Perez-Ortiz, M;
Dormann, C;
Rogers, Y;
Bulathwela, S;
Kreitmayer, S;
Yilmaz, E;
Noss, R;
(2021)
X5Learn: A Personalised Learning Companion at the Intersection of AI and HCI.
In:
Proceedings of the 26th International Conference on Intelligent User Interfaces.
(pp. pp. 70-74).
ACM: Association for Computing Machinery: New York, NY, USA.
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Abstract
X5Learn (available at https://x5learn.org ) is a human-centered AI-powered platform for supporting access to free online educational resources. X5Learn provides users with a number of educational tools for interacting with open educational videos, and a set of tools adapted to suit the pedagogical preferences of users. It is intended to support both teachers and students, alike. For teachers, it provides a powerful platform to reuse, revise, remix, and redistribute open courseware produced by others. These can be videos, pdfs, exercises and other online material. For students, it provides a scaffolded and informative interface to select content to watch, read, make notes and write reviews, as well as a powerful personalised recommendation system that can optimise learning paths and adjust to the user's learning preferences. What makes X5Learn stand out from other educational platforms, is how it combines human-centered design with AI algorithms and software tools with the goal of making it intuitive and easy to use, as well as making the AI transparent to the user. We present the core search tool of X5Learn, intended to support exploring open educational materials.
| Type: | Proceedings paper |
|---|---|
| Title: | X5Learn: A Personalised Learning Companion at the Intersection of AI and HCI |
| Event: | IUI '21: 26th International Conference on Intelligent User Interfaces |
| ISBN-13: | 9781450380188 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3397482.3450721 |
| Publisher version: | http://dx.doi.org/10.1145/3397482.3450721 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Future User Interfaces, User Modeling, Artificial Intelligence, Recommender Systems, Open Education, Human Computer Interaction, Information Retrieval |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10128405 |
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