degree. Proceedings of the 35th Annual Frontiers in Education Conference , FIE'05. S2H-3
  • Erdoğan, B. (2005). Programlama başarısı ile akademik basarı, genel yetenek, bilgisayara karsı tutum, cinsiyet ve lise türü arasındaki ilişkilerin incelenmesi. Yüksek lisans, Marmara Üniversitesi İstanbul.
  • Evans, G. E., & Mark G. S. (1989). What best predicts computer proficiency?. Communications of the ACM, 32(11), 1322-1327.
  • Fang, X. (2012). Application of the participatory method to the computer fundamentals course, Affective Computing and Intelligent Interaction. Advances in Intelligent and Soft Computing, 137, 185-189.
  • Fatin, A.P., Mohamad, B.A., Bakar, M.N., Noor,F.A.R., Lilia, E.M., Normah, M.G. (2010,April). Engineering elements profile among first- and final-year engineering students in Malaysia. Paper presented at IEEE Global Engineering Education Conference (EDUCON) , Amman, Jordan.
  • Feldgen, M., & Clua, O.(2004). Games as a Motivation for Freshman to Learn Programming. Proceedings of the 34th ASEE/IEEE Frontiers in Education Conference, 3, S1H/11–S1H/16
  • Goadrich, M. (2014). Incorporating tangible computing devices into CS1.Journal of Computing Sciences in Colleges, 29(5), 23-31.
  • Gomes, A. & Mendes, A. (2007). Learning to program – difficulties and solutions. Paper presented at International Conference on Education – ICEE 2007, Coimbra, Portugal.
  • Gouws, L. A., Bradshaw, K., & Wentworth, P. (2013, July). Computational thinking in educational activities: an evaluation of the educational game light-bot. Proceedings of the 18th ACM Conference On Innovation And Technology İn Computer Science Education ,10-15.
  • Guzdial, M., Ericson, B., Mcklin, T., & Engelman, S. (2014). Georgia computes An intervention in a US state, with formal and informal education in a policy context. ACM Transactions on Computing Education (TOCE), 14(2), 13.
  • Hawi, N. (2010). Causal attributions of success and failure made by undergraduate students in an introductory-level computer programming course. Computers & Education. 54, 1127–1136.
  • Hernane B., P., Gilney F., Z., & Marcelo A., M.(2010). Learning computer programming: Implementing a fractal in a Turing machine. Computers & Education. 55,767-776
  • Horzum, M. B., & Çakır, Ö. (2009). The validity and reliability study of the Turkish version of the online technologies self-efficacy scale. Educational Sciences: Theory & Practice, 9(3), 1343-1356.
  • Işık F. (2016, Ocak 17). Milli Eğitim Bakanlığımızla yapacağımız çalışma ile Kodlama dersini https://twitter.com/TCSanayi/status/688646739834843136 ‘dan erişildi. ve Liselerde Müfredata alacağız.
  • Jegede, P. O. (2009). Predictors of java programming self-efficacy among engineering students in a Nigerian university. International Journal of Computer Science and Information Security, 4(1&2).
  • Jenkins, T. (2002). On the difficulty of learning to program. Paper presented at 3rd annual Conference of LTSN-ICS, Loughbrorough University, Leicestershire, UK
  • Jones, S. J., & Burnett, G. (2008). Spatial Ability and Learning to Program. Human Technology, 4(1), 47-61.
  • Karasar, N. (2005). Bilimsel Araştırma Yöntemi, Ankara: Nobel Kitabevi.
  • 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.
  • Korkmaz, Ö. (2013). Prospective CITE teachers' self-efficacy perceptions on programming. Proceeding of the 2nd World Conference on Educational Technology Researches (WCETR-2012). 83, 639-643
  • Korkmaz, Ö., & Altun, H. (2013). Mühendislik ve BÖTE Öğrencilerinin Bilgisayar Programlama Öğrenmeye Dönük Tutumları. International Journal of Social Science, 6(2), 1169-1185.
  • Korkmaz, Ö., & Altun, H. (2014). Adapting Computer Programming Self-Efficacy Scale and Engineering Students’ Self-Efficacy Perceptions. Participatory Educational Research (PER), 1(1), 20-31.
  • Lahtinen, E., Ala-Mutka, K., & Järvinen, H.M. (2005). A study of the difficulties of novice programmers. in inroads - ACM SIGCSE Bulletin, 37, 14–18. ACM Press.
  • Lau, W. W. F., & Yuen, A. H. K. (2009). Exploring the effects of gender and learning styles on computer programming performance: implications for programming pedagogy. British Journal of Educational Technology, 40(4), 696-712.
  • Light-Bot (2015), Hour of code, https://lightbot.com/hour-of-code-2015.html adresinden 11.02.2016 tarihinde alınmıştır.
  • Mancy, R., & Reid, N. (2004). Aspects of Cognitive Style and Programming. Paper presented at the 16 th Workshop of the Psychology of Programming Interest Group (PPIG 16). Carlow, Ireland.
  • Mazman, S.G. (2013). Programlama Performansını Etkileyen Faktörlerin Bilişsel Tabanlı Bireysel Farklılıklar Temelinde Modellenmesi. Doktora Tezi, Hacettepe Üniversitesi, Ankara.
  • Mazman, S.G., ve Altun, A. (2013). Programlama–I Dersinin BÖTE Bölümü Öğrencilerinin Programlamaya İlişkin Öz Yeterlik Algıları Üzerine Etkisi. Journal of Instructional Technologies & Teacher Education, 2(3),24-29
  • Milne, I., & Rowe, G. (2002). Difficulties in learning and teaching programming views of students and tutors. Education and Information Technologies. 7(1), 55-66
  • Özyurt, Ö., & Özyurt, H. (2015). Bilgisayar programcılığı öğrencilerinin programlamaya karşı tutum ve programlama öz-yeterliklerinin belirlenmesine yönelik bir çalı. Eğitimde Kuram ve Uygulama. 11(1), 51-67.
  • Pereira, H. B. D. B., Zebende, G. F., & Moret, M. A. (2010). Learning computer programming: Implementing a fractal in a Turing Machine. Computers & Education, 55(2), 767-776.
  • Pillay N., & Jugoo V. R. (2005). An Investigation into Student Characteristics Affecting Novice Programming Performance, in inroads - ACM SIGCSE Bulletin. 37(4), 107-110, ACM Press.
  • Ramalingam, V. & Wiedenbeck, S. (1998). Development and validation of scores on a computer programming self-efficacy scale and group analysis of novice programmer self-efficacy. Journal of Educational Computing Research, 19(4), 367-381.
  • Ramalingam, V., LaBelle, D., & Wiedenbeck, S. (2004, June). Self-efficacy and mental models in learning to program. SIGCSE Bulletin 36(3), 171-175.
  • Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., ... & Kafai, Y. (2009). Scratch: programming for all.Communications of the ACM, 52(11), 60-67.
  • Robins, A. Rountree, J., & Rountree, N. (2003). Learning and Teaching Programming: A Review and Discussion. Computer Science Education, 13( 2), 137–172.
  • Rubio, M. A., Romero-Zaliz, R., Mañoso, C., & Angel, P. (2015). Closing the gender gap in an introductory programming course. Computers & Education,82, 409-420.
  • Saeli, M.,Perrenet, J., Jochems, W. M. G. ve Zwaneveld, B. (2011). Teaching programming in secondary school: A pedagogical content knowledge perspective.Informatics in Education, 10(1), 73-88.
  • Sebetci, Ö., & Aksu, G. (2014). Öğrencilerin mantıksal ve analitik düşünme becerilerinin programlama dilleri başarısına etkisi. Journal of Educational Sciences & practices, 13(25).
  • Sue J., & Gary B. (2008). Spatial Ability and Learning to Program. Interdisciplinary Journal on Humans in ICT Environments ,4 (1), 47–61.
  • Wiedenbeck S., LaBelle D., & Kain V. N.R. (2004). Factors Affecting Course Outcomes in Introductory Programming. 16th Annual Workshop of the Psychology of Programming Interest Group (PPIG16), 97-109.
  • Wolber, D., Abelson, H., Spertus, E., & Looney, L. (2011). App Inventor. O'Reilly Media, Inc.
  • Tan, P. H., Ting, C. Y., & Ling, S. W. (2009). Learning difficulties in programming courses: Undergraduates’ perspective and perception. International Conference on Computer Technology and Development, Kota Kinabalu, Malaysia.
  • Wang, Y., Liu, H., Feng, Y., Jiang, Y., & Liu, Y. (2012). Assessment of programming language learning based on peer code review model: Implementation and experience report. Computers & Education, 59,412–422.
  • Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82-91.
Toplam 60 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Research Article
Yazarlar

Deniz Mertkan Gezgin Bu kişi benim

Müge Adnan Bu kişi benim

Yayımlanma Tarihi 1 Mayıs 2016
Yayımlandığı Sayı Yıl 2016 Cilt: 17 Sayı: 2

Kaynak Göster

APA Gezgin, D. M., & Adnan, M. (2016). Makine Mühendisliği ve Ekonometri Öğrencilerinin Programlamaya İlişkin Öz Yeterlik Algılarının İncelenmesi. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 17(2), 509-525.

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