Matematik Eğitiminde Ölçme ve Değerlendirme: Bibliyometrik Bir Bakış Açısıyla Alandaki Mevcut Bilimsel Verimlilik, Kavramsal ve Tematik Ağlar ile Eğilimler

Öz

Bu çalışma, Web of Science (WoS) ve Scopus veritabanlarından elde edilen 1663 makalenin bibliyometrik analizi yoluyla Matematik Eğitimi'nde Ölçme ve Değerlendirme (MEÖD) alanındaki güncel bilimsel üretkenliği, kavramsal ve tematik ağları ve eğitim araştırmalarındaki eğilimleri ortaya koymayı amaçlamaktadır. Bulgular, MEÖD alanının 2000'lerden itibaren yayınlarda sürekli bir büyüme gösterdiğini ortaya koymaktadır. Bununla birlikte, MEÖD için uluslararası bir standart henüz oluşturulmamıştır; zira devam eden tartışmalar, tamamen özetleyici yaklaşımlardan kavramsal anlayış, akıl yürütme ve problem çözmeye dayalı daha biçimlendirici yaklaşımlara doğru bir kaymayı yansıtmaktadır. Öğretmen yeterliliklerine ilişkin kavramsal ağlar kritik önem taşımaktadır ve alan, tersine çevrilmiş sınıflar ve yeni dijital yöntemler gibi yenilikçi yaklaşımlara teknolojiyi entegre etmeye odaklanmaktadır. PISA, TIMSS gibi matematiksel okuryazarlık sınavları küresel bir bakış açısı sunarken, MEÖD'de geleneksel değerlendirmeden modern dijital bir bakış açısına geçmeye odaklı yeni bir süreç arayışındadır. Ancak bu tür bir dönüşümün yapay zekâ (YZ) ve diğer dijital teknolojilere yönelik olarak da yeniden yapılandırılması gerekmektedir. MEÖD yayınlarındaki coğrafi dengesizliği gidermek için, gelişmiş ülkeler ile Afrika ve Orta Asya’daki az temsil edilen ülkeler arasında daha yaygın bir iş birliğine ihtiyaç duyulmaktadır.

Anahtar Kelimeler

• Matematik Eğitimi
• Ölçme ve Değerlendirme
• Bibliyometrik
• Kavramsal Eğilimler ve Ağlar

Etik Beyan

As this study is based on a systematic review of data obtained from articles available in open-access sources, it does not require ethics committee approval. Nevertheless, the information and findings presented in the article have been documented in accordance with the principles of honesty and transparency, and scientific integrity and ethical standards have been upheld at every stage of the research.

Assessment and Evaluation in Maths Education: The Current Scientific Productivity, Conceptual and Thematic Networks, and Trends through a Bibliometric Analysis Perspective

Öz

The study aims to reveal the current scientific productivity, conceptual and thematic networks, and trends in educational research on Assessment and Evaluation of Maths Education (AEoME) through a bibliometric analysis of 1663 articles from the Web of Science and Scopus databases. The findings reveal that the AEoME field showed consistent growth in publications from the 2000s onwards. However, an international standard for the AEoME has yet to be established, as ongoing discussions reflect a shift from purely summative to more formative approaches based on conceptual understanding, reasoning, and problem-solving. The conceptual networks on teacher competencies remain crucial, and the field focuses on integrating technology into innovative approaches, such as flipped classrooms and new digital methods. While exams like PISA and TIMSS on mathematical literacy introduce a global perspective, the AEoME are also seeking a new process, shifting from a traditional assessment to a modern digital perspective. However, such a transformation should also be restructured towards artificial intelligence (AI) and further digital technologies. Addressing the geographical gap in AEoME publications requires broader cooperation between developed and underrepresented countries in Africa and Central Asia.

Anahtar Kelimeler

• Maths Education
• Assessment and Evaluation
• Bibliometrics
• Conceptual Networks and Trends

Etik Beyan

Bu çalışma, açık erişim kaynaklarında yer alan makale çalışmalarından elde edilen verilerin sistematik incelenmesine dayalı bir çalışma olduğu için etik kurul izni gerektirmemektedir. Bununla birlikte, makalede sunulan bilgi ve bulgular, dürüstlük ve şeffaflık ilkelerine uygun olarak yazıya geçirilmiş olup, araştırmanın her aşamasında bilimsel bütünlüğe ve etik kurallara riayet edilmiştir.

Kaynakça

1. Anwar, L., Sa’dijah, C., Muzam Roudloh, Y. F., Yerizon, Y., & Maiyastri, M. (2025). Enhancing students’ reasoning skills with GeoGebra-based digital worksheets. Salud, Ciencia y Tecnología, 5, Article 2137. https://doi.org/10.56294/saludcyt20252137
2. Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of informetrics, 11(4), 959-975. http://dx.doi.org/10.1016/j.joi.2017.08.007
3. Bayrak, A., & Aslanci, S. (2022). Realistic mathematics education: A bibliometric analysis. Shanlax International Journal of Education, 10(4), 52–62. DOI: https://doi.org/10.34293/education.v10i4.5174
4. Black, P., & Wiliam, D. (2012). Assessment for learning in the classroom. In J. Gardner (Ed.), Assessment and learning (pp. 11–32). Sage.
5. Blömeke, S., & Delaney, S. (2012). Assessment of teacher knowledge across countries: A review of the state of research. ZDM, 44(3), 223–247. https://doi.org/10.1007/s11858-012-0429-7
6. Boaler, J. (2002). Experiencing school mathematics: Traditional and reform approaches to teaching and their impact on student learning (Rev. and expanded ed.). Lawrence Erlbaum Associates.
7. Boaler, J., & Staples, M. (2008). Creating mathematical futures through an equitable teaching approach: The case of Railside School. Teachers College Record, 110(3), 608–645. https://doi.org/10.1111/j.1467-9620.2008.00863.x
8. Bozkurt, K., & Izci, K. (2020). A desirable but difficult goal: Equitable assessment. Education Research Highlights in Mathematics, Science and Technology, 160, 177.

9. Callingham, R., Pegg, J., & Wright, T. (2009). Changing teachers’ classroom practice through developmental assessment: Constraints, concerns and unintended impacts. Crossing Divides, 81–88.
10. Cerado, E. C. (n.d.). Assessment and evaluation in mathematics. Academia.edu. https://www.academia.edu/45577568/Assessment_and_Evaluation_in_Mathematics. Retrieved on March 25, 2026.
11. Cobo, M.J., López-Herrera, A.G., Herrera-Viedma, E. and Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. J. Am. Soc. Inf. Sci., 62: 1382–1402.
12. https://doi.org/10.1002/asi.21525Conference Board of the Mathematical Sciences. (2001). The mathematical education of teachers (Vol. 11). American Mathematical Society.
13. Craig, J., & Guzmán, L. (2018). Six propositions of a social theory of numeracy: Interpreting an influential theory of literacy. Numeracy, 11(2), Article 2. https://doi.org/10.5038/1936-4660.11.2.2
14. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
15. Demir, M. (2025). A systematic review of literature on mathematics curricula in use at primary school level. Cogent Education, 12(1), Article 2557617. https://doi.org/10.1080/2331186X.2025.2557617
16. Drijvers, P. (2018). Digital assessment of mathematics: Opportunities, issues and criteria. Mesure et Évaluation en Éducation, 41(1), 41–66. https://doi.org/10.7202/1056314ar
17. Engelbrecht, J., & Borba, M. C. (2024). Recent developments in using digital technology in mathematics education. ZDM Mathematics Education, 56, 281–292. https://doi.org/10.1007/s11858-023-01530-2
18. Eryani, R., Samitra, D., Arisandi, D., Amelia, W., & Bayumi, N. (2024). Mathematics curriculum evaluation: Challenges and opportunities in meeting global education standards (Case: State junior high school). Journal of Education Research, 5(4), 6294–6307. DOI:10.37985/jer.v5i4.1839
19. Glanzel, W. (2003). Bibliometrics as a research field: A course on Theory and Application of Bibliometric Indicators (Course Handout). Retrieved from: https://www.researchgate.net/publication/378543284_Modelo_para_o_desenvolvimento_de_estrategia_de_busca_para_a_recuperacao_da_informacao_cientifica_e_tecnologica_o_caso_da_impressao_3D
20. Gökçe, S., & Güner, P. (2021). Forty years of mathematics education: 1980-2019. International Journal of Education in Mathematics, Science and Technology, 9(3), 514–539. https://doi.org/10.46328/ijemst.1531
21. Gradini, E. (2022). Development of rubric of higher order thinking skills assessment on mathematics learning. Jurnal Teori dan Aplikasi Matematika, 6(1), 61–74. https://doi.org/10.31764/jtam.v6i1.5342
22. Guskey, T. R., & Brookhart, S. M. (2019). What we know about grading: What works, what doesn't, and what's next. ASCD. Hackenberger, B. K. (2020). “R Software: Unfriendly but Probably the Best”, Croatian Medical Journal, 61, 66–68. DOI:10.3325/cmj. 2020.61.66.
23. Hasanah, N. R., Turmudi, T., Juandi, D., & Amiruddin, M. Z. B. (2024). Exploring research trends on PISA in mathematics: A systematic review using bibliometric analysis. Avalokana Journal of Literature Review, 1(1), 14–29.
24. Hasumi, T., & Chiu, M. S. (2022). Online mathematics education as bio-eco-techno process: Bibliometric analysis using co-authorship and bibliographic coupling. Scientometrics, 127(8), 4631–4654. https://doi.org/10.1007/s11192-022-04374-2
25. Hongli, T., Liu, J., Xu, J., & Zhang, M. (2024). Educational data mining for student performance prediction: Feature selection and model evaluation. J. Electr. Syst., 1063–1074. DOI:10.52783/jes.3434
26. Howard, A., & Donaghue, H. (2014). Teacher evaluation in second language education. Bloomsbury Academic. İnceoğlu, Ç. (2014). Türkiye’de sinemayı konu alan doktora tezleri üzerine bibliyometrik bir çözümleme. Galatasaray Üniversitesi İletişim Dergisi, (21), 31-50. doi: https://doi.org/10.16878/gsuilet.96674
27. Johnson, P., & Fitzmaurice, O. (2025). Navigating mathematics curriculum reform: Teachers’ efforts and implementation challenges. Journal of Curriculum Studies, 1–25. https://doi.org/10.1080/00220272.2025.2495973
28. Kellaghan, T., & Stufflebeam, D. L. (Eds.). (2003). International handbook of educational evaluation. Kluwer Academic Publishers.
29. Kubiszyn, T., & Borich, G. D. (2024). Educational testing and measurement. John Wiley & Sons.
30. Lamichhane, B. R. (2018). Assessment practices in mathematics: Local to global contexts. Saptagandaki Journal, 9, 1–16. https://doi.org/10.3126/sj.v9i0.20876
31. Luo, Z., Mai, J., Feng, C., Kong, D., Liu, J., Ding, Y., ... Zhu, Z. (2024). A method for prediction and analysis of student performance that combines multi-dimensional features of time and space. Mathematics, 12(22), Article 3597. https://doi.org/10.3390/math12223597
32. Manizade, A., & Orrill, C. H. (2020). International perspectives on frameworks for mathematics teachers’ knowing and quality of mathematics instruction. Research in Mathematics Education, 22(2), 93–97. https://doi.org/10.1080/14794802.2020.1798809
33. McAlpine, M. (2002). Principles of assessment. University of Glasgow, Robert Clark Center for Technological Education.
34. Meylani, R. (2025). AI-powered assessments in mathematics education: A systematic review of contemporary research literature. Dokuz Eylül Üniversitesi Buca Eğitim Fakültesi Dergisi, 66, 3642–3674. https://doi.org/10.53444/deubefd.1527781
35. Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Bmj, 339: b2535 doi: 10.1136/bmj.b2535
36. Moses, R. P., & Cobb, C. E. (2001). Radical equations: Civil rights from Mississippi to the Algebra Project. Boston, MA: Beacon Press.
37. Nortvedt, G. A., & Buchholtz, N. (2018). Assessment in mathematics education: Responding to issues regarding methodology, policy, and equity. ZDM, 50(4), 555–570. https://doi.org/10.1007/s11858-018-0950-6
38. Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. Eurasia journal of mathematics, science and technology education, 19(8), em2307. https://doi.org/10.29333/ejmste/13428
39. Radmehr, F., & Vos, P. (2020). Issues and challenges of 21st century assessment in mathematics education. In L. Leite, E. Oldham, A. S. Afonso, F. Viseu, L. Dourado, & H. Martinho (Eds.), Science and mathematics education for 21st century citizens: Challenges and ways forward (pp. 437–462). Nova Science Publishers.
40. Ruthven, K. (1994). Better judgement: Rethinking assessment in mathematics education. Educational Studies in Mathematics, 27, 433–450. https://doi.org/10.1007/BF01273382
41. Tjøstheim, D., Jullum, M., & Løland, A. (2023). Statistical embedding: Beyond principal components. Statistical Science, 38(3), 411–439. https://doi.org/10.1214/22-STS881
42. Toker, Z., & Aksoy, E. (2024). A bibliometric review of studies on mathematics teacher professional development with an emphasis on mathematics coaching research. Journal of Mathematics Teacher Education, 1–75. DOI:10.1007/s10857-024-09671-1
43. Weir, C. J. (2005). Limitations of the Common European Framework for developing comparable examinations and tests. Language testing, 22(3), 281–300. DOI:10.1191/0265532205lt309oa
44. Yambi, T. D. A. C., & Yambi, C. (2018). Assessment and evaluation in education. Universidade Federal do Rio de Janeiro.
45. Zupic, I., & Cater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472. https://doi.org/10.1177/1094428114562629