AI-DRIVEN ASSESSMENT IN VISUAL COMMUNICATION CLASSES
DOI:
https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6651Keywords:
Artificial Intelligence, Visual Communication, Automated Assessment, Design Education, Learning Analytics, Creative EvaluationAbstract [English]
The Artificial Intelligence (AI) of learning has transformed the classroom, particularly in the field of visual communication, which is the creative one. However, the objective assessment of the abilities of students in the sphere of design remains one of the serious concerns due to subjectivity of working in creative sphere and the element of beauty. The problem addressed in this paper is that there is no consistency in evaluation criteria and manual evaluation which is time consuming in visual communication courses. The proposed study will focus on making and testing a grading system based on the AI technology, which will evaluate the visual works of students based on the established criteria such as composition, color play, typography, and innovation. The mixed-methods research was employed, and the qualitative analysis of instructor feedback and quantitative evaluation using AI image-recognition and design-metric algorithms were used. The group of 80 students taking three courses in design was researched. The efficiency of the AI tool at grading was compared to grading by humans, experts. The statistical correlation of the AI-generated scores with instructor scores revealed that the two are very closely correlated with a correlation of 87 percent indicating high degree of reliability. The system saved 65 % of the time on which it was utilized during evaluation and improved the accuracy of feedback 42 %. Findings demonstrate that AI can significantly enhance objectivity and efficiency in the evaluation of creativity and provide the information obtained based on the data to enhance the experience. The paper goes further to adapt the use of AI as an evaluation tool in the broader art and design education context in a manner that scales of assessment systems can be reached, which are both equitable and responsive to human expertise.
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Copyright (c) 2025 Pooja Yadav, Bhavuk Samrat, Navnath B. Pokale, Dr. Namita Parati, Dr. Poonam Singh, Rashmi Keote
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