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Garrett Eastman

Can Preschoolers Profit from a Teachable Agent Based Play-and-Learn Game in Mathematics? - 1 views

internt.ht.lu.se/...xelsson-anderberg-haake-v2.pdf

math mathematics maths education games teaching teachable agent TA preschoolers research studies learning mind

shared by Garrett Eastman on 18 May 13 - No Cached
  • Garrett Eastman on 18 May 13
     
    abstract: "A large number of studies carried out on pupils aged 8-14 have shown that teachable agent (TA) based games are beneficial for learning. The present pi- oneering study aimed to initiate research looking at whether TA based games can be used as far down as preschool age. Around the age of four, theory of mind (ToM) is under development and it is not unlikely that a fully developed ToM is necessary to benefit from a TA's socially engaging characteristics. 10 preschool children participated in an experiment of playing a mathematics game. The partic- ipants playing a TA-version of the game engaged socially with the TA and were not disturbed by his presence. Thus, this study unveil exciting possibilities for further research of the hypothesised educational benefits in store for preschoolers with regard to play-and-learn games employing TAs."
Garrett Eastman

What does mathoverflow tell us about the production of mathematics? - 0 views

arxiv.org/1305.0904.pdf

math mathematics maths education resources interactive mathoverflow collective intelligence collaboration computing

shared by Garrett Eastman on 13 Jun 13 - No Cached
  • Garrett Eastman on 13 Jun 13
     
    From the abstract: "ew innovations by math- ematicians themselves are starting to harness the power of social computation to create new modes of mathematical production. We study the effectiveness of one such system, and make proposals for enhancement, drawing on AI and computer based mathematics. We analyse the content of a sample of questions and responses in the community ques- tion answering system for research mathematicians, math- overflow . We find that mathoverflow is very effective, with 90% of our sample of questions answered completely or in part. A typical response is an informal dialogue, allowing error and speculation, rather than rigorous mathematical argument: 37% of our sample discussions acknowledged er- ror. Responses typically present information known to the respondent, and readily checked by other users: thus the effectiveness of mathoverflow comes from information shar- ing. We conclude that extending and the power and reach of mathoverflow through a combination of people and machines raises new challenges for artificial intelligence and compu ta- tional mathematics, in particular how to handle error, anal - ogy and informal reasoning."
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