Abstract

University students increasingly use generative artificial intelligence (GAI) to assist with, or in some cases, complete learning and assessment activities. Because GAI is an emerging, novel technology, how students assess the ethics of various GAI affordances is unclear. Therefore, research into factors influencing ethical judgments regarding GAI use is needed. One interesting factor that may influence these judgments is whether students are internally or externally motivated to learn. Understanding the relationship between motivation and ethical judgments may be important to the design and implementation of learning aids and interventions intended to help students make sound ethical decisions related to the use of GAI in education. To better understand this relationship, we investigate the following research question: Do students’ learning motivations affect their judgments of the ethics of GAI use for learning activities and assessments? Theoretically, this study is grounded in Self-Determination Theory (SDT) (Ryan & Deci, 2020), which proposes that students who are intrinsically motivated (i.e., internally driven by personal interest and mastery) will more strongly disapprove of ethically questionable GAI uses. Conversely, extrinsically motivated students (i.e., those driven primarily by grades, external recognition, or avoidance of effort) may be more accepting or rationalizing of ethically questionable behaviors involving GAI. Using a scenario-based experimental design, participants will evaluate one or more distinct hypothetical scenarios involving GAI from each category below: • Clearly unethical use: Directly copying a GAI-generated response and submitting it as one's original work. • Clearly ethical use: Utilizing GAI tools for initial brainstorming of project ideas. • Ambiguous or "grey area" use: Employing GAI to substantially revise or rewrite student-written content. These scenarios will be validated by educational experts prior to use. Responses will be used to create an index, which will be used in subsequent analysis. The primary dependent variable will be participants' perceptions of the appropriateness or ethical acceptability of each scenario. The major predictor variable will include intrinsic versus extrinsic motivation. Moral maturity and demographic characteristics such as academic major, age, and classification (e.g., undergraduate or graduate student) will be included as control variables. The results of this study will offer important insights into the psychological factors influencing ethical decision-making related to emerging technologies in higher education and will provide actionable recommendations for academic policy and practice.

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