Case study

Re-imagining and modernizing an in-person field training program

One of the world’s largest humanitarian networks wanted to modernize its training program on reducing corruption to a highly interactive device-agnostic course to educate volunteers, local partners, employees, and various stakeholders.

Intro

Reducing corruption in humanitarian operations through awareness and just-in-time training interventions

Humanitarian aid programs’ quality and effectiveness are measured by their success in delivering the much-needed resource to their intended beneficiaries and purposes.

Corruption in humanitarian aid directly affects the most vulnerable in a crisis, depriving them of resources that could alleviate their suffering.

Training modernization strategies

Engaging and immersive digital learning programs suitable for global delivery

Challenge

Corruption in humanitarian operations is a reality and a danger that all agencies involved in humanitarian missions of any scale face daily.

As the world’s largest humanitarian network, the organization found spreading awareness among all stakeholders involved, specifically the volunteers, donors, and the public, of the corruption risks in these large-scale operations would be the starting point of preventive measures. The challenge was finding an effective training strategy that increases understanding of the gravity of the problem and awareness about the consequences.

Solution

Integra designed a self-paced e-Learning course rich with complex branching scenarios with 25+ decision points. Each decision point was followed by a debrief section, where learners could explore key concepts, best practices, and common misconceptions. The course was designed as a deep, immersive experience placing the learner at the center of the content, guiding them through the consequences of a decision when facing the most egregious form of corruption that affects human lives in their most vulnerable situation.

Integra developed the e-Learning courseware in HTML5 with a responsive design that will allow device-agnostic deployment for multi-device learning – PCs, laptops, tablets, and smartphones with form factors of 4–6 inches.