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@article{198330,
        author = {Yukta Misal and Prof.Dinesh Deore and Danish Shaikh},
        title = {TAAS - Teacher Automation Assistance System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {8106-8115},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198330},
        abstract = {The rapid growth of artificial intelligence has enabled automation of repetitive yet essential educational tasks. Teachers still spend 40–60% of their time on administrative work such as lesson planning, quiz creation, content summarization, and communication, which reduces teaching effectiveness.
This paper presents TAAS (Teacher Automation Assistance System), an AI-powered framework built using n8n, OpenAI LLMs, and Google Workspace APIs. TAAS uses a master routing system to process natural language requests and automate six key tasks: lesson planning, quiz generation, summaries, case studies, slide creation, and emails.
Deployed via Docker on a self-hosted setup, TAAS ensures data control and independence. Evaluation shows an 83% reduction in task time, 4.2/5 quality rating, under 6 seconds latency, and 94% success rate, making it a scalable and efficient solution for AI-driven educational automation.},
        keywords = {Teacher Automation; Workflow Automation; Large Language Models; n8n; OpenAI GPT; Educational Technology; AI in Education; Google Workspace Integration; Lesson Planning Automation; Quiz Generation; Docker; Webhook Architecture},
        month = {April},
        }