Publication Date

12-2025

Date of Final Oral Examination (Defense)

10-3-2025

Type of Culminating Activity

Dissertation

Degree Title

Doctor of Education in Educational Technology

Department

Educational Technology

Supervisory Committee Chair

Young Baek, Ph.D.

Supervisory Committee Member

Yu-Hui Ching, Ph.D.

Supervisory Committee Member

Dazhi Yang, Ph.D.

Abstract

Khanmigo is an LLM AI assistant that is a Socratic-style AI tool supports students while working without offering revisions or correct answers. This case study examined how middle school students interact with Khanmigo during the editing process. The purpose of this intrinsic, embedded case study was to gain a deeper understanding of how students engage with Khanmigo and how this influences students' perceptions about writing and editing. Twelve eighth graders were observed while editing on two different occasions during the 2024-2025 academic term. After each editing session, students were invited into focus groups to discuss their general thinking about the writing process, how access to Khanmigo affected their decision-making, and what they felt about editing with and without this tool. Students were grouped in one of three categories: struggling writers, mid-level performers, and academic achievers. Across all three groups, students reported favorable impressions of editing with the AI, with many indicating a stronger understanding of how to approach editing after just one experience. Many also reported that they learned general writing strategies during the first session that they were able to employ while drafting their second essay. Students leveraged the AI as a more competent alternative to one-on-one tutors. The teacher remained central to the editing experience during both sessions, as students relied on her to confirm their understanding of what types of decisions to make. Finally, students expressed deep appreciation for their ability to maintain ownership and academic integrity of their writing. This study contributes to the existing research gap on middle school students' use of LLM AI technology.

DOI

https://doi.org/10.18122/td.2465.boisestate

Available for download on Wednesday, December 01, 2027

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