Nội dung được dịch bởi AI, chỉ mang tính chất tham khảo
Những điều chúng ta có thể học từ việc sử dụng dữ liệu sinh viên trong phân tích hiệu suất trong bối cảnh giáo dục đại học?
Tóm tắt
Mục đích chính của bài báo là ước lượng hiệu suất của một trường đại học công lập lớn ở Italy bằng cách sử dụng dữ liệu ở cấp độ sinh viên cá nhân, mô hình hóa các biến ngoại sinh trong việc hình thành vốn nhân lực thông qua tiếp cận biên giới ngẫu nhiên không đồng nhất. Cụ thể, một hàm sản xuất cho giáo dục đại học đã được ước lượng với trọng tâm vào tình trạng không hiệu quả và các yếu tố xác định của nó, đồng thời xem xét rõ ràng vai trò do bối cảnh xã hội-kinh tế và quá trình giáo dục của sinh viên tạo ra. Bằng chứng thực nghiệm, dựa trên 48.338 sinh viên năm nhất, dẫn đến việc sử dụng dữ liệu cấp cá nhân nhằm kiểm soát phần thành tích học tập của sinh viên bị ảnh hưởng bởi các đặc điểm cá nhân và nỗ lực, cũng như phần do các nguồn lực hoặc tổ chức các hoạt động của tổ chức. Trong giới hạn của tính hợp lệ bên ngoài cho phép khi hoạt động chỉ trong một trường đại học duy nhất, điểm hiệu suất thu được từ việc sử dụng cả dữ liệu cấp cá nhân và dữ liệu cấp tổng hợp đều cung cấp một công cụ quan trọng cho trường đại học và các cấu trúc quản trị.
Từ khóa
#hiệu suất giáo dục đại học #dữ liệu sinh viên #phân tích hiệu suất #vốn nhân lực #yếu tố xác định hiệu suấtTài liệu tham khảo
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