Education

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Revision as of 15:50, 25 August 2020 by SashaL (talk | contribs) (Updated descriptions and resources)

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On the one hand, in addition to being universally beneficial, education can improve the resilience of communities to climate change, especially in developing countries. ML can help enable personalized and scalable tools for education. On the other, education can empower individuals to adopt more sustainable lifestyles. ML can help educate the public about climate change through conversational agents and adaptive learning techniques.

Data

There are many hurdles in accessing data generated from educational settings, given the privacy issues that arise and the digital divide that exists in many countries,where learning is offline. There are nonetheless a few data sources that can be of interest:

Methods and Software

Recommended Readings

Readings

Online courses

Community

Journals and conferences

Societies and organizations

Past and upcoming events

Important considerations

Next steps

References