AI Article Synopsis
- - The master's program "Multiple Sclerosis Management" at Dresden International University adapted to the COVID-19 pandemic by shifting to online teaching formats, facilitating structured training for specialists.
- - A study analyzed a cloud-based digital hub for student collaboration and evaluations using the Gioia method and descriptive statistics, revealing its effectiveness in enhancing learning and interaction.
- - Despite pandemic-related challenges, students rated the program's courses positively, leading to a blend of successful online and in-person learning formats for future educational practices.
Article Abstract
Since 2020, the master's program "Multiple Sclerosis Management" has been running at Dresden International University, offering structured training to become a multiple sclerosis specialist. Due to the COVID-19 pandemic, many planned teaching formats had to be changed to online teaching. The subject of this paper was the investigation of a cloud-based digital hub and student evaluation of the program. Authors analyzed use cases of computer-supported collaborative learning and student evaluation of courses and modules using the Gioia method and descriptive statistics. The use of a cloud-based digital hub as a central data platform proved to be highly successful for learning and teaching, as well as for close interaction between lecturers and students. Students rated the courses very positively in terms of content, knowledge transfer and interaction. The implementation of the master's program was successful despite the challenges of the COVID-19 pandemic. The resulting extensive use of digital tools demonstrates the "new normal" of future learning, with even more emphasis on successful online formats that also increase interaction between lecturers and students in particular. At the same time, there will continue to be tailored face-to-face events to specifically increase learning success.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8393651 | PMC |
| http://dx.doi.org/10.3390/brainsci11081110 | DOI Listing |
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