📄 Full text: arXiv:2605.04729 · local
Definition
A web-based system that uses LLMs and Learning Analytics dashboards to provide automated, rubric-based feedback on student presentation slides. Developed by Becerra et al. (2026), AISSA addresses the scalability challenge of providing timely formative feedback in large university courses.How It Works
1. Students upload slide decks before presenting 2. System analyzes slide-level features and content using ChatGPT 5.2 3. Generates quantitative scores and qualitative feedback aligned with teacher-defined rubrics 4. Results displayed via interactive dashboards for both students and teachersPilot Results
Tested with 46 undergraduate students in a real academic setting. Findings: technically reliable, economically feasible, and perceived by students as useful for iterative slide improvement.Connections
- Extends automated-grading beyond text assessment to multimodal presentation evaluation
- Applies learning-analytics dashboards to formative feedback workflows
- Complements formative-assessment approaches with rubric-based automation
- Demonstrates scalable AI feedback deployment, relevant to ai-peer-feedback-systems
Related Pages
- slidesqaqa-pedagogical-question-generation — complementary slide analysis focused on pedagogical question extraction