The successful implementation of effective data governance in universities is crucial in complementing the massive information technology (IT) developments in higher education institutions globally. Hence, to identify the enablers of IT governance, this study examined the effects of knowledge value, knowledge-oriented culture, and knowledge-sharing process on the integration of IT governance in the curriculum and the latter’s effects on academic performance and perceived employability among university students in Saudi Arabia. We used a cross-sectional approach to collect quantitative data from 280 university students and employed structural equation modelling and partial least squares to conduct the data analysis. Our results confirmed the significant positive effects of knowledge value and the knowledge-sharing process on IT governance, along with a positive significant effect of IT governance on academic performance and perceived employment. Moreover, the results revealed a direct, positive, and significant effect of academic performance on perceived employment, as well as the significant mediating effects of IT governance and academic performance between these two. Apart from extending the relevant literature, this study offers several policy implications.

This study investigates the role of metacognitive awareness in shaping students’ adoption of artificial intelligence (AI) tools for learning within the framework of the Technology Acceptance Model (TAM). Data were collected from 236 students at the University of Ha’il, and structural equation modeling (SEM) was employed to examine the relationships among metacognitive awareness, perceived usefulness (PU), perceived ease of use (PEU), and behavioral intention (BI). The findings indicate that metacognitive awareness has significant positive effects on both PU and PEU. In turn, PU and PEU significantly influence students’ BI to use AI tools for learning, with PU emerging as the stronger predictor. However, metacognitive awareness does not have a significant direct effect on BI. These results suggest that students’ intention to use AI tools is primarily driven by their perceptions of usefulness and ease of use, while metacognitive awareness plays an important role in shaping these perceptions. The study extends the Technology Acceptance Model by positioning metacognitive awareness as an upstream cognitive factor that enhances students’ evaluation of AI technologies in educational contexts. The findings offer practical implications for higher education institutions, emphasizing the importance of developing students’ metacognitive skills to improve their engagement with AI tools. By fostering students’ ability to reflect on and regulate their learning processes, educators can enhance the perceived value and usability of AI technologies, thereby supporting their effective integration into learning environments.