Vận dụng trí tuệ nhân tạo trong xây dựng quy trình đánh giá năng lực tự chủ và tự học của học sinh trung học phổ thông

Tóm tắt

Self-regulation and self-directed learning are important competencies of students in the context of educational reform. However, assessing these competencies remains challenging due to the lack of suitable assessment procedures and measusrement tools. This study proposes an assessment process for autonomous and self-directed learning among high school students, with the support of artificial intelligence in developing a quantitative scale and processing data. The scale consists of six dimensions representing component competencies, measured by items designed on a four-point Likert scale. A survey of 592 high school students shows that most students achieved fairly good and good levels of these competencies. Regression analysis identifies three main factors influencing autonomous and self-directed learning, including self-regulation, career orientation, and adaptability. The findings highlight the role of component competencies in developing students’ learning autonomy and suggest the potential use of artificial intelligence in competency assessment and teaching innovation.