Award Date

5-15-2026

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Educational Psychology, Leadership, and Higher Education

First Committee Member

Sean Mulvenon

Second Committee Member

Tiberio Garza

Third Committee Member

Steven McCafferty

Fourth Committee Member

Si Jung Kim

Number of Pages

132

Abstract

This study and various other studies use quantitative models to identify which persuasive features predict persuasiveness. Most studies in the field do not explain why participants responded as they did nor do they focus on studying adult non-native English learners also referred to as second language (L2) English learners. Despite seemingly remarkable progress on research related to how to convey persuasive messages, there has been little work related to persuasive messaging targeted at second language learners or non-native speakers. In addition, despite the increasing reliance on AI technologies and tools in language learning within educational and work settings, there has been limited investigation into non-native speakers' attitudes and perceptions towards AI integration in education. To address this gap, in these mixed methods study, a qualitative discourse and sentiment analysis is conducted on participants’ open-ended explanations in addition to analyzing quantitative data from surveys designed to analyze L2 English learners’ ratings of selected persuasive features in positive and negative persuasive opinion multimedia. In addition, this study aims to explore L2 English learners’ overall sentiment and attitudes towards the use of artificial intelligence (AI) in education and work settings. Findings from the combined quantitative and qualitative analyses demonstrate that persuasive effectiveness is not determined by sentiment alone, but by how persuasive features align with emotional framing. The results of this study illustrate that positive opinions activate emotional and heuristic routes to persuasion, while negative opinions trigger more analytic processes. Furthermore, the results of this study inform the design of AI-supported educational tools by identifying which persuasive features of communication most effectively shape opinions and attitudes for multilingual audiences when presented with opposing opinion polarities.

Keywords

Adult Second Language Learners; Attitude Formation towards AI; Media Psychology; Neuromarketing; Persuasive Opinions Multimedia; User Experience (UX) Evaluation

Disciplines

Bilingual, Multilingual, and Multicultural Education | Cognitive Psychology | Marketing

File Format

PDF

File Size

803 KB

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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