Analysis of the readiness of students in automotive engineering education at Universitas Negeri Semarang to engage in learning with generative AI

Abstract

The readiness of Automotive Engineering Education students at Universitas Negeri Semarang (UNNES) to engage in Generative AI-based learning is examined in this study. A survey approach was employed, involving 220 respondents, and data were analyzed across four key areas: learning facilities, knowledge, technical skills, and psychological preparedness. The time frame for this survey was November 2024. Before use, the questionnaire was tested for content validity and reliability. r table for a sample of 30 students, and the alpha value of 0.05 is 0.362. All r product moment values ​​for each question are ​​above 0.362, meaning that all the questions are valid. The Cronbach's alpha value is 0.821 (≥ 0.600), which shows that the data are reliable. The data were examined via a quantitative descriptive method. Students' answers to the questions are then examined and interpreted graphically. It was found that while adequate devices, such as 5G-enabled smartphones (97.73%) and functional laptops (95.45%), are possessed by most students, internet access outside campus remains a significant challenge, with only 57.27% having Wi-Fi at home. A solid understanding of Generative AI applications is demonstrated by the students, but knowledge of ethical use is lacking, with only 20.45% strongly agreeing that AI ethics are understood. Technical readiness in using Generative AI for content creation and modification is shown, but ethical application remains limited, as only 8.64% strongly agree they apply ethics. High psychological readiness to use Generative AI responsibly is exhibited by the students, including verifying content accuracy (69.55%) and safeguarding personal data (75%). The need for enhanced ethics education and improved internet infrastructure is highlighted to support the effective and responsible integration of Generative AI in education.

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