Yapay Zeka Tarafından Oluşturulan İngilizce Öğretimi Ders Planlarının Değerlendirilmesi: MagicSchool.ai ve ChatGPT Üzerine Rubrik Temelli Bir Karşılaştırmalı Analiz

Abstract

Yapay zeka (YZ) araçları, eğitim bağlamlarında giderek daha fazla benimsenmektedir; ancak bu araçların pedagojik açıdan titiz İngilizce Öğretimi (ELT) ders planları üretme kapasitesine ilişkin ampirik kanıtlar sınırlıdır. Bu çalışma, yaygın olarak kullanılan iki YZ platformunun (MagicSchool.ai ve ChatGPT) ELT için ders planlama araçları olarak yapılandırılmış, rubrik temelli bir karşılaştırmalı değerlendirmesi yoluyla bu boşluğu ele almaktadır. Standartlaştırılmış bir öğretim senaryosu (A2 seviyesi, üniversite hazırlık sınıfı İngilizce, 18 öğrenci, hava kirliliği konulu 80 dakikalık oturum) kullanan araştırmacılar, yapılandırılmış uyum (Biggs, 1996), Bloom Taksonomisi (Anderson & Krathwohl, 2001), Diller için Avrupa Ortak Başvuru Metni (CEFR) ve Öğrenme Tasarımı spesifikasyonuna (Koper & Olivier, 2004) dayanan çok boyutlu bir değerlendirme rubriği uygulamıştır. Bulgular, her iki aracın da saniyeler içinde yapısal olarak işlevsel ders planları ürettiğini ve her birinin kendine özgü olanaklar sunduğunu göstermektedir: MagicSchool.ai, Rosenshine'in Öğretim İlkeleri ile örtük bir uyum sergilerken; ChatGPT, daha yüksek iç tutarlılık ve kaynak özgüllüğüne sahip, iskele oluşturulmuş çift oturumlu planlar üretmiştir. Her iki araç da farklılaştırma derinliği, dijital medya entegrasyonu ve süre tahsisi konularında sınırlılıklar göstermiştir. Çalışma, YZ çıktı kalitesini artırmak için pratik bir komut mühendisliği çerçevesi olan SCOPE protokolünü (Senaryo, Bağlam, Hedefler, Pedagoji, Genişletmeler) önermektedir. Öğretmen eğitimi, kurumsal YZ yönetişimi ve ELT mesleki gelişimi için çıkarımlar tartışılmaktadır.

Keywords

• Yapay zeka
• ChatGPT
• İngilizce öğretimi (ELT)
• Ders planlama
• MagicSchool.ai
• Komut mühendisliği (Prompt mühendisliği)

Evaluating AI-Generated Lesson Plans for English Language Teaching: A Rubric-Based Comparative Analysis of MagicSchool.ai and ChatGPT

Abstract

Artificial intelligence (AI) tools are increasingly being adopted in educational contexts, yet empirical evidence regarding their capacity to generate pedagogically rigorous English Language Teaching (ELT) lesson plans remains limited. This study addresses that gap through a structured, rubric-based comparative evaluation of two widely used AI platforms—MagicSchool.ai and ChatGPT—as lesson planning tools for ELT. Using a standardised teaching scenario (A2-level, university preparatory English, 18 students, 80-minute session on air pollution), the researchers applied a multi-dimensional evaluation rubric grounded in constructive alignment (Biggs, 1996), Bloom's Taxonomy (Anderson & Krathwohl, 2001), the Common European Framework of Reference for Languages (CEFR), and the Learning Design specification (Koper & Olivier, 2004). Findings reveal that both tools generated structurally functional lesson plans within seconds, each with distinct affordances: MagicSchool.ai demonstrated implicit alignment with Rosenshine's Principles of Instruction, while ChatGPT produced scaffolded, dual-session plans with higher internal coherence and resource specificity. Both tools exhibited limitations in differentiation depth, digital media integration, and time allocation. The study proposes a practical prompt engineering framework—the SCOPE protocol (Scenario, Context, Objectives, Pedagogy, Extensions)—to enhance AI output quality. Implications for teacher training, institutional AI governance, and ELT professional development are discussed.

Keywords

• Artificial intelligence
• ChatGPT
• ELT
• Lesson planning
• MagicSchool.ai
• Prompt engineering.

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