CLSep 3, 2019

"Can you say more about the location?" The Development of a Pedagogical Reference Resolution Agent

arXiv:1909.00945v17 citations
Originality Synthesis-oriented
AI Analysis

This work addresses geographic literacy for the general public, but it is incremental as it adapts existing game-based learning methods to new platforms.

The paper tackled the problem of improving geographic literacy by developing a collaborative two-player game to help people locate countries on a world map, resulting in participants finding the game engaging and believing they gained lasting knowledge.

In an increasingly globalized world, geographic literacy is crucial. In this paper, we present a collaborative two-player game to improve people's ability to locate countries on the world map. We discuss two implementations of the game: First, we created a web-based version which can be played with the remote-controlled agent Nellie. With the knowledge we gained from a large online data collection, we re-implemented the game so it can be played face-to-face with the Furhat robot Neil. Our analysis shows that participants found the game not just engaging to play, they also believe they gained lasting knowledge about the world map.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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