In traditional education, there is not much difference between assessment tasks designed for learners. However, learners' learning performance may vary due to a number of factors, e.g., learning ability, academic emotion, and learners' and teachers' academic expectations. Considering those factors, accurately recommending personalized assessment tasks for each learner is challenging. To overcome the limitations in the current work, this paper proposed an autonomous-agent-based approach to recommend personalized assessment tasks considering mult...
