This article explores an innovative approach to deliver information about new agricultural technology that combines a versatile and potentially lower cost method of developing animated videos with another low-cost method of sharing it on mobile devices (i.e. mobile phone). It describes a randomized controlled field experiment conducted in Burkina Faso to evaluate the effectiveness of animated videos shown on mobile phone compared with the traditional extension method (live demonstration) in inducing learning and adoption of two post-harvest technologies among low-literate farmers. Results suggest that video-based training was as effective as the traditional method in inducing learning and understanding. For technologies that farmers were already aware of animated video shown on the mobile phone was also as effective as live demonstration in inducing adoption. However, in transferring new technologies, the traditional method was more effective in inducing adoption at p < .10, but not at p < .05. Potential role of mobile phone-based videos as part of the agricultural extension system is discussed.

Shea trees grow across 4 million km² of sub-Saharan Africa. Shea parklands provide a sustainable source of edible fat (shea butter) that, in terms of volume, is currently second only to cocoa butter as a vegetal source of stearic acid in the multi-billion dollar chocolate and cosmetic sectors. However, in terms of international trade, shea has been opaque to consumers of edible products (where the majority of shea exports end their global journey) and actually only well-known in western markets as a cosmetic ingredient. The millions of women collectors have been disconnected from global supply chains, as the majority of their sheanuts are factory processed, supplied by traders who, in many cases, do not understand quality issues nor share knowledge with their village-based collectors—this is the “Paradox of paradoxa”. This review provides the background to this issue by contextualizing the industry and describing how weak post-harvest quality control impacts the shea supply chain. The paper then explains how this knowledge was incorporated into a 3D animation available for free transmission to rural African audiences and viewing on portable devices like video capable mobile phones. This tool offers the potential of low-cost multiple benefits to users, which we term here a win-cubed [win³] opportunity, where women collectors can receive free knowledge of using less resources to produce higher quality shea kernels which in turn offer higher extraction yields, lowering production costs, of a better and more marketable product.

Securing the adoption of scalable agro-educational information and communication technology (ICT) solutions by farmers remains one of the international development community’s most elusive goals – in part due to two key gaps in the data: (1) limited comparisons of competing knowledge-delivery methods, and (2) few to no follow-ups on long-term knowledge retention and solution adoption. Addressing both of these gaps, this follow-up study measures farmer knowledge retention and solution adoption two years after being trained on an improved postharvest bean storage method in northern Mozambique. The results found animated-video knowledge delivery at least as effective as a traditional extension approach for knowledge retention (97.9%) and solution adoption (89%). As animated video can more cost-effectively reach the widest – even geographically isolated – populations, it readily complements extension services and international development community efforts to secure knowledge transfer and recipient buy-in for innovations. Implications and future research for adult learning are also discussed.

Indigeneity is a much contested term, complicated by formal definitions under domestic and international law, the unlimited right to self-identification by indigenous people, conflicts and/or contradictions between these legal principles, and the political inequalities that result from variations in access to the processes and legal actions that invoke these terms. In particular, this generates a gap between legal definitions of indigeneity (framed, then and now, by hegemonic powers) and sociocultural practices of indigeneity (expressed and experienced, then as now, by cultures themselves). Reviewing the conceptual framing(s) of indigeneity both internationally and in a domestic (US) context, this article explores and offers a more flexible, resilient, and just understanding of indigeneity capable of closing the legal/sociocultural gap currently affecting indigenous people worldwide. At root, this less means asking what (or where) is indigeneity, and more instead when is indigeneity.

Despite the recognized importance of women’s participation in agricultural extension services, research continues to show inequalities in women’s participation. Emerging capacities for conducting large-scale extension training using information and communication technologies (ICTs) now afford opportunities for generating the rich datasets needed to analyze situational factors that affect women’s participation. Data was recorded from 1,070 video-based agricultural extension training events (131,073 farmers) in four Administrative Divisions of Bangladesh (Rangpur, Dhaka, Khulna, and Rajshahi). The study analyzed the effect of gender of the trainer, time of the day, day of the week, month of the year, Bangladesh Administrative Division, and venue type on (1) the expected number of extension event attendees and (2) the odds of females attending the event conditioned on the total number of attendees. The study revealed strong gender specific training preferences. Several factors that increased total participation, decreased female attendance (e.g., male-led training event held after 3:30 pm in Rangpur). These findings highlight the dilemma faced by extension trainers seeking to maximize attendance at training events while avoiding exacerbating gender inequalities. The study concludes with a discussion of ways to mitigate gender exclusion in extension training by extending data collection processes, incorporating machine learning to understand gender preferences, and applying optimization theory to increase total participation while concurrently improving gender inclusivity.