Adaptation of the Programming Resilience Scale to Turkish Culture: A Validity and Reliability Study

Öz

The aim of this research is to adapt the Programming Resilience Scale, which consists of 12 items and 4 sub-dimensions, to Turkish culture and to conduct the validity and reliability study of the scale. The original version of the scale was first translated into Turkish and the final version of the scale translation was formed in line with the opinions of academicians who are experts in the field of CEIT, Turkish language experts and English language experts. Then, it was applied to 15 people representing the target group for trial purposes. In line with expert opinions and as a result of the trial application, it was found that the Turkish translation was compatible with the original translation in terms of meaning, was sufficient in terms of Turkish language and was understandable for the target audience. The final version of the scale was applied to the target population for confirmatory factor analysis, and as a result of the analysis, a model with excellent and good fit was obtained according to the fit indices. In order to calculate the reliability of the scale, the internal consistency coefficient was calculated and it was found that the scale reliability coefficient was between the criterion values. All these results show that the scale was successfully adapted to Turkish culture and is valid and reliable. In addition, it would be useful to test the scale in different samples in future studies in order to examine the validity and reliability analyses of the scale more comprehensively.

Anahtar Kelimeler

• Programming
• resilience
• scale adaptation

Programlama Sürecinde Dayanıklılık Ölçeğinin Türk Kültürüne Uyarlanması: Geçerlik ve Güvenirlik Çalışması

Öz

Bu araştırmanın amacı 12 madde ve 4 alt boyuttan oluşan Programlama Sürecinde Dayanıklılık Ölçeğinin Türk kültürüne uyarlanması ve ölçeğin geçerlilik ve güvenilirlik çalışmasının yapılmasıdır. Ölçeğin orijinal hali ilk olarak Türkçeye çevrilmiş ve BÖTE alanında uzman, Türkçe dil uzmanı ve İngilizce dil uzmanı akademisyenlerin görüşleri doğrultusunda ölçek çevirisinin son hali oluşturulmuş ve hedef kitleyi temsil eden 15 kişiye uygulanmıştır. Uzman görüşleri doğrultusunda ve deneme uygulaması sonucunda Türkçe çevirinin anlam bakımından orijinal çeviri ile uyumlu olduğu, Türkçe dil bakımından yeterli olduğu ve hedef kitle açısından da anlaşılır olduğu görülmüştür. Ölçeğin en son hali doğrulayıcı faktör analizi için hedef kitleye uygulanmış ve analiz sonucunda uyum indekslerine göre mükemmel ve iyi uyum elde edilen bir model ortaya çıkmıştır. Ölçeğin güvenirliğinin hesaplaması için iç tutarlık katsayısı hesaplanmış ve ölçek güvenirlik katsayısının kriter değerler arasında olduğu bulunmuştur. Tüm bu sonuçlar ölçeğin Türk kültürüne uygun olarak başarıyla adapte edildiğini ve geçerli ve güvenilir olduğunu göstermektedir. Bunun yanında ileriki araştırmalarda ölçeğin farklı örneklemlerde test edilmesi, ölçeğin geçerlilik ve güvenilirlik analizlerini daha kapsamlı bir şekilde incelemek açısından faydalı olacaktır.

Anahtar Kelimeler

• Programlama
• dayanıklılık
• ölçek uyarlama

Kaynakça

1. Ahmavaara, A., & Houston, D.M. (2007). The effects of selective schooling and selfconcept on adolescents‘ academic aspiration: An examination of Dweck‘s selftheory. British Journal of Educational Psychology, 77(3), 613-632.
2. Alva, S.A. (1991). Academic invulnerability among Mexican-American students: The importance of protective and resources and appraisals. Hispanic Journal of Behavioral Sciences, 13(1), 18–34.
3. Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence. Journal of Experimental Social Psychology, 38(2), 113-125. https://doi.org/10.1006/jesp.2001.1491
4. Arslan, G., & Balkıs, M. (2016). Ergenlerde duygusal istismar, problem davranışlar, öz-yeterlik ve psikolojik sağlamlık arasındaki ilişki. Sakarya University Journal of Education, 6(1), 8-22.
5. Basım, H. N., & Çetin, F. (2011). Yetişkinler için psikolojik dayanıklılık ölçeği’ nin güvenilirlik ve geçerlilik çalışması. Türk Psikiyatri Dergisi, 22(2), 104-114.
6. Bayrakçeken, S., Oktay, Ö., Samancı, O., & Canpolat, N. (2021). Motivasyon kuramları çerçevesinde öğrencilerin öğrenme motivasyonlarının arttırılması: Bir derleme çalışması. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 25 (2), 677-698.
7. Bennedsen, J., & Caspersen, M. E. (2019). Failure rates in introductory programming - 12 years later. ACM Inroads, 10(2), 30-35. https://doi.org/10.1145/3324888
8. Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78(1), 246-263. https://doi.org/10.1111/j.1467-8624.2007.00995.x

9. Bosse, Y., & Gerosa, M. A. (2017). Why is programming so difficult to learn? Patterns of difficulties related to programming learning Mid-Stage. ACM SIGSOFT Software Engineering Notes, 41(6), 1-6. https://doi.org/10.1145/3011286.3011301 Brown, T. A. (2006). Confirmatory factor analysis for applied research. GuilfordPress
10. Brooks, J. E. (2006). Strengthening resilience in children and youths: Maximizing opportunities in the schools. Children and Schools, 28(2), 69–76.
11. Byrne, B. M. (1994). Structural equation modeling with EQS and EQS/Windows: Basic concepts, applications, and programming. Sage Publications, Inc.
12. Cassidy, S. (2015). Resilience building in students: The role of academic self-efficacy. Frontiers in psychology, 6, 1781.
13. Cheah, C. S. (2020). Factors contributing to the difficulties in teaching and learning of computer programming: A literature review. Contemporary Educational Technology, 12(2), 272.
14. Chisholm-Burns, M. A., Spivey, C. A., Sherwin, E., Williams, J., & Phelps, S. (2019). Development of an instrument to measure academic resilience among pharmacy students. American Journal of Pharmaceutical Education, 83(6), 1390-6896. https://doi.org/10.5688/ajpe6896
15. Christoph, G., Goldhammer, F., Zylka, J., & Hartig, J. (2015). Adolescents' computer performance: The role of self-concept and motivational aspects. Computers & Education, 81, 1-12.
16. Çetin, B., & İlhan, M. (2013). The Turkish adaptation of implicit theory of intelligence scale the validity and reliability study. Necatibey Eğitim Fakültesi Elektronik Fen ve Matematik Eğitimi Dergisi, 7(1).
17. Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2014). Sosyal bilimler için çok değişkenli istatistik: SPSS ve Lisrel uygulamaları. Pegem Akademi.
18. Dane, E., & Olgun, N. (2016). Hemodiyaliz hastalarının psikolojik dayanıklılık durumları ve etkileyen faktörlerin değerlendirilmesi. Nefroloji Hemşireliği Dergisi, 11(1), 43-54.
19. Dweck, C. S. (2013). Self-theories: Their role in motivation, personality, and development. Psychology press.
20. Eccles, J. S. (2005). Subjective task values and the model of achievement related choices. A. J. Elliot & C. S. Dweck (Eds.). In Handbook of competence and motivation (105-121). Guilford Publications.
21. Fergus, S., & Zimmerman, M. A. (2005). Adolescent resilience: A framework for understanding healthy development in the face of risk. Annual Review of Public Health, 26(1), 399-419.
22. Finn, J. D., & Rock, D. A. (1997). Academic success among students at risk for school failure. Journal of Applied Psychology, 82(2), 221-234.
23. Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological assessment, 7(3), 286.
24. Fu, Q., Zhang, L. W., Hong, J. C., & Dong, Y. (2021). Development and verification of the programming resilience scale for university students. Australasian Journal of Educational Technology, 37(6), 141-155. https://doi.org/10.14742/ajet.6833
25. Garmezy N (1991) Resilience and vulnerability to adverse developmental outcomes associated with poverty. American behavioral scientist, 34(4), 416:430.
26. Hines, A. M., Merdinger, J., & Wyatt, P. (2005). Former foster youth attending college: Resilience and the transition to young adulthood. American Journal of Orthopsychiatry, 75(3), 381-394.
27. Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1).
28. Howard, S., & Johnson, B. (2000). What makes the difference? Children and teachers talk about resilient outcomes for children “at risk.” Educational Studies, 26(3), 321–337.
29. Hu, L.T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55.
30. Hunter A. J. (2001). A cross-cultural comparison of resilience in adolescents. Journal of Pediatric Nursing, 16(3), 172-179
31. Jiau, H. C., Chen, J. C., & Ssu, K. F. (2009). Enhancing self-motivation in learning programming using gamebased simulation and metrics. IEEE Transactions on Education, 52(4), 555-562. https://doi.org/10.1109/TE.2008.2010983
32. Karaırmak, Ö. (2006). Psikolojik sağlamlık, risk faktörleri ve koruyucu faktörler. Türk Psikolojik Danışma ve Rehberlik Dergisi, 3(26), 129-138.
33. Kaner, S., Bayraklı, H., & Güzeller, C.O. (2011). Anne-babaların yılmazlık algılarının bazı değişkenler açısından incelenmesi. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Özel Eğitim Dergisi, 12(2) 63-78.
34. Kelloway, K. E. (1998). Using Lisel for structural equation modeling: A researcher' s guide. Sage Publications.
35. Kline, T. J. (2005). Psychological testing: A practical approach to design and evaluation. Sage Publications.
36. Kooken, J., Welsh, M. E., McCoach, D. B., Johnston-Wilder, S., & Lee, C. (2016). Development and validation of the mathematical resilience scale. Measurement and Evaluation in Counseling and Development, 49(3), 217-242. https://doi.org/10.1177/0748175615596782
37. Kuusinen, K. (2016, August). Are software developers just users of development tools? Assessing developer experience of a graphical user interface designer. Sözel Bildiri, 6th International Conference on Human-Centered Software Engineering HCSE 2016, Stockholm, Sweden.
38. Lahtinen, E., Ala-Mutka, K., & Järvinen, H. M. (2005). A study of the difficulties of novice programmers. Acm Sigcse Bulletin, 37(3), 14-18.
39. Law, K. M. Y., Lee, V. C. S., & Yu, Y. T. (2010). Learning motivation in e-Learning facilitated computer programming courses. Computers & Education, 55(1), 218-228.
40. Licorish, S. A., & MacDonell, S. G. (2017). Exploring software developers’ work practices: Task differences, participation, engagement, and speed of task resolution. Information & Management, 54(3), 364-382.
41. Linn, M. C., & Dalbey, J. (1989). Cognitive consequences of programming instruction. In E. Wiedenbeck & J. C. Spohrer (Eds.), Studying the novice programmer (pp. 57–81). Lawrence Erlbaum.
42. Luthar, S. S. (2006). Resilience in development: A synthesis of research across five decades. In C. Dante & J. C. Donald (Eds.), Developmental psychopathology (pp.739-795). John Wiley & Sons. https://doi.org/10.1002/9780470939406.ch20
43. Martin, A. J., & Marsh, H. W. (2006). Academic resilience and its psychological and educational correlates: A construct validity approach. Psychology in the Schools, 43(3), 267-281.
44. Martin, A. J., & Marsh, H.W. (2009). Academic resilience and academic buoyancy: Multidimensional and hierarchical conceptual framing of causes, correlates and cognate constructs. Oxford Review of Education, 35(3), 353–370.
45. Maruyama, G. M. (1998). Basics of structural equation modeling (First Edition). Sage Publications.
46. OECD (2013). PISA 2012 results: Excellence through equity: Giving every student the chance to succeed (Volume II). OECD Publishing. http://dx.doi.org/10.1787/19963777
47. Özcan, B. (2005). Annebabaları boşanmış ve annebabaları birlikte olan lise öğrencilerinin yılmazlık özellikleri ve koruyucu faktörler açısından karşılaştırılması. [Yüksek lisans tezi. Ankara Üniversitesi].
48. Rebuta, K. M. N., Cabaron, I. M. P., Pucong, R. J. C., Bisquera, J. M. C., Llerado, R. T., & Buladaco, M. V. M. (2022). Relationship of programming skills and perceived value of learning programming among information technology education students in Davao Del Sur. International Journal of Research and Innovation in Social Science, 6(6), 882-887.
49. Robins, A. V. (2019). 12 Novice programmers and introductory programming. The Cambridge handbook of computing education research, 327-376.
50. Robins, A., Rountree, J., & Rountree, N. (2003). Learning and teaching programming: A review and discussion. Computer science education, 13(2), 137-172. DOI: 10.1076/csed.13.2.137.14200
51. Schumacker, R. E., & Lomax, R. G. (1996). A beginner’s guide to structural equation modeling. Lawrence Erlbaum Associates Publishers.
52. Schunk, D. H., & Pajares, F. (2005). Competence perceptions and academic functioning. In A. J. Elliot & C. S. Dweck (Eds.), Handbook of competence and motivation (85-104). Guilford Press.
53. Steiger, J. H. (2007). Understanding the limitations of global fit assessment in structural equation modeling. Personality and Individual Differences, 42(5), 893-898.
54. Stump, G., Husman, J., Chung, W. T., & Done, A. (2009, October). Student beliefs about intelligence: Relationship to learning. 2009 39th IEEE Frontiers in Education Conference (pp. 1-6), San Antonio, TX, USA.
55. Sümer, N. (2000). Yapısal eşitlik modelleri: Temel kavramlar ve örnek uygulamalar. Türk Psikoloji Yazıları, 3(6), 4974.
56. Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Allyn & Bacon.
57. Terzi, Ş. (2008). Üniversite öğrencilerinde kendini toparlama gücünün içsel koruyucu faktörlerle ilişkisi. Hacettepe Üniversite Eğitim Fakültesi Dergisi, 35, 297-306.
58. Trigueros, R., Magaz-González, A. M., García-Tascón, M., Alias, A., & Aguilar-Parra, J. M. (2020). Validation and adaptation of the academic-resilience scale in the Spanish context. International Journal of Environmental Research and Public Health, 17(11), 1-11. https://doi.org/10.3390/ijerph17113779
59. Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. American Psychological Association.
60. Tusaie, K., & Dyer, J. (2004). Resilience: A historical review of the construct. Holist Nursing Practice, 18, 3-8.
61. Wagnild, G. M., & Young, H. M. (1993). Development and psychometric evaluation of the resilience scale. J Nurs Meas, 1,165-178.
62. Wang, M. C., Haertel, G. D., & Walberg, H. J. (1994). Educational resilience in inner cities. In M. C. Wang & E. W. Gordon (Eds.), Educational resilience in inner-city America: Challenges and prospects (pp. 45-72). Lawrence Erlbaum.
63. Weinstein, C. E., Husman, J., & Dierking, D. R. (2000). Self-regulation interventions with a focus on learning strategies. Handbook of self-regulation, pp. 727-747.
64. Wigfield, A. (1994). Expectancy-value theory of achievement motivation: A developmental perspective. Educational Psychology Review, 6(1), 49-78.
65. Winslow, L.E. (1996). Programming pedagogy – A psychological overview. SIGCSE Bulletin, 28, 17–22.
66. Volman, M., Van Eck, E., Heemskerk, I., & Kuiper, E. (2005). New technologies, new differences. Gender and ethnic differences in pupils' use of ICT in primary and secondary education. Computers & Education, 45(1), 35-55.
67. Vermetten, Y. J., Lodewijks, H. G., & Vermunt, J. D. (2001). The role of personality traits and goal orientations in strategy use. Contemporary Educational Psychology, 26(2), 149-170.
68. von Mayrhauser, A., & Vans, A.M. (1994). Program understanding – A survey (Tech. Rep. CS-94-120). Colorado State University.
69. Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist, 47(4), 302-314. https://doi.org/10.1080/00461520.2012.722805
70. Zhen, R., Liu, R. D., Wang, M. T., Ding, Y., Jiang, R., Fu, X., & Sun, Y. (2020). Trajectory patterns of academic engagement among elementary school students: The implicit theory of intelligence and academic self-efficacy matters. British Journal of Educational Psychology, 90(3), 618-634. https://doi.org/10.1111/bjep.12320