Abstract
In every course, there are learners who successfully pass assessments and complete the course. However, there are also those who fail the course for various reasons. One of such reasons may be related to success in assessment. Although performance in assessments has been studied before, there is a lack of knowledge on the degree of variance between different types of learners in terms of scores and the number of resubmissions. In the paper, we analyse the performance in assessments demonstrated by non-completers and completers and by completers with different engagement levels and difficulty-resolving patterns. The data have been gathered from the Moodle statistics source based on the performance of 1065 participants, as regards their completion status, the number of attempts made per each programming task and quiz, and the score received per quiz. Quantitative analysis was performed with descriptive statistics and non-parametric tests. Non-completers and completers were similar in resubmissions per quiz, but the former, expectedly, made more resubmissions per programming task and received lower quiz scores. Completers made more attempts per task than per quiz. They could provide a correct solution with a few resubmissions and receive good scores already at a pragmatic engagement level. At the same time, the increased use of help sources in case of difficulties was also associated with a higher number of attempts and lower quiz scores received. The study may have implications in understanding the role of assessments in dropouts and how completers with different engagement and difficulty-resolving patterns cope with assessments.
Highlights
Comparing non-completers and completers for each of the six programming tasks, we found that, only in the last task, there was no difference in the average number of attempts (H = 3.306; p > 0.05)
While Chen et al [20] showed that completers in computer science courses make more submissions in problem sets, our results indicated that non-completers made on average more attempts per programming task than completers
We aimed to analyse the performance of non-completers and completers in assessments in a massive open online course (MOOC) on programming
Summary
Participation in a massive open online course (MOOC) usually does not require any prerequisite or predefined levels from learners. This aspect makes MOOCs attractive to self-directed learners who are basically interested in improving their knowledge in a course field [1]. Repeated attempts (resubmissions) with improving solutions allow learners to have higher grades in MOOCs [8,9]. In the context of learning programming, Auvinen [10] theorised that a student makes a high number of attempts because exercise is difficult to solve on the first attempt and a student makes a low number of attempts because the solution is carefully checked before submission. Numerous attempts, even without getting the right solution, demonstrate a student’s resilience—a key feature for programmers [11]
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