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Conventional academic assignment management and evaluation processes often burden lecturers with repetitive manual tasks, lengthy grading times, and a susceptibility to grading bias. On the students' side, they frequently face ambiguity regarding the expected scope of discussion and are forced to wait extended periods to receive performance feedback. To address these challenges, A.I.M.S Pro was developed as an end-to-end educational technology (EdTech) platform that integrates generative artificial intelligence (Google Gemini 1.5 Flash) to fully digitally transform the assignment management and grading ecosystem.

The main objective of this innovation is to modernize the academic workflow through four interconnected novel features. First, the Batch Assignment Registration Module (Persistent Metadata) is specifically designed to allow lecturers to add multiple assignments rapidly. The system automatically retains basic class information without the need for repeated data entry. Second, the system utilizes AI-Contextualized Rubric Keyword Generation, where the smart engine reads the Main Title and Assignment Synopsis to extract assessment parameters that are 100% accurate and relevant, eliminating the issue of off-topic keywords. Third, this innovation is driven by an AI Auto-Grading Engine capable of marking papers objectively, transparently, and swiftly according to the rubric weightings calibrated by the lecturer. Fourth, the Interactive Student Portal provides real-time access for students to select assignments, read discussion scope guidelines, submit tasks, and review grading results along with detailed rubric feedback immediately after the grading is completed.

The implementation of A.I.M.S Pro promises a highly significant impact on higher education institutions. This innovation minimizes lecturers' assignment management and grading time by up to 80%, providing greater capacity for effective student mentoring. For students, the system's transparency guarantees task clarity and provides swift performance feedback for continuous improvement. Built using a highly scalable architecture, this system possesses broad commercial value and the flexibility to be adopted by various faculties and universities, thereby serving as a catalyst for AI-driven educational transformation.

Keywords: Generative Artificial Intelligence, AI Auto-Grading, Assignment Management System, Contextual Rubrics, Real-Time Student Portal, Educational Technology (EdTech).