Exploring the Impact of Learners’ Demographic Characteristics on Course Completion and Dropout in Massive Open Online Courses

Abstract

MOOCs (Massive Open Online Courses) have the potential to change education by offering high-quality online courses in a variety of disciplines. However, just a few studies have investigated the impact of MOOC students' demographics on their completion rates. In this research, we investigate the impact of demographic features of learners in the completion and dropping rate of MOOCs. The data from a survey is used in this study to determine which learner demographic features may have an impact on MOOC completion and dropout. The data was analyzed using Chi-square test.The findings demonstrate that four factors, including gender, marital status, age, and educational level, have no impact on degree of MOOC completion. It was also discovered that marital status, age, and educational level, have no effect on MOOC dropout. However, we discovered a statistically significant link between gender and MOOC dropout (χ2 = 6.347, df = 1, p = 0.012). These results can be considered in future instructional initiatives.

Predicting Dropout in Programming MOOCs through Demographic Insights

“…The current work also supports most of the previous findings regarding gender, indicating that this variable has no significant impact on the completion/dropout rate [36,[45][46][47]49], although studies showing different results also exist. In [3] authors claim that female participants are more likely to drop science courses, while the results of [29,37] suggest that females are generally more likely to drop out, no matter the course topic.…”

“…Looking at the respective demographic variables considered, our results-in contrast to some prior works [36,46], but in line with [3,16,28,29,37,45,47]-show that age could be used as a predictor of course completion or dropout. In our case, however, older participants (25 or more years old) were less likely to complete the course than younger learners, which is in line with [28,29] but contradictory to the remaining studies, which indicate older students are more successful [3,37,45,47].…”

“…Our findings concerning the level of education support those presented in [28,37,45,48], showing that this feature can also be used as a course completion predictor but, in contrast to those reports, our case indicates that higher education of participants decreases the completion probability. There are also studies which have found that this variable is not significant in relation to dropout [36,46].…”

“…Table 1 lists identified literature sources that took into account demographic predictors influencing the dropout/completion rate in MOOCs and online courses. [34] 597,692 * X X X E3, U1, U3, U5, U8 [36] 379 X X X X C1, C2, U4 [45] 2338 X X X X X D9 [37] 67,333 X X X X A1, A4, H1, U5, U6, U7 [46] 79 X X X D10 [30] 32,593 ** X X X X B9, D1, D11, E4, U1, U2, U7 [27] Unspecified X X X X X D2-D8, H1, S1, S2 [3] 668,017 *** X X X C1, U1, U5, U9, U11 [47] 624 X X X X X A3, A4, D6, D9, H3 [28] 32,593 ** X X X X D1, D11, E4, U1, U2, U7 [38] 1069 X X X X A4, H1, H4, S4, S5 [48] 1038 X X X A3, A4, H1, S4, U11 [29] 14,791 X X X D10, S2, U7, U9, U11 [49] 154,763 X X X D9, U1, U7, U9, U14 * HarvardX, ** OULAD, *** XuetangX.…”