Teaching Tip: developing an intercollegiate Twitter forum to aid student exam study and the development of digital professionalism

#VetFinals has been developed as a novel online Twitter teaching event designed to support intercollegiate veterinary teaching using social media. Previous studies in other fields have suggested that Twitter use within universities may have benefits for undergraduate education. This “teaching tip” paper describes a project using Twitter to host online exam study sessions. The project has been a highly successful collaborative effort between the Royal Veterinary College and Nottingham Veterinary School in the UK. Over 4 years, the #VetFinals project has developed into a long-term, self-sustaining enterprise. This initiative provides a semi-structured means for student exam preparation with direct real-time input from a faculty member. It also creates a network of peers both horizontally across institutions and vertically throughout year groups. Based on similar initiatives in other disciplines, an anticipated outcome of this project was to contribute to student online professionalism. This could help address the veterinary community's recently highlighted problems with professional conduct and appropriate use of social media. Analysis of the success of this endeavor will be available in a future publication

"Twitter Archeology" of Learning Analytics and Knowledge Conferences

The goal of the present study was to uncover new insights about the learning analytics community by analyzing Twit-ter archives from the past four Learning Analytics and Knowl-edge (LAK) conferences. Through descriptive analysis, in-teraction network analysis, hashtag analysis, and topic mod-eling, we found: extended coverage of the community over the years; increasing interactions among its members regard-less of peripheral and in-persistent participation; increas-ingly dense, connected and balanced social networks; and more and more diverse research topics. Detailed inspection of semantic topics uncovered insights complementary to the analysis of LAK publications in previous research