Author: Marketing Desk

Posted On Jun 09, 2015   |   2 min

Recently, Harbinger presented speaker sessions at the mLearnCon 2015 and the Performance Support Symposium (a co-located event to mLearnCon), held at Austin, TX from June 10-12, 2015. The conference was attended by 1000+ eLearning domain enthusiasts and business executives, featured 100+ sessions from a faculty chosen among the leading industry experts in the eLearning world.

In our speaker session ‘Micro-learning for Performance Support Using MVC: Mobile-video Collaboration’, we discussed how today’s learner is overwhelmed by the information available to him/her and further adding to the woes of an organization’s Training and Development team is the fact that our attention spans are getting shorter.

Harbinger shared the importance and application of bite-sized knowledge chunks in performance support. This session also covered how one can visualize microlearning as a complete solution to providing performance support. We dwelled on the importance of mobile, video and crowdsourcing in creating and distributing microlearning content, and showcased how our Mobile-Video-Collaboration (MVC) model is helping to provide performance support effectively in the areas like sales training, product training, on-the-job aids, and more.

In the one hour session, Umesh Kanade, GM-Technology Solutions, Harbinger Systems and Mahesh Kharade, Associate Architect, Harbinger Systems talked about these aspects and the application of these methods for better learner engagement through MVC model.

Here is the slide deck of the speaker presentation. Hope you find it useful.

In another session, presented by the same duo ‘xAPIs and IoT Frameworks: The Future of Mobile Learning’, we discussed about the convergence of Internet of Things (IoT) with eLearning and how mobile can be an effective enabler for this. We also shared from our experience, the key factors one needs to consider in IoT frameworks for mobile learning applications and how xAPI can be used to pool data from various sensors and devices to a learning management system (LMS).

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