I’m included this link as the idea of player and team assessment in professional sports has begun to change. I just find this a fascinating topic in how our society is seeing a shift in how we evaluate in general including in the realm of professional sports. In the past player evaluation was done by experts who would watch and make a decision – the process is very subjective. Analytics provide ways to quantify in numbers what we see happen on the ice or field. The same goes for teams. While at the end of the day the score is what matters, analysts have found metrics to identify keys to long term success for teams as well.
Not all learning analytics are the same. Discover how proactive learning analytics help you influence and improve ongoing learning processes by predicting the future and creating recommendations for action. Identify the 4 key elements that will determine the success of your analytics journey.
This presentation explores shortcomings of learning analytics for the wide adoption in educational organisations. It is NOT about ethics and privacy rather than focuses on shortcomings of learning analytics for teachers and students in the classroom (micro-level).
This pilot project collects problems and metrics/datasets from the AI research literature, and tracks progress on them. You can use this notebook to see how things are progressing in specific subfields or AI/ML as a whole, as a place to report new results you've obtained, as a place to look for problems that might benefit from having new datasets/metrics designed for them, or as a source to build on for data science projects. At EFF, we're ultimately most interested in how this data can influence our understanding of the likely implications of AI. To begin with, we're focused on gathering it.
M. Ferrari Dacrema, P. Cremonesi, and D. Jannach. Proceedings of the 13th ACM Conference on Recommender Systems, page 101–109. New York, NY, USA, Association for Computing Machinery, (2019)
A. Said, E. Zangerle, and C. Bauer. Proceedings of the 17th ACM Conference on Recommender Systems, page 1221-1222. New York, NY, USA, ACM, (September 2023)