Hirnanda Dimas Pradana, Alim Sumarno, R. Rusijono, Ainur Rofik, Fajar Arianto, Zaenal Abidin
This study aimed to design an artificial intelligence-based evaluation system that aligns with outcome-based education (OBE) principles to enhance learning assessment in higher education. A design and development research approach was adopted, including need analysis, system design, and prototype development. The prototype utilized supervised machine learning and natural language processing to map course learning outcomes (CLOs) to program learning outcomes (PLOs), assess student submissions, and provide personalized feedback. Results showed the system accurately evaluated student achievements and generated real-time visual dashboards. Because conventional evaluations are often fragmented and non-adaptive, this system offers a data-driven solution to promote transparency, adaptiveness, and accountability. The impact of this research supports the digital transformation of education aligned with sustainable development goals (SDGs), particularly in fostering quality education and educational innovation. © School of Engineering, Taylor’s University.
Universitas Negeri Surabaya, Surabaya, Indonesia
