Data-driven Decisions of Higher Education Instructors in an Era of a Global Pandemic

被引:0
|
作者
Usher, Maya [1 ]
Hershkovitz, Arnon [1 ]
机构
[1] Tel Aviv Univ, Tel Aviv, Israel
来源
ONLINE LEARNING | 2023年 / 27卷 / 02期
关键词
data-driven decisions; educational data; online teaching; higher education; instructor perspective; LEARNING ANALYTICS;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
The impact of the COVID-19 pandemic on the higher education sector has been overwhelming, with emergency responses that have affected decision-making processes. Yet, our understanding of higher education instructors' perspectives regarding the process of data-driven decisions, especially in times of emergency, is still limited. We aimed at characterizing the types of data-driven decisions that higher education instructors have made in their courses. This was done while asking the instructors to reflect upon a face-to-face (F2F) course that was suddenly shifted to emergency remote teaching (ERT), due to the COVID-19 pandemic outbreak. Taking a qualitative approach, data were collected via an open-ended online questionnaire distributed among 109 higher education instructors from different countries. The findings suggest that the instructors mentioned a wider range of data sources, and a wider range of data-driven decisions while referring to the ERT mode, compared with their F2F instruction. In F2F teaching, the instructors mostly provided students with real-time educational assistance. In ERT, the instructors mostly adjusted the course requirements, promoted collaboration among students, and offered them social and emotional support.
引用
收藏
页码:170 / 186
页数:17
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