Zeeguu is a project that aims to support learners of foreign languages accelerate the acquisition of their vocabulary by a three-pronged approach:
- finding relevant articles on the net for them
- supporting their reading with translation and pronunciation support
- strengthening retention with the use of automatically and personally generated vocabulary exercises
The architecture of Zeeguu includes both a browser extension and a web application that communicate with each other.
As We May Study: Towards the Web as a Personalized Language Textbook
- in this paper we introduce the project
- we report on a study of using it in a highschool French class in the Netherlands
- students love and take advantage of the chance of reading on the topics that they like
Bootstrapping an ubiquitous monitoring ecosystem for accelerating vocabulary acquisition
- a paper that presents a generic ecosystem architecture of which Zeeguu is an instantiation
Analyzing user interactions to estimate reading time in web-based L2 reader applications - paper with Nora Hollenstein - we describe how one can estimate reading time on the web when they study free reading in the wild
- better and more meaningful progress feedback
- better and more precise time-measurement on the platform (include exercises, include reviewing words, etc.)
- more diverse exercises: e.g. reorder parts of sentence into whole with drag and drop
- add a social component: allow the learners in a class see each other’s activity; allow seeing social feedback on existing articles
- create mobile applications for the various platforms; probably with a cross-platform tech, e.g. Flutter
- research questions that should be answereed
- how important is the difficulty estimator given that Zeeguu supports the reader also with translations - so they can read texts that are harder than their level; how much harder than their level can they read now?
- how to evaluate the efficiency of the exercise scheduling algorithm?