There has been much debate on the issue of whether online learning was better than traditional education and vice-versa over the past decade. Over time, the concept of blended learning became quite the norm, especially within traditional universities who could no longer turn a blind eye to the educational revolution brought about by information and communication technologies. While the pace of technology integration in universities generally varies in pace, the world has recently experienced a massive uptake, albeit in an unplanned and mostly disorganized manner, of e-learning technologies due to the Covid-19 pandemic. Researchers have emphasized on the quality of online courses from a perspective of learner achievement in terms of student satisfaction, engagement and performances. In this paper, we analyze student feedback and report the findings of a study of the relationships between student satisfaction and their engagement in an online course with their overall performances. The module was offered online to 844 university students in the first year across different disciplines, namely Engineering, Science, Humanities, Management and Agriculture. It was assessed mainly through continuous assessments and was designed using a learning-by-doing pedagogical approach. The focus was on the acquisition of new skills and competencies, and their application in authentic mini-projects throughout the module. Student feedback was coded and analyzed both from a quantitative and qualitative perspective. The association between satisfaction and engagement was significant and positively correlated. On the other hand, there was a weak but positive and significant correlation between satisfaction or engagement with their overall performances. We further observed that students were generally very satisfied with the learning design philosophy, irrespective of their performance levels. Students, however, reported issues related to lack of tutor support and experiencing technical difficulties across groups. The findings raise important implications for institutional e-learning policy making. The factors that are important relate to the object of such policies, learning design models, personalized support, distributed virtual learning through synchronous interaction, and learning analytics.