Students’ Attitudes towards the Use of Generative Artificial Intelligence in Higher Education Learning
This dataset contains anonymized responses from a questionnaire investigating higher education students' attitudes toward the use of Generative Artificial Intelligence (GenAI) in learning. The survey examines students' perceptions, experiences, and acceptance of GenAI technologies as learning support tools, together with their views on personalization, engagement, learning effectiveness, decision-making support, ethical concerns, and future educational applications. The questionnaire was administered to university students enrolled in higher education programs. All responses were collected anonymously and contain no personally identifiable information. The dataset includes: - demographic characteristics of respondents (e.g., gender, age group, field of study, academic level); - previous experience with Generative AI tools; - frequency and purpose of GenAI use in learning; - Likert-scale responses measuring attitudes toward GenAI-assisted learning; - perceived educational benefits and challenges; - perceptions of personalization, engagement, and decision-support capabilities; - concerns related to academic integrity, privacy, bias, and over-reliance on AI; - coding rules for questionnaire variables. The dataset is intended to support research on artificial intelligence in education, technology acceptance, digital learning, educational decision support, and cognitive computing. It may also be used for statistical analysis, machine learning, educational data mining, structural equation modeling, and comparative studies across institutions or countries.