Năng lực thiết kế học tập thích ứng với trí tuệ nhân tạo của giảng viên: Nghiên cứu tại Đại học Cần Thơ - Lữ Quốc Vinh, Lữ Quốc Vinh; Nguyễn Ngọc Chi Lan, Nguyễn Ngọc Chi Lan; Nguyễn Ngọc Phương Thảo, Nguyễn Ngọc Phương Thảo; Nguyễn Minh Thư, Nguyễn Minh Thư (Tạp chí Giáo dục, 2026)
Currently, the rapid development of artificial intelligence (AI) places new demands on the learning design capabilities of university lecturers. This study uses a descriptive quantitative design to survey the AI-adaptive learning design capabilities of 215 lecturers at Can Tho University, based on a competency framework comprising five groups: learning activity design; assessment design; feedback and learning support; academic integrity assurance; and awareness and use of AI in teaching. Data were collected using a 5-level Likert questionnaire and analyzed using descriptive statistics with SPSS 20 software. The results show that the lecturers’ AI-adaptive learning design capabilities are generally high (overall average = 3.43/5), while capabilities related to assessment design and academic integrity assurance are limited. These findings provide a practical basis for adjusting course design and faculty training in the context of digital transformation in higher education.