Data on teacher responsibility, generative AI-supported learning effectiveness, fellow student collaboration, and students’ psychological well-being in higher education
Description
This dataset contains survey data collected from 1,558 university students in Vietnam on teacher responsibility, generative AI-supported learning effectiveness, fellow student collaboration, and student psychological well-being in higher education. The dataset comprises 37 variables, including 32 measurement items and five demographic variables. Teacher Responsibility (TR) is represented by 13 items (TR1–TR13), Generative AI-Supported Learning Effectiveness (ASLE) by four items (ASLE1–ASLE4), Fellow Student Collaboration (FSC) by four items (FSC1–FSC4), and Student Psychological Well-Being (SPW) by 11 items (SPW1–SPW11). Five demographic variables describe gender, type of university, year of study, major, and duration of regular generative AI use. All measurement items were assessed using a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. The dataset contains no missing values and no direct personal identifiers. It can be reused for measurement validation, PLS-SEM and other multivariate analyses, subgroup comparisons, cross-context comparisons, and further research on teacher-related resources, generative AI-supported learning, peer collaboration, and psychological well-being in higher education. The repository also provides the questionnaire used to generate the dataset, including an English-language version to facilitate replication and international reuse.
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Steps to reproduce
The dataset was generated using a self-administered questionnaire administered to university students in Vietnam. Respondents were instructed to select a recent course in which the lecturer assigned learning activities or in which generative AI/AI-supported learning tools, such as ChatGPT, Gemini, Copilot, chatbots, LMS, or e-learning tools, were used. They then evaluated the questionnaire statements based on their experience in that course. The questionnaire contained 32 measurement items representing four constructs: Teacher Responsibility (TR1–TR13), Generative AI-Supported Learning Effectiveness (ASLE1–ASLE4), Fellow Student Collaboration (FSC1–FSC4), and Student Psychological Well-Being (SPW1–SPW11). Responses were recorded on a five-point Likert scale from 1 = strongly disagree to 5 = strongly agree. Five additional variables captured gender, type of university, year of study, major, and duration of regular generative AI use. To reproduce the dataset structure, administer the accompanying questionnaire to an eligible university-student sample, code the responses according to the variable definitions provided in the questionnaire and data file, and retain one row per respondent. The deposited dataset contains 1,558 complete observations and no missing values. Measurement-model assessment may be reproduced using the item codes provided in the dataset.