As access has grown to online courses in the form of MOOCs (Massive Open Online Courses), the language barrier has become an important issue for users worldwide. Machine translation (MT) appears to offer an alternative or complementary solution to existing forms of MOOC translation. Very little attention has been paid, however, to the use and utility of MT for MOOC content. The main goal of this research is to test the impact machine-translated subtitles have on Chinese viewers’ reception of MOOC content. We are interested in whether there is any difference between viewers’ reception of raw machine-translated subtitles as opposed to fully post-edited machine-translated (PEMT) subtitles and human-translated (HT) subtitles. Based on an eye-tracking experiment conducted at two Chinese universities and survey methods, we show that participants who were offered full PEMT subtitles scored better overall on our reception metrics than those who were offered raw MT subtitles. HT subtitles, on the other hand, did not necessarily lead to better reception as expected; in contrast, the participants who were offered HT subtitles performed the worst in some of our reception metrics.