Dataset on The Role of Moral Obligation and Moral Intention in the Relationships Between Threat Appraisal, Coping Appraisal, and Attitudes Toward Avoiding AI-Assisted Plagiarism
Description
This dataset contains survey data collected from 1,240 university students in Vietnam concerning their perceptions, moral responsibility, and attitudes toward avoiding AI-assisted plagiarism. The dataset includes 43 variables, comprising 34 measurement items across eight constructs and nine demographic and background variables. The eight constructs are Perceived Vulnerability (PEV), Perceived Negative Learning Effects (NLE), Perceived Severity (PSE), Self-Efficacy (SEF), Response Efficacy (REF), Moral Intention (MOI), Attitude Toward Avoiding Plagiarism (ATT), and Moral Obligation (MOB). All measurement items were assessed using a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. The questionnaire was adapted primarily from Ali and Arpaci (2025) and related validated sources. Perceived Vulnerability, Perceived Severity, Self-Efficacy, and Response Efficacy were adapted from measures used in protection motivation research. Moral Intention, Moral Obligation, and Attitude Toward Avoiding Plagiarism were adapted from previous studies on ethical decision-making and plagiarism. Perceived Negative Learning Effects was re-conceptualized from items concerning the negative consequences of AI chatbot use and reflects perceived reductions in self-reliance, confidence in independent learning, and willingness to invest effort in learning tasks. The dataset also contains information on gender, year of study, academic major, type of educational institution, frequency of generative AI use for learning, generative AI tools used, common purposes of use, prior guidance on academic integrity when using AI, and awareness of university or course policies regarding generative AI. The data can be reused for research on academic integrity, responsible use of generative AI, protection motivation, moral responsibility, cognitive offloading, and students’ attitudes toward AI-assisted plagiarism in higher education.
Files
Steps to reproduce
The dataset was collected using an online questionnaire administered to university students in Vietnam. Participants were informed about the purpose of the research and voluntarily agreed to participate before completing the questionnaire. Respondents were university students with experience using generative AI or AI chatbots for learning purposes. The questionnaire contained 34 measurement items and nine demographic and background questions. The measurement items were assessed using a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. The constructs included Perceived Vulnerability, Perceived Negative Learning Effects, Perceived Severity, Self-Efficacy, Response Efficacy, Moral Intention, Attitude Toward Avoiding Plagiarism, and Moral Obligation. After collection, responses were coded and screened before inclusion in the final dataset. The deposited Excel file contains 1,240 valid cases. Each row represents one respondent and each column represents one survey variable. The variable names correspond directly to the item codes reported in the English questionnaire. Researchers can reproduce descriptive analyses and measurement-model assessments using the deposited dataset and questionnaire.