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  • Sosyal Bilimler ve Eğitim Dergisi
  • Cilt: 8 Sayı: 1
  • Design of an iOS Mobile Application for the Automated Evaluation of Open-Ended Exams via Artificial ...

Design of an iOS Mobile Application for the Automated Evaluation of Open-Ended Exams via Artificial Intelligence and Image Processing

Authors : Nazmi Ekin Vural
Pages : 1-35
Doi:10.53047/josse.1691312
View : 86 | Download : 103
Publication Date : 2025-05-31
Article Type : Research Paper
Abstract :Evaluating open-ended exams presents significant challenges in terms of time management and consistency in educational processes. This study aims to develop an iOS-based mobile application, “Exam Reader” to streamline the evaluation of handwritten open-ended exam responses by integrating visual recognition and language analysis tools, enabling educators to deliver timely and fair assessments. Developed using the Swift programming language, the application relies on two core technologies. First, handwritten student responses are converted into digital text using Optical Character Recognition (OCR) via the Google Cloud Vision API. These texts are then analyzed for clarity and coherence using the OpenAI API and GPT-4o model, ensuring that students’ ideas are presented in a structured, accessible format for evaluation. Finally, the evaluation results and related data are provided to users in PDF format. Designed with a user-friendly interface, the application allows educators to quickly interpret responses and align them with expected learning outcomes through integrated language and image analysis tools. This system offers an innovative model for digitizing, standardizing, and automating open-ended exam evaluations, contributing to the systematic improvement of educational assessment processes. However, the application has limitations. Variations in handwriting and low-quality scans may reduce OCR accuracy, and AI-supported content analysis risks missing contextual nuances. Additionally, the system requires a stable internet connection, limiting offline functionality. Future enhancements, including advanced OCR models, multilingual support, and an offline mode, are planned to address these issues. The application developed in this direction is expected to make a significant contribution to the digitalization of educational assessment and to adapt to next-generation technologies.
Keywords : Görüntü İşleme, El Yazısı Tanıma, Yapay Zekâ, Cloud Vision API, OpenAI API, iOS

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