While the DataChallenge@LAK19 Workshop will give anonymized data to researchers, sometimes it may be possible to link the data that was intended to be anonymized back to individuals.
You agree, as a condition of using the DataChallenge@LAK19 datasets, to the following terms and conditions meant to ensure that student data remains anonymous:
- The dataset is only to be used for the purpose of this workshop which is to support educational and learning activities.
- After the workshop has finished, the dataset is to be deleted from all systems.
- You will not use the data to discover personally identifiable information about the individual students in the study.
- If you discover something that can identify students personally, you will both delete it from your computer, and inform the DataChallenge@LAK19 Workshop Organizers ( dclak19 [at] gmail [dot] com ) of this immediately. You will work with the the DataChallenge@LAK19 Workshop Organizer to take steps to make sure data that is supposed to be anonymous is in fact anonymous.
- You agree to not give this data to a third party.
- You agree to not commercialize this data or use it in a malicious or unintended manner.
- When describing the dataset provided by this workshop you will cite the following:
Hiroaki Ogata, Chengjiu Yin, Misato Oi, Fumiya Okubo, Atsushi Shimada, Kentaro Kojima, and Masanori Yamada, E-Book-based learning analytics in university education, Proceedings of the 23rd International Conference on Computer in Education (ICCE 2015) pp.401-406, 2015.
Brendan Flanagan, Hiroaki Ogata, Integration of Learning Analytics Research and Production Systems While Protecting Privacy, Proceedings of the 25th International Conference on Computers in Education (ICCE2017), pp.333-338, 2017.