Abstract

The purpose of this research study is to explore insights to create more contextual lecturer performance indicators (LPIs); and to gain a fairer and more useful evaluation tool for lecturers in the online environment during the COVID-19 pandemic. This significant change in conditions has forced higher education to understand the new requirements, especially of lecturers, who have played a central role in creating engaging moments for students in online classes. This study adopts a qualitative approach, based on the need for a more in-depth exploration of new phenomena. It explores students’ daily lives in class, which were expressed through social media, and gains further understanding through in-depth interviews with students and lecturers. The results indicate that most of the items taken from the Social-Task-Technology-Fit (STTF) framework remain the same; there are not many changes compared to the era before the pandemic. However, some aspects have new meanings that need to be revisited to capture the lecturers' performance in the new context. Three new themes emerged from the exploration study which have never been discussed in previous studies on LPIs for online teaching, especially in abnormal conditions such as a pandemic. The first theme concerns the variations in digital literacy of lecturers and the implications for lecturers' performance. The second theme is the dynamic ratio of social versus task activities, which implies the need to focus on academic (task-oriented) or non-academic (social) tasks. The third theme is the degree of controllability of each performance. This study provides awareness of the importance of weighting in evaluating lecturer performance, especially when not all lecturers are digitally literate, not all factors are controllable, and the ratios between social versus task requirements are not the same. These weighted evaluations have never been discussed in previous studies, which mainly used quantitative surveys. In addition, these insights can also be applied to online learning beyond the pandemic. The study results can be used by higher education information management to design more contextual LPIs for the early detection of issues with lecturer performance.

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