Abstract:

Data science is currently one of the world’s most in-demand jobs. Employers don’t only require highly cognitive skilled people to fill these positions but are also looking for people who have soft skills. Self-efficacy and time management are some of the important skills for this fast-paced career that is often deadline driven and where procrastination cannot be tolerated.

Universities have access to student data on their learning management systems that can be utilised to determine how well their data analytics students are managing their time by measuring their procrastination behaviour and its effect on their performance. This study combines systems thinking and educational analytics to design a dashboard that may assist educators to recognise vicious cycles of procrastination in their students. This will enable educators to intervene and guide students to break out of this vicious cycle and rather move to a virtuous cycle of self-efficacy.

The times at which students submitted their assignments were used to track students’ procrastination behaviour by comparing these times to the times when the assignments were due. Students who submitted early (before the deadline) were more likely to obtain a distinction, whereas those who submitted late, were more likely to fail. Different options and scenarios were explored on how these data can be represented on a dashboard to enable educators to detect possible procrastination behaviour that should be addressed.

Keywords:

Data science, dashboard, feedback loops, learning analytics, learning management system, procrastination, self-efficacy, systems thinking, time management.