Pleiotropic effects of GDF-15 to regulate nutritional status: perspectives from body composition to nutrition-related disorders.

The integration of artificial intelligence (AI) in Saudi Arabia's higher education sector supports the nation's 2030 Vision for Comprehensive Development. It plays a key role in changing the educational strategies and outcomes. Research shows that AI in Saudi higher education is still in its early stages but is considered an important reality for meeting future learning challenges in the country. The use of AI tackles significant educational issues by changing teaching methods, speeding up progress toward national development goals, and highlighting the need for students to gain the technical skills required to work with and develop AI technologies (). Stakeholders in Saudi higher education are aware of the potential of AI to improve teaching and learning experiences. They expect that it will also streamline administrative duties while promoting innovation. Despite(this), there is a sense of hope in the air about careers for any variety of learners and how AI can provide them with support infinitely long. Nevertheless, great attention should be paid to issues of privacy, security, and bias in AI's implementation, which could be damaging. Even knowing about AI integration must take into account technical, ethical, social, and educational factors for the responsible application of this technology to take root in academic circles (). For example, in academic fields such as architectural education, surveys show that while students are eager to adopt and familiarize themselves with AI tools, the faculty are hesitant. Some of this resistance stems from a worry that the AI (associated) might affect creativity. The two groups agreed that it is essential to include AI in future curricula. In order for AI To enhance and encourage creativity in architectural learning and teaching, it is suggested that students and educators participate in training and workshops related to AI skills (). In addition, data-driven approaches, such as machine learning and big data, signify the future of AI implementation, which can facilitate personalized learning and better decisions by institutions. Random Forest predictive models have been shown to be highly accurate and beneficial for the educational process in their uses. Nonetheless, realizing the benefits easily and sustainably will require overcoming challenges, such as high costs, privacy concerns, and a shortage of qualified personnel (). The acceptance of AI among students is influenced by usability factors. This refers to factors in digital learning platforms, such as LMS. There are factors that influence the perceived usefulness and PEU of the system. These include quality content, system navigability and interactivity, and instructional support. Given that LMS is still growing in Saudi higher education, improving these components can enhance students' engagement with AI-powered educational tools (). The Saudi architectural education case study provides a statement of students' enthusiasm vs. faculty's reluctance. Students demonstrated a high level of interest and understanding of the use of AI tools, whereas the faculty members were skeptical, fearing that excessive use of AI might undermine creativity and creativity phases, commonly known as “design shallowing,” where they choose to use AI-generated options instead of going through the design thinking process (). The rigidity of AI frameworks to limit creative thinking is also cited in a wider-scale study of AI in college education in relation to the applications of AI in teaching (). One of the strengths of RF is its ability to manage numerous variables, minimize overfitting, and pinpoint the most significant predictors of the problem, such as the number of units taken, grade in subjects, use of library, and frequency, which can then be used to inform interventions and allocation of resources (; ). In all Technology Acceptance Model (TAM) studies, Perceived Ease of Use (PEU/PEOU) reflects the ease with which users perceive a system to be learned and used by them. Generally, it is beneficial for enhancing attitudes, satisfaction, and intention to use AI-based e-learning (; ). AI supporting personal learning environments (PLE) has a significant influence on perceived ease of use and perceived usefulness, which consequently impacts attitude, satisfaction, and intention to use e-learning, which varies according to gender and learner type (). In a related study on AI-driven platforms, social learning networks and personal learning portfolios were shown to increase perceived usefulness and ease of use, and self-efficacy and innovativeness acted as moderators of intentions ().