ij3dptdi

International Journal of 3D Printing Technologies and Digital Industry

2602-3350 2602-3350

Kerim ÇETİNKAYA

10.46519/ij3dptdi.1811214

Artificial Intelligence (Other)

Yapay Zeka (Diğer)

AI-ENHANCED FEEDBACK AND FEEDFORWARD SYSTEMS: DEVELOPMENT AND STAKEHOLDER-BASED EVALUATION OF A PERSONALIZATION AND ETHICS-FOCUSED CONCEPTUAL FRAMEWORK FOR MATHEMATICS EDUCATION

YAPAY ZEKÂ İLE GÜÇLENDİRİLMİŞ GERİ VE İLERİ BİLDİRİM SİSTEMLERİ: MATEMATİK EĞİTİMİ İÇİN KİŞİSELLEŞTİRME VE ETİK ODAKLI BİR KAVRAMSAL ÇERÇEVENİN GELİŞTİRİLMESİ VE PAYDAŞ TEMELLİ DEĞERLENDİRİLMESİ

https://orcid.org/0000-0002-9812-9552

Zübeyde

Milli Eğitim Bakanlığı, Adana

https://orcid.org/0000-0002-6107-3487

Akın

Ayça

Antalya Belek University

https://orcid.org/0000-0001-8717-4983

Alkan

Selçuk

Hatay Mustafa Kemal University

https://orcid.org/0000-0002-2700-3565

Güzeller

Cem

YILDIZ TEKNİK ÜNİVERSİTESİ

04 30 2026

10 1 243 265 10 26 2025 01 16 2026

2017

International Journal of 3D Printing Technologies and Digital Industry

This study examines, from both theoretical and practical perspectives, how feedback and feedforward processes in mathematics education can be restructured within AI-supported learning environments. While traditional feedback systems often fail to adequately account for individual differences and tend to provide delayed responses, AI-based systems are able to analyze student performance in real time and deliver personalized, explanatory, and strategically oriented guidance. The study provides a comprehensive evaluation of the pedagogical opportunities offered by AI-supported feedback systems in mathematics education, with a focus on teacher roles, ethical considerations, and sustainability. In addition, a conceptual model based on the feedforward approach is proposed, and its integration with learning analytics, adaptive systems, and data-driven instruction is discussed. This research contributes to the literature at a theoretical level while also offering practical recommendations for the human-centered, ethical, and inclusive use of AI in education.

Bu çalışma, matematik eğitiminde geri bildirim (feedback) ve ileri bildirim (feedforward) süreçlerinin yapay zekâ (YZ) destekli öğrenme ortamlarında nasıl yeniden yapılandırılabileceğini kuramsal ve uygulamalı açıdan ele almaktadır. Geleneksel geri bildirim sistemlerinin bireysel farklılıkları yeterince dikkate alamaması ve gecikmeli dönüt sunması gibi sınırlılıklarına karşılık, YZ tabanlı sistemler öğrenci performansını anlık olarak analiz ederek kişiselleştirilmiş, açıklamalı ve stratejik yönlendirmeler sağlayabilmektedir. Çalışmada, YZ destekli geri bildirim sistemlerinin matematik eğitimi özelinde sunduğu pedagojik olanaklar, öğretmen rolleri, etik boyutlar ve sürdürülebilirlik açısından bütüncül biçimde değerlendirilmiştir. Ayrıca, ileri bildirim yaklaşımına dayalı kavramsal bir model önerisi geliştirilmiş ve bu modelin öğrenme analitiği, adaptif sistemler ve veri temelli öğretimle nasıl entegre edilebileceği tartışılmıştır. Araştırma, hem teorik düzeyde alan yazına katkı sunmakta hem de YZ’nin eğitimde insani, etik ve kapsayıcı biçimde kullanılmasına yönelik pratik öneriler ortaya koymaktadır.

Yapay Zekâ Matematik Eğitimi Geri Bildirim İleri Bildirim.

Artificial Intelligence Feedback Feedforward Mathematics Education.

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