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Previous studies have found that the frequency and the regularity of taking the self-assessment are positively correlated with learning performance. However, as artificial intelligence is widely used for self-assessment in various educational contexts, numerous behaviors have been identified, including nonstandard behaviors that can negatively impact learning. Therefore, more analysis regarding students' self-assessment behaviors in different contexts and their influence on learning is required. In this study, we examined students’ behaviors in online self-assessment task and how it affects their learning performance. A 6-week experiment was conducted in an accounting course. Students were instructed to complete online self-assessment in the form of formative quizzes after class. We performed clustering analysis, which revealed three behavioral patterns in online self-assessment, and we compared the learning performance of students across different patterns. The results indicated that students who frequently took the online assessments after class tended to achieve a higher examination score than those who did not. However, the learning performance of students who demonstrated nonstandard behaviors did not necessarily improve, even though they actively took the assessments. Our results suggest that student behavior is a critical factor in improving learning through self-assessment. These findings provide insights for researchers in the learning analytics field as well as for practitioners who wish to adopt online self-assessment for learning.