Event Date & Time
This event is part of the CTLT Winter Institute, taking place from December 12-15, 2022.
Student Experience of Instruction (SEI) quantitative data consists of responses on a Likert-type scale (most commonly a 5- or 7-point scale). For many years, the mean (average) and standard deviation were used to summarize and present quantitative data in instructor reports. However, more recently, UBC began using different metrics to report student experience of instruction survey results. The reported metrics include: the interpolated median, percent favorable and measure of dispersion suitable for ordinal data.
This session will introduce the new SEI metrics. Participants will have the opportunity to discuss, in small groups, how to interpret the summary stats in instructor reports.
- Abdel Azim Zumrawi, Statistician, Planning and Institutional Research
- Jovy Eramela, Support Analyst, PAIR
- Tizitash Mohammed, Programmer Analyst, PAIR
- Gavin Yap, Research analyst, PAIR
This event will be hosted on Zoom.