Artificial Intelligence in Education: Transforming Pedagogical Practices and Student Learning Outcomes
Trefwoorden:
Artificial intelligence in education, adaptive learning, personalized learning, AI-driven pedagogy, automated assessment, student engagement, intelligent tutoring systems, education technology, digital learning transformation, AI ethics in educationSamenvatting
The integration of artificial intelligence (AI) in education is reshaping traditional pedagogical practices, offering innovative solutions to enhance teaching efficiency, student engagement, and personalized learning. AI-powered tools such as adaptive learning systems, automated assessments, and intelligent tutoring systems provide educators with data-driven insights to refine instructional methods (Luckin et al., 2016). AI fosters individualized learning by analyzing student performance patterns and tailoring content accordingly, ensuring learners receive support aligned with their needs (Holmes et al., 2021). Additionally, AI facilitates automated grading, freeing educators to focus on pedagogical innovation and student interaction (Ng, 2020). However, ethical concerns regarding data privacy, algorithmic bias, and accessibility remain critical challenges (Selwyn & Facer, 2021).
AI's transformative role extends beyond primary and secondary education to higher education and professional training, where AI-driven analytics support student retention and curriculum optimization (Eynon, 2020). Despite its benefits, the digital divide persists, limiting AI's potential for equitable learning experiences (Tuomi, 2021). This study explores AI’s influence on pedagogical practices, its impact on student learning outcomes, and the challenges associated with its implementation. Addressing ethical and policy considerations is essential for maximizing AI’s positive contributions to education (Williamson, 2020).
