Petra Hendriks - Language acquisition and the Eliza effect
It is generally believed that children must first learn to comprehend a linguistic expression before they can correctly use it themselves. However, several studies have found that children's production of correct word order, pronouns like he and him, and several other linguistic forms seems to precede their comprehension. This surprising pattern may not have been observed earlier because not only the interactions of humans with computers, but also the interactions of adults with children are subject to the Eliza effect: the susceptibility to read far more understanding than is warranted into strings of words (Hofstadter, 1996). In this talk I will discuss an explanation of asymmetries between children's production and their comprehension in terms of children's non-adult ranking of the constraints of their grammar and their failure to consider the perspective of their conversational partner. Evidence will be presented from linguistic experiments such as eyetracking (e.g., Cannizzaro, 2012) and cognitive modeling in ACT-R (van Rij, 2012) to support this explanation.
Last modified: | 13 June 2019 1.40 p.m. |
More news
-
06 May 2025
Overcoming grid congestion: ‘Making better use of what we already have’
Grid congestion poses a major problem. There is little to no capacity to connect new households and businesses to the power grid and it risks halting the energy transition. Michele Cucuzzella, Associate Professor of Energy Systems & Nonlinear...
-
29 April 2025
Impact | Rubber recycling
In the coming weeks the nominees for the Ben Feringa Impact Award 2025 will introduce themselves and their impactful research or project. This week: Francesco Picchioni on his innovative way to recycle rubber.
-
29 April 2025
Impact | Improving Human-AI Decision-Making in healthcare
In the coming weeks the nominees for the Ben Feringa Impact Award 2025 will introduce themselves and their impactful research or project. This week: Andra Cristiana Minculescu on her research project on Human-AI Decision-Making in healthcare.