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Kariyer Planlama Yetkinliği: Ölçek Geliştirme Çalışması

Year 2025, Volume: 27 Issue: 3, 454 - 466, 30.09.2025
https://doi.org/10.17556/erziefd.1657526

Abstract

Üniversite eğitimi öncesi öğrencilerin kariyer planlama yeterlilik düzeyi ve bu yeterliliğin altında yatan psikolojik mekanizmaların anlaşılması öğrencilere sunulacak kariyer danışmanlığı noktasında kritik rol oynayabilir. Bu amaçla lise öğrencilerinin kariyer planlama yetkinliğini belirlemeye yönelik geçerli ve güvenilir bir ölçek geliştirilmesi hedeflenmiştir. Karma araştırma yöntemine uygun olarak tasarlanan araştırmada 790 lise öğrencisine ulaşılmıştır. Ayrıca mülakatlar 12, test tekrar-test işlemleri için 130 öğrenci araştırmaya dahil edilmiştir. Veriler Bilgi Toplama Formu, Kariyer Planlama Yetkinliği Ölçeği, Kariyer Kararı Öz-Yeterliliği Ölçeği ve Bilişsel Esneklik Ölçeği ile toplanmıştır. Ölçeğin psikometrik özelliklerinin belirlenmesi için kapsam geçerliliği, yapı geçerliliği ve güvenilirlik analizleri yapılmıştır. Analizler SPPS ve Mplus programları ile yapılmıştır. AFA sonucunda toplam varyansın %55,90’ını açıklayan, 12 maddelik ve dört boyuttan oluşan yapı elde edilmiştir. Dört boyutlu yapı DFA ile doğrulanmış ve ölçek yapısın literatürde işaret edilen mükemmel uyum iyiliği değerlerine sahip olduğu tespit edilmiştir. Kariyer kararı öz-yeterliliği ve bilişsel esneklik arasındaki ilişkiler ölçüt geçerliliğinin sağlandığı işaret etmektedir. Ölçümlerin güvenirliği Cronbach Alfa ve test tekrar test yöntemleri ile araştırılmıştır. Sonuçlar güvenirlik katsayılarının kabul edilebilir olduğunu göstermiştir. %27’lik alt-üst grup karşılaştırmaları ölçek maddelerinin ayırt edici olduğunu göstermiştir. Araştırma sonucunda Kariyer Planlama Yetkinliği Ölçeği’nin geçerli ve güvenilir ölçme aracı olduğu ve öğrencilere sunulacak kariyer danışmanlığı hizmetinin yönünü belirleme amacıyla kullanılabileceği anlaşılmaktadır.

Ethical Statement

Bu çalışma Ordu Üniversitesi Sosyal ve Beşeri Bilimler Araştırmaları Etik Kurulunda 30.03.2023 sayı 2023/68 toplantısında alınan onay kararı ile yürütülmüştür. Bu çalışmanın ilk verileri 10. Uluslararası Eğitim Araştırmaları Kongresinde (EJER) bildiri olarak sunulmuştur.

References

  • Aytekin, E., & Isiksal-Bostan, M. (2018). Middle school students’ attitudes towards the use of technology in mathematics lessons: does gender make a difference? International Journal of Mathematical Education in Science and Technology, 50(5), 707–727. https://doi.org/10.1080/0020739X.2018.1535097
  • Bento Miguens, A. L., Nunes Piedade, J. M., Dos Santos, R. J. B., & Oliva, T. L. (2024). Meaningful learning in mathematics: A study on motivation for learning and development of computational thinking using educational robotics. Educational Media International, 61(1–2), 4–15. https://doi.org/10.1080/09523987.2024.2357472
  • Büyüköztürk, Ş. (2018). Bilimsel araştırma yöntemleri (25. Ed.). Pegem Akademi.
  • Bourdeau, J., & Balacheff, N. (2014). Technology-enhanced learning: From thesaurus and dictionary to ontology. In J. Jovanović & R. Chiong (Eds.), Technological and social environments for interactive learning (pp. 1–33). Informing Science.
  • Clark-Wilson, A., Robutti, O., & Thomas, M. (2020). Teaching with digital technology. ZDM Mathematics Education, 52, 1223–1242. https://doi.org/10.1007/s11858-020-01196-0
  • Cullen, C. J., Hertel, J. T., & Nickels, M. (2020). The Roles of Technology in Mathematics Education. The Educational Forum, 84(2), 166–178. https://doi.org/10.1080/00131725.2020.1698683
  • Downes, S. (2014). From technology enhanced learning to technology enhanced learner. In R. Huang, Kinshuk, & N. Chen (Eds.), The new development of technology-enhanced learning: Concept, research, & best practices (pp. v-vii). Springer. https://doi.org/10.1007/978-3-642-32301-0
  • Drijvers, P. (2015). Digital technology in mathematics education: Why it works (or doesn’t). In S. Cho (Ed.), Selected regular lectures from the 12th International Congress on Mathematical Education (pp. 95–104). Springer. https://doi.org/10.1007/978-3-319-17187-6_8
  • Drijvers, P., & Sinclair, N. (2024) The role of digital technologies in mathematics education: purposes and perspectives. ZDM Mathematics Education 56, 239–248. https://doi.org/10.1007/s11858-023-01535-x
  • Goodyear, P., & Retalis, S. (2010). Learning, technology and design. In P. Goodyear & S. Retalis (Eds.), Technology-enhanced learning: Design patterns and pattern languages (pp. 1–27). Sense Publishers. https://brill.com/display/book/9789460910623/BP000002.xml
  • Hacıömeroğlu, G. (2017). Reliability and Validity Study of the Attitude towards Mathematics Instruments Short Form. Journal of Computer and Education Research, 5(9), 84-99. https://doi.org/10.18009/jcer.67962
  • Hidayat, A., & Firmanti, P. (2024). Navigating the tech frontier: a systematic review of technology integration in mathematics education. Cogent Education, 11(1), 1-15. https://doi.org/10.1080/2331186X.2024.2373559
  • Higgins, K., Huscroft-D'Angelo, J., & Crawford, L. (2017). Effects of technology in mathematics on achievement, motivation, and attitude: A meta-analysis. Journal of Educational Computing Research, 57(2), 283-319. https://doi.org/10.1177/0735633117748416
  • Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020). The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education, 153, 103897. https://doi.org/10.1016/j.compedu.2020.103897
  • Hourigan, M., Leavy, A. M., & Carroll, C. (2016). ‘Come in with an open mind’: changing attitudes towards mathematics in primary teacher education. Educational Research, 58(3), 319–346. https://doi.org/10.1080/00131881.2016.1200340
  • Kavaz, S., & Kocak, O. (2024). The Effect of the Online Flipped Learning Model on Secondary School Students’ Academic Achievement, Attitudes Towards Their Mathematics Course, and Cognitive Load. Int J of Sci and Math Educ 22, 1709–1737. https://doi.org/10.1007/s10763-024-10455-5
  • Kaya, E., & İzci, E. (2024). Attitude Scale for Science Course: A study of Validity and Reliability. Journal of History School, 69, 1082-1099. https://doi.org/10.29228/Joh.74280
  • Kirkwood, A., & Price, L. (2013). Technology-enhanced learning and teaching in higher education: What is ‘enhanced’ and how do we know? A critical literature review. Learning, Media and Technology, 39(1), 6–36. https://doi.org/10.1080/17439884.2013.770404
  • Law, N., Niederhauser, D. S., Shear, L., & Christensen, R. W. (2015). Indicators of quality technology-enhanced learning and teaching. In K. W. Lai (Ed.), Technology advanced quality learning for all: EDUsummIT 2015 summary report (pp. 49–55). University of Otago College of Education.
  • Li, M., Vale, C., Tan, H., & Blannin, J. (2025). Factors influencing the use of digital technologies in primary mathematics teaching: Voices from Chinese educators. Educ Inf Technol, 30, 12573-12608. https://doi.org/10.1007/s10639-024-13309-3
  • Lim, S.Y., & Chapman, E. (2013). Development of a short form of the attitudes toward mathematics inventory. Educ Stud Math, 82, 145–164. https://doi.org/10.1007/s10649-012-9414-x
  • Ministry of National Education. (2018). Mathematics Curriculum (Elementary and Middle School Grades 1-8). Ministry of National Education.
  • National Council of Teachers of Mathematics. (2014). Principles to actions: Ensuring mathematical success for all. National Council of Teachers of Mathematics.
  • OECD. (2020). PISA 2018 results (Volume V): Effective policies, successful schools, PISA, OECD Publishing, Paris, https://doi.org/10.1787/ca768d40-en
  • Peng, H., Ma, S., & Spector, J. M. (2019). Personalized adaptive learning: An emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6(9), 1-14. https://doi.org/10.1186/s40561-019-0089-y
  • Pierce, R., & Ball, L. (2009). Perceptions that may affect teachers' intention to use technology in secondary mathematics classes. Educational Studies in Mathematics, 71(3), 299-317. https://doi.org/10.1007/s10649-008-9177-6
  • Pittalis, M., & Drijvers, P. (2023). Embodied instrumentation in a dynamic geometry environment: eleven-year-old students’ dragging schemes. Educ Stud Math 113, 181–205. https://doi.org/10.1007/s10649-023-10222-3
  • Reed, H.C., Drijvers, P., & Kirschner, P. A. (2010). Effects of attitudes and behaviours on learning mathematics with computer tools. Computers & Education, 55(1), 1-15. https://doi.org/10.1016/j.compedu.2009.11.012
  • Taylor, D. L., Yeung, M., & Bashet, A. Z. (2021). Personalized and adaptive learning. In J. Ryoo & K. Winkelmann (Eds.), Innovative learning environments in STEM higher education (pp. 17–34). Springer Briefs in Statistics. Springer. https://doi.org/10.1007/978-3-030-58948-6_2
  • Viberg, O., & Mavroudi, A. (2018). The role of ubiquitous computing and the Internet of Things for developing 21st-century skills among learners: Experts’ views. In V. Pammer-Schindler, M. Pérez-Sanagustín, H. Drachsler, R. Elferink, & M. Scheffel (Eds.), Lifelong technology-enhanced learning (pp. 640–643). Lecture Notes in Computer Science, 11082. Springer.https://doi.org/10.1007/978-3-319-98572-5_63
  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4
  • Weiss, I., Kramarski, B., & Talis, S. (2006). Effects of multimedia environments on kindergarten children’s mathematical achievements and style of learning. Educational Media International, 43(1), 3–17. https://doi.org/10.1080/09523980500490513
  • Young, J. (2017). Technology-enhanced mathematics instruction: A second-order meta-analysis of 30 years of research. Educational Research Review, 22, 19–33. https://doi.org/10.1016/j.edurev.2017.07.001

Career Planning Competency: A Scale Development Study

Year 2025, Volume: 27 Issue: 3, 454 - 466, 30.09.2025
https://doi.org/10.17556/erziefd.1657526

Abstract

The understanding of the career planning competency level of students prior to university education and the underlying psychological mechanisms plays a critical role in the career counselling to be provided to these students. This study aimed to develop a valid and reliable scale to determine the career planning competency of high school students. In accordance with the mixed method research design, 790 high school students were reached. In addition, interviews were conducted with 12 students, and 130 students were included in the research for test-retest procedures. The data were collected using the Information Form, Career Planning Competency Scale, Career Decision Self-Efficacy Scale, and Cognitive Flexibility Scale. For the determination of the psychometric properties of the scale, content validity, construct validity, and the reliability analyses were conducted. The analyses were performed using SPSS and Mplus programs. As a result of the EFA, a 12-item structure consisting of four dimensions, explaining 55.90% of the total variance, was obtained. The four-dimensional structure was confirmed by CFA, and it was determined that the scale structure had excellent goodness-of-fit values indicated in the literature. The relationship between career decision self-efficacy and cognitive flexibility indicate that criterion validity was achieved. The reliability of the measurements was investigated with Cronbach's Alpha and test-retest methods. The results showed that the reliability coefficients were acceptable. The 27% lower and upper group comparisons showed that the scale items were discriminating. According to the results, it is understood that the Career Planning Competency Scale is a valid and reliable measurement tool and can be used to determine the direction of career counselling services to be provided to students.

References

  • Aytekin, E., & Isiksal-Bostan, M. (2018). Middle school students’ attitudes towards the use of technology in mathematics lessons: does gender make a difference? International Journal of Mathematical Education in Science and Technology, 50(5), 707–727. https://doi.org/10.1080/0020739X.2018.1535097
  • Bento Miguens, A. L., Nunes Piedade, J. M., Dos Santos, R. J. B., & Oliva, T. L. (2024). Meaningful learning in mathematics: A study on motivation for learning and development of computational thinking using educational robotics. Educational Media International, 61(1–2), 4–15. https://doi.org/10.1080/09523987.2024.2357472
  • Büyüköztürk, Ş. (2018). Bilimsel araştırma yöntemleri (25. Ed.). Pegem Akademi.
  • Bourdeau, J., & Balacheff, N. (2014). Technology-enhanced learning: From thesaurus and dictionary to ontology. In J. Jovanović & R. Chiong (Eds.), Technological and social environments for interactive learning (pp. 1–33). Informing Science.
  • Clark-Wilson, A., Robutti, O., & Thomas, M. (2020). Teaching with digital technology. ZDM Mathematics Education, 52, 1223–1242. https://doi.org/10.1007/s11858-020-01196-0
  • Cullen, C. J., Hertel, J. T., & Nickels, M. (2020). The Roles of Technology in Mathematics Education. The Educational Forum, 84(2), 166–178. https://doi.org/10.1080/00131725.2020.1698683
  • Downes, S. (2014). From technology enhanced learning to technology enhanced learner. In R. Huang, Kinshuk, & N. Chen (Eds.), The new development of technology-enhanced learning: Concept, research, & best practices (pp. v-vii). Springer. https://doi.org/10.1007/978-3-642-32301-0
  • Drijvers, P. (2015). Digital technology in mathematics education: Why it works (or doesn’t). In S. Cho (Ed.), Selected regular lectures from the 12th International Congress on Mathematical Education (pp. 95–104). Springer. https://doi.org/10.1007/978-3-319-17187-6_8
  • Drijvers, P., & Sinclair, N. (2024) The role of digital technologies in mathematics education: purposes and perspectives. ZDM Mathematics Education 56, 239–248. https://doi.org/10.1007/s11858-023-01535-x
  • Goodyear, P., & Retalis, S. (2010). Learning, technology and design. In P. Goodyear & S. Retalis (Eds.), Technology-enhanced learning: Design patterns and pattern languages (pp. 1–27). Sense Publishers. https://brill.com/display/book/9789460910623/BP000002.xml
  • Hacıömeroğlu, G. (2017). Reliability and Validity Study of the Attitude towards Mathematics Instruments Short Form. Journal of Computer and Education Research, 5(9), 84-99. https://doi.org/10.18009/jcer.67962
  • Hidayat, A., & Firmanti, P. (2024). Navigating the tech frontier: a systematic review of technology integration in mathematics education. Cogent Education, 11(1), 1-15. https://doi.org/10.1080/2331186X.2024.2373559
  • Higgins, K., Huscroft-D'Angelo, J., & Crawford, L. (2017). Effects of technology in mathematics on achievement, motivation, and attitude: A meta-analysis. Journal of Educational Computing Research, 57(2), 283-319. https://doi.org/10.1177/0735633117748416
  • Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020). The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education, 153, 103897. https://doi.org/10.1016/j.compedu.2020.103897
  • Hourigan, M., Leavy, A. M., & Carroll, C. (2016). ‘Come in with an open mind’: changing attitudes towards mathematics in primary teacher education. Educational Research, 58(3), 319–346. https://doi.org/10.1080/00131881.2016.1200340
  • Kavaz, S., & Kocak, O. (2024). The Effect of the Online Flipped Learning Model on Secondary School Students’ Academic Achievement, Attitudes Towards Their Mathematics Course, and Cognitive Load. Int J of Sci and Math Educ 22, 1709–1737. https://doi.org/10.1007/s10763-024-10455-5
  • Kaya, E., & İzci, E. (2024). Attitude Scale for Science Course: A study of Validity and Reliability. Journal of History School, 69, 1082-1099. https://doi.org/10.29228/Joh.74280
  • Kirkwood, A., & Price, L. (2013). Technology-enhanced learning and teaching in higher education: What is ‘enhanced’ and how do we know? A critical literature review. Learning, Media and Technology, 39(1), 6–36. https://doi.org/10.1080/17439884.2013.770404
  • Law, N., Niederhauser, D. S., Shear, L., & Christensen, R. W. (2015). Indicators of quality technology-enhanced learning and teaching. In K. W. Lai (Ed.), Technology advanced quality learning for all: EDUsummIT 2015 summary report (pp. 49–55). University of Otago College of Education.
  • Li, M., Vale, C., Tan, H., & Blannin, J. (2025). Factors influencing the use of digital technologies in primary mathematics teaching: Voices from Chinese educators. Educ Inf Technol, 30, 12573-12608. https://doi.org/10.1007/s10639-024-13309-3
  • Lim, S.Y., & Chapman, E. (2013). Development of a short form of the attitudes toward mathematics inventory. Educ Stud Math, 82, 145–164. https://doi.org/10.1007/s10649-012-9414-x
  • Ministry of National Education. (2018). Mathematics Curriculum (Elementary and Middle School Grades 1-8). Ministry of National Education.
  • National Council of Teachers of Mathematics. (2014). Principles to actions: Ensuring mathematical success for all. National Council of Teachers of Mathematics.
  • OECD. (2020). PISA 2018 results (Volume V): Effective policies, successful schools, PISA, OECD Publishing, Paris, https://doi.org/10.1787/ca768d40-en
  • Peng, H., Ma, S., & Spector, J. M. (2019). Personalized adaptive learning: An emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6(9), 1-14. https://doi.org/10.1186/s40561-019-0089-y
  • Pierce, R., & Ball, L. (2009). Perceptions that may affect teachers' intention to use technology in secondary mathematics classes. Educational Studies in Mathematics, 71(3), 299-317. https://doi.org/10.1007/s10649-008-9177-6
  • Pittalis, M., & Drijvers, P. (2023). Embodied instrumentation in a dynamic geometry environment: eleven-year-old students’ dragging schemes. Educ Stud Math 113, 181–205. https://doi.org/10.1007/s10649-023-10222-3
  • Reed, H.C., Drijvers, P., & Kirschner, P. A. (2010). Effects of attitudes and behaviours on learning mathematics with computer tools. Computers & Education, 55(1), 1-15. https://doi.org/10.1016/j.compedu.2009.11.012
  • Taylor, D. L., Yeung, M., & Bashet, A. Z. (2021). Personalized and adaptive learning. In J. Ryoo & K. Winkelmann (Eds.), Innovative learning environments in STEM higher education (pp. 17–34). Springer Briefs in Statistics. Springer. https://doi.org/10.1007/978-3-030-58948-6_2
  • Viberg, O., & Mavroudi, A. (2018). The role of ubiquitous computing and the Internet of Things for developing 21st-century skills among learners: Experts’ views. In V. Pammer-Schindler, M. Pérez-Sanagustín, H. Drachsler, R. Elferink, & M. Scheffel (Eds.), Lifelong technology-enhanced learning (pp. 640–643). Lecture Notes in Computer Science, 11082. Springer.https://doi.org/10.1007/978-3-319-98572-5_63
  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4
  • Weiss, I., Kramarski, B., & Talis, S. (2006). Effects of multimedia environments on kindergarten children’s mathematical achievements and style of learning. Educational Media International, 43(1), 3–17. https://doi.org/10.1080/09523980500490513
  • Young, J. (2017). Technology-enhanced mathematics instruction: A second-order meta-analysis of 30 years of research. Educational Research Review, 22, 19–33. https://doi.org/10.1016/j.edurev.2017.07.001
There are 33 citations in total.

Details

Primary Language Turkish
Subjects Career Counseling
Journal Section In This Issue
Authors

Şenel Çıtak 0000-0003-1155-1767

Sezer Bulut 0000-0002-9576-979X

Publication Date September 30, 2025
Submission Date March 14, 2025
Acceptance Date August 22, 2025
Published in Issue Year 2025 Volume: 27 Issue: 3

Cite

APA Çıtak, Ş., & Bulut, S. (2025). Kariyer Planlama Yetkinliği: Ölçek Geliştirme Çalışması. Erzincan Üniversitesi Eğitim Fakültesi Dergisi, 27(3), 454-466. https://doi.org/10.17556/erziefd.1657526