Taklif.AI: LLM-Powered Platform for Interest-Based Personalized College Assignments
Zaki Kurdya, Mohammed Zuqlam, Salem Amassi, Shady Telbany, Motaz Saad

TL;DR
Taklif.AI is a novel platform that uses LLMs to generate personalized college assignments based on students' interests, aiming to improve engagement and reduce unethical practices.
Contribution
It introduces a structured prompt engineering pipeline with guardrails to incorporate extracurricular interests and cultural contexts into assignment generation.
Findings
84% of participants rated personalization as beneficial
Preliminary testing shows positive reception among students and educators
System architecture leverages Llama 3.3 70B with serverless AWS deployment
Abstract
Educators face significant challenges in creating engaging, personalized assignments that accommodate students' diverse interests and cognitive abilities. Traditional one-size-fits-all assignments frequently lead to decreased student engagement and increased reliance on unethical practices such as plagiarism. To address these challenges, we present Taklif.AI, a platform that leverages Large Language Models (LLMs) to automatically generate personalized assignments tailored to individual student interests. Unlike existing AI-powered educational platforms that personalize based on academic performance metrics alone, Taklif.AI incorporates students' extracurricular interests and cultural contexts into the assignment generation process through a structured prompt engineering pipeline with input and output guardrails. The platform employs a serverless architecture on AWS with Next.js, using…
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