This study investigated the factors underlying the estimation of learner self-confidence during explanations with a conversational agent in an online explanation task. Based on reviews of previous studies, we focused on how factors such as the learner's task activities and personal characteristics can be predictors. To examine these points, we used an online explanation task, which was run by a conversational agent for students in a classroom on information processing psychology (n=99). We asked the participants to make text-based explanations to the agent in a question-and-answer (Q&A) style, and clarified a particular concept that was taught in a previous lecture in the class. The results show that an increase in the amount of actual task work for explanations and personal characteristics (such as social skills) helped to predict higher self-confidence. The findings have implications not only for knowledge of how such factors might influence learner self-confidence in an online explanation task, but also for the design of online tutoring systems that can automatically detect learner confidence using these variables, and facilitate learning adequately based on such data. {For the full proceedings, see ED593090.]