Developing and validating an artificial intelligence ethical awareness scale for secondary and university students: Cultivating ethical awareness through problem-solving with artificial intelligence tools

Although there is growing attention to artificial intelligence (AI) ethics education with the rapid surge of AI technology, little research has explored the use of problem-solving to cultivate students' AI ethical awareness. To address this gap, this study developed a scale to multidimensionally measure AI ethical awareness and cultivated students' AI ethical awareness through problem-solving using AI tools within an AI literacy course. A total of 573 Hong Kong secondary and university students participated in a 14-h course. Data was collected through the AI Ethical Awareness Scale (AIEAS) questionnaire and students' self-reflective writings. The AIEAS framework, encompassing three dimensions, was based on the Belmont Report principles of human autonomy, beneficence, and fairness. Confirmatory factor analysis (CFA) supported this three-factor structure, with nine items retained. Multigroup CFA results demonstrated strong measurement invariance across gender, education level, and programming knowledge. All Cronbach's alpha and omega coefficient values exceeded 0.70, indicating satisfactory internal consistency and fair temporal stability. Furthermore, students' ethical awareness showed a significant improvement following the course intervention. This study not only provides a robust measure for researchers and practitioners to assess students' ethical awareness through behavioural engagement but also demonstrates the necessity of implementing an education course for cultivating ethical awareness through integrating experience and reflection.