Journals / Turkiye Kimya Dernegi Dergisi Kısım C: Kimya Egitimi / 2026 / Cilt: 11 Sayı: 2

Title of the Book Reviewed: STEM Education: Shaping Future Learning Practices in the Age of AI

KİTAP iNCELEME: STEM Education: Shaping Future Learning Practices in the Age of AI

Burak Feyzioğlu(AYDIN ADNAN MENDERES ÜNİVERSİTESİ)0000-0002-0128-3343
Pages
255–274
Publication Date
2026-09-28
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Overall, the book provides a timely, multidimensional, and critical reference for STEM, science, and chemistry education.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study reviews STEM Education: Shaping Future Learning Practices in the Age of AI, edited by Elmas and Akarsu and published by Palgrave Macmillan in 2026.
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Key Findings & Data:The chapter on teaching chemical reactions particularly illustrates the use of AI in chemistry education.
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Conclusion & Impact:Overall, the book provides a timely, multidimensional, and critical reference for STEM, science, and chemistry education.
🔬Design:Review & Systematic Survey
📍Scope:2026 Verileri
⚙️Variables:STEM Eğitimi · Yapay Zeka · Kimya Eğitimi

Abstract

This study reviews STEM Education: Shaping Future Learning Practices in the Age of AI, edited by Elmas and Akarsu and published by Palgrave Macmillan in 2026. The review examines how the book conceptualizes the transformation of STEM education in the age of artificial intelligence (AI) and evaluates the opportunities and limitations of its approach from the perspective of chemistry education. Consisting of fourteen chapters, the book was examined in terms of context and purpose, relevance to its target audience, timeliness and contribution to the literature, content, and theoretical, methodological, and practical strengths and limitations. The review indicates that the book considers AI not merely as a technological innovation but in relation to teacher education, teacher and student roles, engineering design, assessment, ethics, equity, real-life problems, and socioecological dimensions. AI is positioned as a means of supporting pedagogical and cognitive processes rather than replacing teachers or students. The chapter on teaching chemical reactions particularly illustrates the use of AI in chemistry education. However, a more holistic conceptual framework connecting the chapters and stronger empirical evidence on learning outcomes are needed. Overall, the book provides a timely, multidimensional, and critical reference for STEM, science, and chemistry education.

Özet

Bu çalışmada, Elmas ve Akarsu editörlüğünde 2026 yılında Palgrave Macmillan tarafından yayımlanan STEM Education: Shaping Future Learning Practices in the Age of AI adlı kitap incelenmiştir. İncelemede, kitabın yapay zekâ çağında STEM eğitiminin dönüşümünü nasıl kavramsallaştırdığı ve ortaya koyduğu yaklaşımın kimya eğitimi açısından sunduğu olanaklar ve sınırlılıklar değerlendirilmiştir. On dört bölümden oluşan kitap; bağlam ve amaç, hedef kitleye uygunluk, güncellik ve literatüre katkı, içerik ile teorik, metodolojik ve pratik güçlü yönler ve sınırlılıklar açısından ele alınmıştır. İnceleme sonucunda, kitabın yapay zekâyı STEM eğitiminde yalnızca teknolojik bir yenilik olarak ele almadığı; öğretmen eğitimi, öğretmen ve öğrenci rolleri, mühendislik tasarımı, ölçme-değerlendirme, etik, eşitlik, gerçek yaşam problemleri ve sosyoekolojik boyutlarla ilişkilendirdiği belirlenmiştir. Yapay zekâ, öğretmen veya öğrencinin yerine geçen bir unsurdan çok, pedagojik ve bilişsel süreçleri destekleyen bir araç olarak konumlandırılmıştır. Özellikle kimyasal tepkimelerin öğretimine odaklanan bölüm, yapay zekânın kimya eğitimindeki kullanımını somutlaştırmaktadır. Bununla birlikte, bölümlerdeki yaklaşımları ilişkilendiren daha bütüncül bir kavramsal çerçeveye ve önerilen uygulamaların öğrenme çıktıları üzerindeki etkilerini ortaya koyan daha güçlü ampirik kanıtlara gereksinim bulunmaktadır. Genel olarak kitap, STEM, fen ve kimya eğitimi alanları için güncel, çok boyutlu ve eleştirel bir başvuru kaynağıdır.

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Cite This Article

Feyzioğlu, B., *, B. F. (2026). Title of the Book Reviewed: STEM Education: Shaping Future Learning Practices in the Age of AI. Turkiye Kimya Dernegi Dergisi Kısım C: Kimya Egitimi, Cilt: 11 Sayı: 2, 255–274. https://doi.org/10.37995/jotcsc.2033615

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References (10)

  1. Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2025). Generative AI without guardrails can harm learning: Evidence from high school mathematics. Proceedings of the National Academy of Sciences, 122(26), e2422633122. https://doi.org/10.1073/pnas.2422633122
  2. Berendt, B., Littlejohn, A., & Blakemore, M. (2020). AI in education: Learner choice and fundamental rights. Learning, Media and Technology, 45(3), 312–324. https://doi.org/10.1080/17439884.2020.1786399
  3. Elmas, R., & Akarsu, M. (Eds.). (2026). STEM Education: Shaping Future Learning Practices in the Age of AI. Palgrave Macmillan. https://doi.org/10.1007/978-981-95-9023-0
  4. Felix, J., & Webb, L. (2024). Use of artificial intelligence in education delivery and assessment (POSTnote 712). Parliamentary Office of Science and Technology. https://doi.org/10.58248/PN712
  5. Kohnke, S., & Zaugg, T. (2025). Artificial intelligence: An untapped opportunity for equity and access in STEM education. Education Sciences, 15(1), 68. https://doi.org/10.3390/educsci15010068
  6. Maurer, N., & Huwer, J. (2026). Teaching and Learning about Artificial Intelligence (AI) in Secondary Education Chemistry Classes. Journal of Chemical Education. https://doi.org/10.1021/acs.jchemed.6c00128 Miao, F., & Cukurova, M. (2024). AI competency framework for teachers. UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000391104
  7. Noyes, K., Franovic, C. G. C., & Cooper, M. M. (2026). Design principles for developing and analyzing formative assessments to support mechanistic reasoning. In Exploring Mechanistic Reasoning in Science Education: Understanding Phenomena (pp. 107-123). Cham: Springer Nature Switzerland.
  8. Nuangchalerm, P. (2023). AI-driven learning analytics in STEM education. International Journal of Research in STEM Education, 5(2), 77-84. https://doi.org/10.33830/ijrse.v5i2.1596
  9. Ramnarain, U. (2026). A systematic review of research on the integration of real and virtual laboratories for inquiry-based learning. In L. Leite, L. Dourado, A. S. Afonso, S. Morgado, & L. Carvalho (Eds.), Practical work in science education in the digital era: Challenges and opportunities (pp. 249–266). Springer. https://doi.org/10.1007/978-3-032-13788-3_18
  10. Tijani, B. E., Ojo, O. T., Akinde, A. A., & Irilochuwe, G. E. (2026). Artificial Intelligence-Enhanced Work-Integrated Learning in Chemistry Education: Bridging Laboratory Theory and Professional Practice. Open Books and Proceedings, Six-87. https://doi.org/10.38140/obp5-2026-06 Zhai, X., & Crippen, K. (2026). Transforming science learning materials in the era of artificial intelligence. In X. Zhai & K. Crippen (Eds.), Advancing AI in Science Education: Envisioning Responsible and Ethical Practice. Springer. https://doi.org/10.1007/978-3-032-16871-9_8