Designing LMS and Instructional Strategies for Integrating Generative-Conversational AI
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866915472436363264 |
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| author | Ra, Elias Kim, Seung Je Seo, Eui-Yeong So, Geunju |
| author_facet | Ra, Elias Kim, Seung Je Seo, Eui-Yeong So, Geunju |
| contents | Higher education faces growing challenges in delivering personalized, scalable, and pedagogically coherent learning experiences. This study introduces a structured framework for designing an AI-powered Learning Management System (AI-LMS) that integrates generative and conversational AI to support adaptive, interactive, and learner-centered instruction. Using a design-based research (DBR) methodology, the framework unfolds through five phases: literature review, SWOT analysis, development of ethical-pedagogical principles, system design, and instructional strategy formulation. The resulting AI-LMS features modular components -- including configurable prompts, adaptive feedback loops, and multi-agent conversation flows -- aligned with pedagogical paradigms such as behaviorist, constructivist, and connectivist learning theories. By combining AI capabilities with human-centered design and ethical safeguards, this study advances a practical model for AI integration in education. Future research will validate and refine the system through real-world implementation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_00709 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Designing LMS and Instructional Strategies for Integrating Generative-Conversational AI Ra, Elias Kim, Seung Je Seo, Eui-Yeong So, Geunju Computation and Language Higher education faces growing challenges in delivering personalized, scalable, and pedagogically coherent learning experiences. This study introduces a structured framework for designing an AI-powered Learning Management System (AI-LMS) that integrates generative and conversational AI to support adaptive, interactive, and learner-centered instruction. Using a design-based research (DBR) methodology, the framework unfolds through five phases: literature review, SWOT analysis, development of ethical-pedagogical principles, system design, and instructional strategy formulation. The resulting AI-LMS features modular components -- including configurable prompts, adaptive feedback loops, and multi-agent conversation flows -- aligned with pedagogical paradigms such as behaviorist, constructivist, and connectivist learning theories. By combining AI capabilities with human-centered design and ethical safeguards, this study advances a practical model for AI integration in education. Future research will validate and refine the system through real-world implementation. |
| title | Designing LMS and Instructional Strategies for Integrating Generative-Conversational AI |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2509.00709 |