# A Domain-Driven Framework to Analyze Learning Dynamics in MOOCs through Event Abstraction
## 5 Case Study: Successful Student Sessions in Coursera
### Discussion  
First and foremost, the findings indicate that students' behavior evolved throughout the course, as they were initially hesitant to evaluate themselves and preferred to view the content rather than assess their level of knowledge. The situation changed as participants progressed through the course, with 25% of the total number of events reported in the log resulting in completed assessments, either for the first time or by redoing a previously completed assessment. This shows that students' dedication to the subject grew as the course continued. According to the case analysis performed, the most frequent variants were of a single activity, and the longest sequences typically featured activities of the same type (e.g., Progressing and Echoing or Skimming and Retaking) indicating a student's purpose when carrying out a MOOC session. This reinforces [8] findings that effective learners typically focus their session time on a single learning resource (assessments, lectures, etc. ), with the focus shifting from session to session. It is is also consistent with [39] research on study patterns, where it was discovered that a sizeable portion of learners in the MOOC focus their time on a specific task, such as viewing videos or submitting an assignment, and with [5; 21], which recognizes that the most common interaction patterns are associated with the use of a single type of resource (video-lecture only and assessment-summative only, respectively). Additionally, this is in line with the most common learning tactics  
Figure 11: Z-scores of the amount of activities for each cluster. reported in [4; 6], where content-only and assessment-only tactics account for a considerable portion of the presented sample. Our research builds on these findings by distinguishing between first-time and re-engagement with content and assessments. Excluding students who dropped out of the course from the analysis allowed for the description of behaviors that successful students commonly display. From the five clusters obtained, four types of sessions were identified: Short sessions with a specific goal (Cluster 1), long sessions in which the student moves through the course sequence in an orderly fashion (Cluster 4), sessions associated with Retaking-Skimming dynamics (Cluster 3), and sessions with content search and repetition (Cluster 2). The clusters obtained are akin to those reported in [8], except for the two associated with No activity and Drop out, which are not present in our analysis. Furthermore, the patterns reported here are aligned with the activity patterns outlined in [34] for successful students and in [19] for the cluster researchers named _\"Achievers\"_. One of the unexpected findings in this study was that the Skimming dynamic was the most common variant, accounting for 26.7% of the high-level log. This could indicate the need to refine this dynamic because the review of an unfinished assessment could be the result of several factors, including: reviewing the difficulty of the content to be assessed in preparation for a serious attempt to complete it; reviewing mistakes made in previous attempts; and using the questions as learning examples, among others. Particularly in a programming course, this could be related to the necessity to check the code's syntax or to better understand some control flow structure or data type. It is worth looking into the possibilities of obtaining more precise information from MOOCs in order to determine the actual objectives behind these unfinished assessment attempts. One method could be to investigate how the variants that incorporate Skimming connect to the content being viewed. Another approach is to contrast with external data, such as questionnaires, to uncover patterns underlying the skimming activities in order to describe more precise dynamics. This research illustrates how a domain knowledge-based abstraction enables the description of student-MOOC interactions that would not be possible without this transition from low to high level.