Due Tomorrow, Do Tomorrow: Measuring and Reducing Procrastination Behavior Among Introductory Physics Students in an Online Environment

This work is focused on the measurement and prevention of procrastination behavior among college level introductory physics students completing online assignments in the form of mastery-based online learning modules. The research is conducted in two studies. The first study evaluates the effectiveness of offering students the opportunity to earn a small amount of extra credit for completing portions of their homework early. Unsupervised machine learning is used to identify an optimum cutoff duration which differentiates taking a short break during a continuous study session from a long break between two different study sessions. Using this cutoff, the study shows that the extra credit encouraged students to complete assignments earlier. The second study examines the impact of adding a planning-prompt survey prior to a string of assignments. In the survey, students were asked to write a plan for when and where they would work on their online homework assignments. Using a difference in differences method, a multilinear modeling technique adopted from economics research, the study shows that the survey led to students completing their homework on average 18 hours earlier and spreading their efforts on the homework over time significantly more. On the other hand, behaviors associated with disengagement, such as guessing or answer-copying, were not impacted by the introduction of the planning prompt. These studies showcase novel methods for measurement of procrastination behavior, as well as evaluating the effectiveness of the designed interventions to help students avoid waiting until the last minute to make progress on assigned tasks

Interdisciplinarity in Smart Sustainable City education: exploring educational offerings and competencies worldwide

More and more higher education institutions are offering specialized study programs for current and future managers of Smart Sustainable Cities (SSCs). In the process, they try to reconcile the interdisciplinary nature of such studies, covering at least the technical and social aspects of SSC management, with their own traditionally discipline-based organization. However, there is little guidance on how such interdisciplinarity should be introduced. In order to address this gap, this paper identifies 87 SSC-related study programs from around the world and analyzes their disciplinary and interdisciplinary coverage. The analysis classifies programs and competencies, the former using text mining and clustering algorithms, the latter using Bloom’s taxonomy and correlation analysis

Technology-enhanced Personalised Learning: Untangling the Evidence

Technology-enhanced personalised learning is not yet common in Germany, which is why we have tasked scientists with summarising the current status of international research on the matter. This study demonstrates the great potential of technology in implementing effective personalised learning. Nevertheless, it has not been assessed yet whether the practical implementation actually works: Even in countries such as the U.S., which lead the way in using techology in classroom settings, hardly any evaluation studies have been done to prove the effectiveness of technology-enhanced personalised learning. In the light of the above, the authors make recommendations for actions to be taken in Germany to make best use of the potential of technology in providing individual support and guidance to students