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From Grading to Guidance,

 Integrating AI Feedback to Enhance Language Assessment in Higher Education

Mariappen Gopalakrishnan, Sri Sarmila Dewi Khrishnan, Shuhashini Balan
Politeknik Balik Pulau , Politeknik Seberang Perai

 [email protected]

ABSTRACT

This innovative AI-driven method introduces a fresh way of handling assessment. Instead of the usual tick marks that only show whether an answer is right or wrong, AI Powered Blackbox AI turns marking into meaningful, student-focused feedback. Learners don’t just see their mistakes — they get clear explanations that help them understand what went wrong and how to improve. For lecturers, this approach lightens the workload while still enriching the learning process. In one case study with 30 comprehension scripts from English language students at a Malaysian polytechnic, Blackbox AI was used to provide rubric-based evaluations along with tailored feedback for each incorrect response. The results were striking: students engaged more deeply with the AI-generated feedback, reflecting on their errors and correcting themselves more effectively. Lecturers, meanwhile, reported saving time and seeing an overall improvement in the quality of feedback. The findings show that this approach offers a practical, scalable solution — one that balances efficiency with the richness of pedagogy, making language classrooms more interactive and learner-centered.

Keywords: Language Assessment, Artificial Intelligence in Education, Formative Feedback, Student-Centered Learning, TVET