Machine-supported decision-making to improve agricultural training participation and gender inclusivity.

Women comprise a significant portion of the agricultural workforce in developing countries but are often less likely to attend government sponsored training events. The objective of this study was to assess the feasibility of using machine-supported decision-making to increase overall training turnout while enhancing gender inclusivity. Using data obtained from 1,067 agricultural extension training events in Bangladesh (130,690 farmers), models were created to assess gender-based training patterns (e.

Breaking out: the turning point in learning using mobile technology.

Despite considerable research on YouTube as a digital media platform, little research to date has quantified the device-type used to that online media. Analyzing access-device data for videos on one YouTube video channel-Scientific Animations Without Borders (SAWBO), which produces educational content specifically accessible to low- or non-literate, poor, or geographically isolated learners in less developed areas of the world-the results identify the historical moments between 2015 and 2017 when mobile/smartphones, both globally and by region, crossed a tipping point to surpass all other ICT devices (including desktop PCs, laptops, and other Internet-accessing technologies) as the primary device-type for accessing SAWBO videos. Specifically, data from January 2013 to June 2018 obtained for SAWBO's YouTube channel were sampled to capture and distinguish the access device-type used and then summarized in broad global and regional categories.