Abstract
Students' perspectives on using generative artificial intelligence (AI) chatbots and machine learning are crucial in shaping the design, development, and implementation of their learning projects across various disciplines. Cognitive thinking, a key aspect of AI-related machine learning, aims to replicate human intelligence and behavior. However, the relation between cognitive thinking and knowledge acquisition is not always clear. Therefore, it is essential for students to engage in higher-order thinking, which allows them to critically analyze diverse viewpoints, assess their relevance, and understand the complex relationship between cognitive thinking and knowledge acquisition. This empirical study investigates the role of higher-order thinking skills, such as problem-solving, critical thinking, and creativity, in the relationship between academic achievements and attitudes toward machine learning technologies using generative AI chatbots. Four hundred sixteen undergraduate students (n = 416) from diverse academic backgrounds voluntarily took part in a project, in which they designed and developed generative AI chatbots in media and information literacy courses. The findings indicate that creativity mediated the relationship between academic achievements and attitudes toward machine learning, but its moderating impact was not significant. Problem-solving and critical thinking did not show significant mediating effects on attitudes toward machine learning, while they showed significant moderating effects in the connection between academic performance and attitudes toward machine learning. This study contributes by elucidating the interrelationships between students’ higher-order thinking skills, academic performance, and attitudes on the use of AI and machine learning technologies. By highlighting the mediating role of creativity and the moderating effects of problem-solving and critical thinking, this study offers a deeper understanding of how these skills shape students' perceptions of AI. The findings have significant implications for educational practices, suggesting that fostering higher-order thinking skills is crucial in preparing students to embrace AI and machine learning technologies.