Abstract
The purpose of this study is to explore the types of scaffolding that AI chatbots can
 provide through systematic feedback based on learners' individual utterances during
 elementary English learning-oriented assessment. For the study, the researcher designed
 an English speaking task and implemented an learning-oriented speaking assessment
 using an AI chatbot for 25 learners in the 6th grade. Subsequently, individual interviews
 were conducted to analyze the learners' responses to the scaffolding. By analyzing
 learner responses and transcripts of conversations between learners and chatbots, the
 researcher categorized the types of scaffolding that AI chatbots can provide during
 the learning-oriented assessment. As a result, first, the scaffolding can be categorized
 into three areas: linguistic, cognitive, and affective. Linguistically, the chatbots
 provided scaffolding for conveying meaning, language forms, and pronunciation
 aspects. In the cognitive aspect, the scaffolding assisted learners in their thinking
 processes, while in the affective aspect, it helped regulate frustration. Second, through
 scaffolding using various strategies, learners demonstrated the ability to self-correct
 erroneous utterances and gradually complete sentences on their own. In addition,
 cognitive scaffolding helped learners solve challenging tasks at their current cognitive
 level, and affective scaffolding contributed to improving confidence in speaking
 English. The study offers implications and recommendations based on the findings.
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