USING AI TO PERSONALIZE CREATIVE LEARNING PATHS
DOI:
https://doi.org/10.29121/shodhkosh.v6.i5s.2025.6905Keywords:
Personalized Learning, Creative Education, Artificial Intelligence, Learner Modeling, Adaptive Pathways, Creativity IndexAbstract [English]
The fast development of artificial intelligence has created additional opportunities to create highly adaptive and creativity-based learning environments. The paper proposes an AI-based framework of customizing the creative learning trajectory by means of incorporating cognitive modeling, profiling of the learners, and active content-adaptation. In contrast to conventional, static learning systems, the proposed one examines multimodal learner data, including, but not limited to, behavioral interactions, creative artefacts, affective cues, and performance tracks, to provide personalized recommendations, which can be in line with the dynamic creative potential of particular learners. The system does use clustering algorithms, pattern-discovery methods, and creativity indices in order to keep the learning pathways in check, so that the instructional content, level of difficulty and the way feedback is provided are to continuously change on the fly. Based on modern scientific studies of personalized learning, artificial intelligence use to provide recommendations, and computer-generated creativity, the paper presents a system architecture in the form of modules related to the input of data, analytics, personalization, and visual feedback. The results of the experiment indicate significant increases in creativity scores, reflective thinking, and retention of the learned lessons in varied groups of learners. Quantitative results demonstrate the presence of measurable improvements in ideation fluency, aesthetic judgment, and originality in problem-solving, whereas qualitative thoughts demonstrate the growth of motivation among learners, their confidence, and their involvement in creative assignments. Teachers expressed that AI-generated insights helped them monitor the progress and implement specific interventions better.
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Copyright (c) 2025 Dr. Vivek Kumar, S. Balakrishnan, Gurpreet Kaur, Jaskirat Singh, Mr. Abhinav Srivastav, Pawan Wawage
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