Dataset of AI adoption usage, expectations, attitudes, perceptions, and motivations for learning in higher education

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-09-25 DOI:10.1016/j.dib.2025.112106

Zaky Farid Luthfi , Wibowo Heru Prasetiyo , Beti Indah Sari , Atri Waldi , Arief Muttaqiin

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引用次数: 0

Abstract

This dataset presents the use of artificial intelligence (AI) among university students as a tool for completing academic tasks. A total of 535 data points were collected from students participating in an online survey conducted across 152 universities and 20 provinces in Indonesia. The dataset includes demographic information, educational level, field of study, and the types of AI tools used. It also captures students' use of AI, including performance expectations, challenges in using AI, attitudes toward AI use, perceptions of AI, and motivational intent to use AI. All collected data are described according to the results of descriptive statistical analysis, which aims to both describe and explore the relationships between the constructs. Moreover, this dataset offers significant potential for reuse and further comparative studies for researchers interested in the application of AI in academic contexts. It can serve as a reference for future investigations into the potential determinants influencing AI use in higher education settings. Potential applications include the development of advanced AI tool features tailored to students' specific characteristics and usage priorities.

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高等教育中人工智能的采用、使用、期望、态度、看法和学习动机数据集

本数据集展示了大学生使用人工智能（AI）作为完成学业任务的工具。共有535个数据点从参与在线调查的学生中收集，该调查在印度尼西亚的152所大学和20个省进行。该数据集包括人口统计信息、教育水平、研究领域和使用的人工智能工具类型。它还捕获了学生对人工智能的使用，包括绩效期望、使用人工智能的挑战、对人工智能使用的态度、对人工智能的看法以及使用人工智能的动机意图。所有收集到的数据都是根据描述性统计分析的结果进行描述的，描述性统计分析的目的是描述和探索结构之间的关系。此外，该数据集为对人工智能在学术环境中的应用感兴趣的研究人员提供了重用和进一步比较研究的巨大潜力。它可以作为未来调查影响人工智能在高等教育环境中使用的潜在决定因素的参考。潜在的应用包括根据学生的具体特点和使用优先级开发先进的人工智能工具功能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.