Analysis of online college teaching data before and after the COVID-19 epidemic

KONG Xiao; LIU Naijia; ZHANG Menghao; XU Mingwei

doi:10.16511/j.cnki.qhdxxb.2020.21.017

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Journal of Tsinghua University(Science and Technology) ›› 2021, Vol. 61 ›› Issue (2) : 104-116. DOI: 10.16511/j.cnki.qhdxxb.2020.21.017

SPECIAL SECTION: COVID-１９

Analysis of online college teaching data before and after the COVID-19 epidemic

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Abstract

The corona virus disease 2019 (COVID-19) pandemic has led Chinese universities to turn to online teaching. Several researchers have used surveys to study the characteristics and challenges of online teaching. However, these surveys inevitably included subjective bias and sample limitations. This study analyzed the server logs of the Tsinghua University course selection system during online teaching with comparisons with those of the past two years. Since all students must visit the course selection system every semester, the server logs track the students' learning and living habits. After data cleaning, visualization and analysis, the logs show that over 98% of the sessions came from outside the campus during the epidemic. The number of visits to the system decreased by 25%-47%, the number of visits originating from mobile devices decreased by 7%, and the average browsing time per visit declined by 8%. Thus, this study shows evidence that online teaching leads to a notable decline in student engagement with the system. This study then suggests that colleges pay more attention to the student's productivity and engagement, thereby improving the quality of teaching.

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Web servers / corona virus disease 2019 (COVID-19) / online teaching / student engagement

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KONG Xiao, LIU Naijia, ZHANG Menghao, XU Mingwei. Analysis of online college teaching data before and after the COVID-19 epidemic[J]. Journal of Tsinghua University(Science and Technology). 2021, 61(2): 104-116 https://doi.org/10.16511/j.cnki.qhdxxb.2020.21.017

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