Award Date

May 2025

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Teaching and Learning

First Committee Member

P.G. Schrader

Second Committee Member

Xue Xing

Third Committee Member

Yan Chen

Fourth Committee Member

Heather Dahl-Jacinto

Number of Pages

189

Abstract

This three-article dissertation investigated the effectiveness, implementation quality, and automation of Individual Learning Plans (ILPs) in promoting college and career readiness. Article 1 analyzed High School Longitudinal Study of 2009 data and found that ILPs did not significantly guide course alignment. Article 2 examined ILP implementation across Nevada high schools, revealing inconsistent quality, limited standardization, and few culturally responsive practices. These findings informed the creation of a new high-quality ILP framework. Article 3 employed a convergent parallel mixed methods design to assess an automated ILP prototype based on this framework. Participants in the automated group reported significantly higher scores in engagement, user experience, and cultural relevance. Thematic and sentiment analyses supported these results, with participants expressing greater confidence, clarity, and motivation. This dissertation expanded the ILP literature by identifying key gaps, creating a new framework, and introducing automation as a scalable, equitable solution for improving implementation.

Keywords

AI-Enhanced Career Planning; Education Policy; Educational Technology; Individual Learning Plan; Student-Centered Automation; Workforce Development

Disciplines

Artificial Intelligence and Robotics | Computer Engineering | Curriculum and Instruction | Curriculum and Social Inquiry | Education | Educational Methods

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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