"first, we give empirical evidence that shows the extent to which productive training (i.e. vocalizing words) is superior to receptive vocabulary training, and discuss the use of scaffolding hints to "unpack" factors in the learner‟s linguistic knowledge that may impact reading. Second, we discuss what our results suggest for future research in HCI."
"Training was accomplished using a videogame paradigm that emphasizes
associations among sound categories, visual information, and players' responses to videogame characters"
From the abstract: "Collective Artificial Intelligence (CAI) simulates human intelligence from data contributed by many
humans, mined for inter-related patterns. This thesis applies CAI to social role-playing, introducing an
end-to-end process for compositing recorded performances from thousands of humans, and simulating
open-ended interaction from this data. The CAI process combines crowdsourcing, pattern discovery, and
case-based planning. Content creation is crowdsourced by recording role-players online. Browser-based
tools allow non-experts to annotate data, organizing content into a hierarchical narrative structure.
Patterns discovered from data power a novel system combining plan recognition with case-based
planning. The combination of this process and structure produces a new medium, which exploits a
massive corpus to realize characters who interact and converse with humans. This medium enables new
experiences in videogames, and new classes of training simulations, therapeutic applications, and social
robots. .... As a proof of concept, a CAI system has been evaluated by recording over 10,000 performances
in The Restaurant Game, automating an AI-controlled waitress who interacts in the world, and
converses with a human via text or speech. Quantitative results demonstrate CAI supports significantly
open-ended interaction with humans, while focus groups reveal factors for improving engagement."