Citation

Izani, M. and Dalia, R. and Aishah, R. (2025) Click, Analyze, Improve: Unveiling IRIS, an AI-Based Photography Learning Tool. In: International Conference on Artificial Intelligence and Virtual Reality, 19-21 July 2024, Fukuoka, Japan.

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Abstract

This paper builds upon previous research into virtual reality (VR) simulators for photography education by introducing a conceptual framework for a novel AI-powered application, named IRIS (Intelligent Recommendation & Improvement System). IRIS is designed to assist students in learning photography by using artificial intelligence to analyze their photographs and provide personalized feedback from a professional photographer's perspective. This research is part of an initiative to integrate AI tools as sub-elements within the new Applied Media program at the Higher Colleges of Technology (HCT), where photography is a featured course. The paper details the initial stages in the conceptual design and planning of IRIS, which include strategies for data collection, model training, the development of feedback generation algorithms, and considerations for user interface design. At this stage, the application remains in the conceptual phase, with development focused on establishing a proof-of-concept (POC) to demonstrate the feasibility and potential effectiveness of AI-driven feedback in enhancing photography education. By proposing the use of AI to deliver accessible and personalized guidance, this research aims to not only augment student learning outcomes but also encourage creative exploration and contribute to innovative pedagogical strategies within the Applied Media program at HCT. Future work will involve further development and refinement of the IRIS application, with an emphasis on more interactive features, multi-modality, and the effective integration of AI capabilities to support educational goals.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	AI technology
Subjects:	L Education > LB Theory and practice of education > LB1060 Learning
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	27 Aug 2025 03:15
Last Modified:	29 Aug 2025 10:00
URII:	http://shdl.mmu.edu.my/id/eprint/14420

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