STEM Kariyeri ve Tutumları Konusundaki Araştırmalarda Uluslararası İşbirliklerine Genel Bakış

Year 2024, Volume: 7 Issue: 2, 129 - 148, 04.06.2024

Ülke Balcı Yeşilkaya , İlker Yeşilkaya , Salih Çepni , Salih Tutun

Abstract

STEM alanlarının öneminin artmasıyla birlikte her geçen gün STEM mesleklerine yönelik ihtiyaç da artmaktadır. Bu durum STEM alanlarına yönelik çalışmaların incelenmesini gerekli kılmaktadır. Bu amaçla çalışmada, STEM meslekleri ve STEM’ e yönelik tutum üzerine çalışan araştırmacılar arasında kurulan ortak yazarlık ilişkileri bir sosyal ağ oluşturarak incelenmiştir. 1983-2023 yılları arasında Web of Science Core Collection veri tabanında “STEM Career” (STEM Kariyeri), “STEM Jobs” (STEM İşleri), “STEM Occupation” (STEM Meslekleri), “STEM Vocation” (STEM Meslekleri) ile “STEM Attitude” (STEM Tutumları) kelimelerini barındıran sorgu sonucunda 6371 adet yayına ulaşılmıştır. Çalışmamızda, ortak yazarlık ağında yer alan 10989 yazar, 237 üniversite ve 121 ülke arasında kurulan ilişkiler modellenmiştir. Ağdaki yazarlar arasındaki iş birlikleri sonucunda Louvain algoritması ile öne çıkan topluluklar bulunmuştur. Gephi yazılımı kullanılarak ağırlıklı derece merkeziliği, yakınlık derece merkeziliği ve arasındalık derece merkeziliği gibi diğer ağ metrikleri hesaplanmış ve görselleştirilmiştir. Analiz sonucunda elde edilen bulgular, sosyal ağdaki bilimsel iş birliklerinin karakteristik örüntülerini, alanda öne çıkan yazarları, üniversiteleri ve ülkeleri ortaya çıkarılmıştır. Çalışmamız sonucunda elde ettiğimiz grafik yoğunluğu değerlerinin yıllara göre dağılım sonuçları, STEM meslekleri ve kariyerleri alanında yapılan çalışmalarda yazarlar, üniversiteler ve ülkeler bazında akademik iş birliği sayısının arttığını göstermiştir. Ülkeler arası iş birlikleri incelendiğinde ilk 10 sırada yer alan ülkeler ABD, İngiltere, Avusturalya ve Kanada iken sıralamada önde gelen üniversitelerin University of Washington, Vanderbilt University, Purdue Universtity ve University of Colorado olduğu görülmektedir. Bu durum ABD nin STEM alanında lider ülke konumunda olduğunu göstermektedir. Yazarlar arası iş birliklerinde 2010 yılı itibariyle artış görülmekle beraber ülkeler arası iş birliklerinde 2016 yılından itibaren dikkat çekici artış gözlemlenmiştir.

Keywords

STEM tutumu, STEM Kariyeri, STEM Meslekleri, Sosyal Ağ Analizi

Overview of International Collaborations in Research on STEM Careers and Attitudes

Abstract

By the increasing importance of STEM fields, the need for STEM professions is increasing day by day. This situation makes it necessary to examine the studies on STEM fields. For this purpose, the study examined the co-authorship relationships between researchers working on STEM professions and attitudes towards STEM by creating a social network. In the Web of Science Core Collection database between 1983-2023, 6371 publications were reached as a result of the query containing the words “STEM Career”, “STEM Jobs”, “STEM Occupation”, “STEM Vocation” and “STEM Attitude”. In our study, the relationships between 10989 authors, 237 universities and 121 countries in the co-authorship network were modeled. As a result of the collaborations between authors in the network, prominent communities were found with the Louvain algorithm. The findings of the analysis reveal the characteristic patterns of scientific collaborations in the social network, the prominent authors, universities and countries in the field. As a result of our study, when the collaborations between countries are analyzed, it is seen that the top 10 countries are the USA, the UK, Australia and Canada, while the leading universities in the ranking are University of Washington, Vanderbilt University, Purdue Universtity and University of Colorado. Although there has been an increase in collaborations between authors since 2010, a remarkable increase has been observed in collaborations between countries since 2016.

Keywords

: STEM career, STEM Attitude, STEM Jobs, Social Network Analyses

References

• Abbate, S., Centobelli, P., Cerchione, R., Nadeem, S.P., Riccio, E. (2023) Sustainability trends and gaps in the textile, apparel and fashion ındustries. environment, Development and Sustainability. https://doi.org/10.1007/s10668-022-02887-2.https://doi.org/10.1007/s10668-022-02887-2.
• Acedo, F. J., Barroso, C., Casanueva, C., & Galán, J. L. (2006). Co‐authorship in management and organizational studies: An empirical and network analysis. Journal of management studies, 43(5), 957-983.
• Aung, T. T., & Nyunt, T. T. S. (2020). Modularity based ABC algorithm for detecting communities in complex networks. International Journal of Machine Learning and Computing, 10(2).
• Agung, I. D. G., Suardana, I. N., & Rapi, N. K. (2022). E-modul IPA dengan model STEM-PjBL berorientasi pendidikan karakter untuk meningkatkan hasil belajar siswa. Jurnal Ilmiah Pendidikan Dan Pembelajaran, 6(1), 120-133.
• Babarović, T., Dević, I., & Burušić, J. (2019). Fitting the STEM interests of middle school children into the RIASEC structural space. International Journal for Educational and Vocational Guidance, 19, 111-128.
• Bastian, M., Heymann, S., & Jacomy, M. (2009, March). Gephi: an open source software for exploring and manipulating networks. In Proceedings of the international AAAI conference on web and social media (Vol. 3, No. 1, pp. 361-362).
• Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment, 2008(10), P10008.
• Bordons, M., Aparicio, J., González-Albo, B., & Díaz-Faes, A. A. (2015). The relationship between the research performance of scientists and their position in co-authorship networks in three fields. Journal of informetrics, 9(1), 135-144.
• Chen, Y., So, W. W. M., Zhu, J., & Chiu, S. W. K. (2024). STEM learning opportunities and career aspirations: the interactive effect of students’ self-concept and perceptions of STEM professionals. International Journal of STEM Education, 11(1), 1.
• Cherven, K. (2013). Network graph analysis and visualization with Gephi (Vol. 24). Birmingham: Packt Publishing.
• Clarke, M. A., Sharma, N. M., & Schiller, A. M. (2019). An outreach program with hands-on, physiology-based exercises generates questions about STEM career expectations. Advances in physiology education, 43(2), 175-179.
• Cowhitt, T., Butler, T., & Wilson, E. (2020). Using social network analysis to complete literature reviews: a new systematic approach for independent researchers to detect and interpret prominent research programs within large collections of relevant literature. International Journal of Social Research Methodology, 23(5), 483-496.
• Dou, R., & Cian, H. (2022). Constructing STEM identity: An expanded structural model for STEM identity research. Journal of Research in Science Teaching, 59(3), 458-490.
• Fayer, S., Lacey, A., & Watson, A. (2017). STEM occupations: Past, present, and future. Spotlight on Statistics, 1, 1-35.
• Freeman, L. (2004). The development of social network analysis. A study in the sociology of science, 1(687), 159-167.
• Gazni, A., & Didegah, F. (2016). The relationship between authors’ bibliographic coupling and citation exchange: analyzing disciplinary differences. Scientometrics, 107, 609-626.
• Gil-Doménech, D., Berbegal-Mirabent, J., & Merigó, J. M. (2020). STEM education: A bibliometric overview. In Modelling and Simulation in Management Sciences: Proceedings of the International Conference on Modelling and Simulation in Management Sciences (MS-18) (pp. 193-205). Springer International Publishing.
• Göktepe Körpeoğlu, S., & Göktepe Yıldız, S. (2022). Comparative analysis of algorithms with data mining methods for examining attitudes towards STEM fields. Education and Information Technologies, 1-36.
• Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods.
• Heinze, T., & Kuhlmann, S. (2008). Across institutional boundaries?: Research collaboration in German public sector nanoscience. Research policy, 37(5), 888-899.
• Heymann, S., & Le Grand, B. (2013, July). Visual analysis of complex networks for business intelligence with gephi. In 2013 17th International Conference on Information Visualisation (pp. 307-312). IEEE.
• Hiğde, E., & Aktamış, H. (2022). The effects of STEM activities on students’ STEM career interests, motivation, science process skills, science achievement and views. Thinking Skills and Creativity, 43, 101000.
• Höffler, T. N., Köhler, C., & Parchmann, I. (2019). Scientists of the future: An analysis of talented students’ interests. International Journal of STEM Education, 6, 1-8.
• Huang, B., Jong, M. S. Y., King, R. B., Chai, C. S., & Jiang, M. Y. C. (2022). Promoting secondary Students' twenty-first century skills and STEM career interests through a crossover program of STEM and community service education. Frontiers in Psychology, 13, 903252.
• Ibrahim, Y., & Kamsani, S. R. (2022). Is exploring students’ career interests still a necessity? An overview of the STEM world of work. Internatıonal Journal Of Specıal Educatıon, 37(3s).
• Ji, P., Jin, J., Ke, Z. T., & Li, W. (2022). Co-citation and Co-authorship Networks of Statisticians. Journal of Business & Economic Statistics, 40(2), 469-485.
• Kang, J., Salonen, A., Tolppanen, S., Scheersoi, A., Hense, J., Rannikmäe, M., ... & Keinonen, T. (2021). Effect of embedded careers education in science lessons on students’ interest, awareness, and aspirations. International Journal of Science and Mathematics Education, 1-21.
• Katz, J. S. and Martin, B. R. (1997). ‘What is research collaboration?. Research Policy, 26, 1–18.
• Karahan, E., Kara, A. & Akçay, A.O. Designing and implementing a STEM career maturity program for prospective counselors. IJ STEM Ed 8, 23 (2021). https://doi.org/10.1186/s40594-021-00281-4
• Kayan-Fadlelmula, F., Sellami, A., Abdelkader, N., & Umer, S. (2022). A systematic review of STEM education research in the GCC countries: Trends, gaps and barriers. International Journal of STEM Education, 9, 1-24.
• Kennedy, J., Quinn, F., & Taylor, N. (2016). The school science attitude survey: a new instrument for measuring attitudes towards school science. International Journal of Research & Method in Education, 39(4), 422-445.
• Ketenci, T., Leroux, A., & Renken, M. (2020). Beyond student factors: A study of the impact on STEM career attainment. Journal for STEM Education Research, 3(3), 368-386.
• Lee, S. and Bozeman, B. (2005), “The impact of research collaboration on scientific productivity”, Social studies of Science, Vol. 35 No. 5, pp. 673-702.
• Lu, X., & Ma, C. (2017). Mapping research collaboration network of international methane hydrate research. Procedia computer science, 122, 820-825.
• Makhlouf, J., & Mine, T. (2020). Analysis of click-stream data to predict STEM careers from student usage of an intelligent tutoring system. Journal of Educational Data Mining, 12(2), 1-18.
• Marques, L., & Manzanares, M. D. (2022). Towards social network metrics for supply network circularity. International Journal of Operations & Production Management, 43(4), 595-618.
• Melin, G., & Persson, O. (1996). Studying research collaboration using co-authorships. Scientometrics, 36(3), 363-377.
• Miller, K., Sonnert, G., & Sadler, P. (2018). The influence of students’ participation in STEM competitions on their interest in STEM careers. International Journal of Science Education, Part B, 8(2), 95-114.
• Morel, C. M., Serruya, S. J., Penna, G. O., & Guimarães, R. (2009). Co-authorship network analysis: a powerful tool for strategic planning of research, development and capacity building programs on neglected diseases. PLoS neglected tropical diseases, 3(8), e501.
• M Savić, M Ivanović, M Radovanović, Z Ognjanović, A Pejović, TJ Krüger, " Exploratory analysis of communities in coauthorship networks: a case study", International Conference on ICT Innovations, Springer, 2015, pp. 55-64
• Newman, M. E. (2001). The structure of scientific collaboration networks. Proceedings of the national academy of sciences, 98(2), 404-409.
• Newman, M. E. (2006). Modularity and community structure in networks. Proceedings of the national academy of sciences, 103(23), 8577-8582.
• OECD (2015). The ABS of gender Equality in Education: Aptitude, behavior, confidence, PISA. OECD Publishing https://doi.org/10.1787/9789264229945-en.
• Organisation for Economic Co-operation and Development. (2019). Education at a Glance 2019: OECD indicators. OECD Publishing.
• Okamoto, K., hen, W., & Li, X. Y. (2008). Ranking of closeness centrality for large-scale social networks. Lecture Notes in Computer Science, 5059, 186-195.
• Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social networks, 32(3), 245-251.
• Özcan, H., & Koca, E. (2019). STEM’e yönelik tutum ölçeğinin Türkçeye uyarlanması: Geçerlik ve güvenirlik çalışması. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 34(2), 387-401.
• Palmer, T. A., Burke, P. F., & Aubusson, P. (2017). Why school students choose and reject science: A study of the factors that students consider when selecting subjects. International Journal of Science Education, 39(6), 645-662.
• Plasman, J. S., Gottfried, M., Freeman, J., & Dougherty, S. (2022). Promoting persistence: Can computer science career and technical education courses support educational advancement for students with learning disabilities?. Policy Futures in Education, 14782103211049913.
• Pratiwi, N., Putri, F. A., & Ali, M. (2024). The effect of stem approach in problem-based learning for ıncreasing students' problem-solving ability in the topic of environmental pollution. KnE Social Sciences, 1063-1073.
• Riondato, M., & Kornaropoulos, E. M. (2014, February). Fast approximation of betweenness centrality through sampling. In Proceedings of the 7th ACM international conference on Web search and data mining (pp. 413-422).
• Sahin, A., Waxman, H. C., Demirci, E., & Rangel, V. S. (2020). An investigation of harmony public school students’ college enrollment and STEM major selection rates and perceptions of factors in STEM major selection. International Journal of Science and Mathematics Education, 18(7), 1249-1269.
• Salmela-Aro, K. (2020). The role of motivation and academic wellbeing–The transition from secondary to further education in STEM in Finland. European Review, 28(S1), S121-S134.
• Sithole, A., Chiyaka, E. T., McCarthy, P., Mupinga, D. M., Bucklein, B. K., & Kibirige, J. (2017). Student attraction, persistence and retention in STEM programs: Successes and continuing challenges. Higher Education Studies, 7(1), 46-59.
• Sonnenwald, D. H. (2007). Scientific collaboration. Annu. Rev. Inf. Sci. Technol., 41(1), 643-681.
• Tas, N., & Bolat, Y. İ. (2022). An examination of the studies on stem in education: a bibliometric zapping analysis. International Journal of Technology in Education and Science, 6(3), 477-494.
• Turner, J. R., & Baker, R. (2020). Collaborative research: Techniques for conducting collaborative research from the science of team science (SciTS). Advances in Developing Human Resources, 22(1), 72-86.
• Umadevi, V. (2014, February). Community mining in co-authorship network. In International Conference on Information Communication and Embedded Systems (ICICES2014) (pp. 1-5). IEEE.
• Unfried, A., Faber, M., Stanhope, D. S., & Wiebe, E. (2015). The development and validation of a measure of student attitudes toward science, technology, engineering, and math (S-STEM). Journal of Psychoeducational Assessment, 33(7), 622-639.
• Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications.
• Wasserman, S., & Robins, G. (2005). An introduction to random graphs, dependence graphs, and p*. Models and methods in social network analysis, 27, 148-161.Van der Geer, J., Hanraads, J. A. J., & Lupton R. A. (2000). The art of writing a scientific article. Journal of Scientific Communications, 163, 51-59.
• Villanueva Baselga, S., Marimon Garrido, O., & González Burón, H. (2022). Drama-based activities for STEM education: encouraging scientific aspirations and debunking stereotypes in secondary school students in Spain and the UK. Research in Science Education, 52(1), 173-190.
• Vooren, M., Haelermans, C., Groot, W., & van den Brink, H. M. (2022). Comparing success of female students to their male counterparts in the STEM fields: an empirical analysis from enrollment until graduation using longitudinal register data. International Journal of STEM Education, 9, 1-17.
• Yeşilkaya, Ü. B., Yeşilkaya, İ., Çepni, S. & Tutun, S. (2023). How did academic collaboration occur in research on STEM attitudes and careers? New Trends and Issues Proceedings on Humanities and Social Sciences. 10(1), 40-48.https://doi.org/10.18844/prosoc.v10i1.8841
• Yeşilkaya, Ü. B., Yeşilkaya, İ., Çepni, S. & Tutun, S. (2023). At what age does vocational tendency begin? New Trendsand Issues Proceedings on Humanities and Social Sciences. 10(1), 62-71.https://doi.org/10.18844/prosoc.v10i1.8843
• Zervas, P., Tsitmidelli, A., Sampson, D. G., & Chen, N. S. (2014). Studying research collaboration via co-authorship analysis in the field of TeL: the case of Educational Technology & Society Journal. In 2014 IEEE 14th International Conference on Advanced Learning Technologies (pp. 376-377). IEEE.
• Zhan, Z., Shen, W., Xu, Z., Niu, S., & You, G. (2022). A bibliometric analysis of the global landscape on STEM education (2004-2021): towards global distribution, subject integration, and research trends. Asia Pacific Journal of Innovation and Entrepreneurship, 16(2), 171-203.