Many students do not finish their introductory programming courses in higher education and it is difficult to identify why. While this thesis doesn’t concern itself with investigating drop outs, this fact motivated the authors to research if there was a correlation between problematic student work patterns and the students' success in the course.The aim of this thesis is to identify problematic student work patterns. To do this, we conducted a case study on the introductory programming course 1DV025 at Linnaeus University, focusing on quantitative data. This data was collected by developing an application which fetches student data from the GitLab repository of the course. After conducting statistical testing on the data, the results were analyzed in order to determine distinguishing traits that can be an indication of problematic student work patterns.The analysis uncovered that these do exist for some students that fail their examination assignments. Hopefully, the conclusions of this report can help teachers to recognize problematic student work patterns and apply preemptive actions accordingly.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-113828 |
| Date | January 2022 |
| Creators | Salo, Joel, Ekberg, Karl |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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