IJCOPE Journal

UGC Logo DOI / ISO Logo

International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
Journal Information
ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 11

Published on: November 2026

ANIMEEDU: AN AI-POWERED PERSONALIZED LEARNING PLATFORM WITH ANIME-BASED EXPLANATIONS

Anusha L. Dhanushree C. A. Shambhavi B. Spandana D

Prof. Sharadhi S

Department of Artificial Intelligence and Machine Learning, Kalpataru Institute of Technology, Tiptur, Karnataka, India

Article Status

Plagiarism Passed Peer Reviewed Open Access

Available Documents

Abstract

Traditional digital learning platforms commonly deliver educational material through text, static presentations, or prerecorded lessons, which may not adequately address differences in learners’ language preferences, interests, and learning pace. This paper presents AnimeEdu, an AI-powered personalized learning platform that combines topic-based explanations with anime-inspired animated teaching to create an interactive learning experience. The proposed platform organizes learning around a workflow in which learners select a topic, preferred language, learning material, and teaching-avatar style. AI-assisted lesson generation is used to prepare simplified explanations, which are presented through an animated teaching interface. The platform further incorporates an AI-based doubt-solving interface, quiz-based assessment, and a dashboard for communicating learner performance. The system design brings together concepts from multimedia learning, adaptive educational systems, conversational AI, and engagement-oriented interface design. The project is evaluated at the functional-workflow level by examining the intended operation of its principal modules and their integration. The available project material describes the platform features but does not provide a controlled learner study or validated pre- and post-assessment dataset; therefore, improvements in learning outcomes are not claimed. AnimeEdu demonstrates a practical model for integrating animated explanations and AI-supported learning assistance, while identifying empirical evaluation, stronger content grounding, and deeper learner adaptation as important directions for further development.

Keywords— Personalized learning; Artificial intelligence; Animated education; Conversational AI; Educational technology; Learning assessment

How to Cite this Paper

L., A., A., D. C., B., S. & D, S. (2026). Animeedu: An AI-Powered Personalized Learning Platform with Anime-Based Explanations. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(11), 1-9. https://doi.org/10.55041/ijcope.v2i11.038

L., Anusha, et al.. "Animeedu: An AI-Powered Personalized Learning Platform with Anime-Based Explanations." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 11, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i11.038.

L., Anusha,Dhanushree A.,Shambhavi B., and Spandana D. "Animeedu: An AI-Powered Personalized Learning Platform with Anime-Based Explanations." International Journal of Creative and Open Research in Engineering and Management 02, no. 11 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i11.038.

Search & Index

References

[1] R. E. Mayer, “Applying the science of learning: Evidence-based principles for the design of multimedia instruction,” American Psychologist, vol. 63, no. 8, pp. 760–769, 2008, doi: 10.1037/0003-066X.63.8.760.

[2] R. E. Mayer, “Research-based principles for the design of instructional messages: The case of multimedia explanations,” Document Design, vol. 1, no. 1, pp. 7–19, 1999, doi: 10.1075/dd.1.1.02may.

[3] P. Brusilovsky, “Adaptive hypermedia,” User Modeling and User-Adapted Interaction, vol. 11, no. 1–2, pp. 87–110, 2001, doi: 10.1023/A:1011143116306.

[4] M. A. Kuhail, N. Alturki, S. Alramlawi, and K. Alhejori, “Interacting with educational chatbots: A systematic review,” Education and Information Technologies, vol. 28, pp. 973–1018, 2023, doi: 10.1007/s10639-022-11177-3.

[5] L. Labadze, M. Grigolia, and L. Machaidze, “Role of AI chatbots in education: Systematic literature review,” International Journal of Educational Technology in Higher Education, vol. 20, Art. no. 56, 2023, doi: 10.1186/s41239-023-00426-1.

[6] S. Deterding, D. Dixon, R. Khaled, and L. Nacke, “From game design elements to gamefulness: Defining ‘gamification’,” in Proc. 15th International Academic MindTrek Conference, 2011, pp. 9–15, doi: 10.1145/2181037.2181040.

[7] P. Lewis et al., “Retrieval-augmented generation for knowledge-intensive NLP tasks,” in Advances in Neural Information Processing Systems, vol. 33, 2020, pp. 9459–9474.

Ethical Compliance & Review Process

  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
  • •Authors retain copyright.
  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Nov 11 2026
CCBYNC

This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

View License
Scroll to Top