hiperlearn

In a modern high-performing organization, learning and training needs to be optimized to reduce time and costs – but without sacrificing conceptual depth at any stage of the learning process. In this context, a blended learning architecture that combines different modalities appropriately is very useful towards creating a sustainable intervention that nurtures performance outcomes without sacrificing swiftness. But how do we create a performance-oriented blended learning architecture? While there can be many “blends”, here are a few pointers on how this can be achieved.

Create Desirable Blends

A desirable blend is a tailored blend for module-flow and/or course flow, which harmonizes organizational and individual goals. For example, for the autonomous employee/working team, automated and unsupervised training can be programmed in appropriately for (relatively) routine tasks and processes, whereas the more novel, complex, and/or creative task training may be overseen by a subject-matter expert (SME) or supervisor. This could enable the employee(s) to take care of the (relatively) mundane in their own time, while providing enough support and mentorship through a novel task to ensure learning support, security, and appropriate feedback.

Desirable blends can be used to engage different modalities – such as to provide simulations of “live” performance scenarios, accelerated learning through expert advice (through podcasts and/or SME workshops), and learning resources that that engage the learner by situating the resource within the appropriate usage context. By incorporating mindful digital design, it is possible to nurture performance in a time and cost-effective manner, whilst maximizing performance outcomes for learners.

Avoid Undesirable Blends

Perhaps the pressing matter of concern in many learning and development (L&D) designs is the issue of undesirable blends. Too much task-switching and context-switching (such as switching between different file formats and/or learning formats too often) and/or hasty design can leave learners feeling overwhelmed, instead of facilitating immersion. In this context, it seems appropriate to reduce bloat in the learning design, and to align learning and training interventions with individual and organizational goals at every stage.

Establishing effective learning pathways are the salient concern, the minutiae of content and formatting should merely act as an enabler for the same.

Focus on iterative improvements to improve learning flow

Iterative improvement of the learning pathway and module/course flow(s) is essential. As L&D designers, while the focus is to engage the learners, it is unreasonable (and impossible!) to expect any learning pathway to be perfectly optimal – in terms of learning depth and performance. Receiving feedback and advice from learners and/or learning cohorts is, therefore, the key that unlocks the continuous improvement of the learning design.

While some feedback may lead to minor changes (such as issues with accessing certain formats and/or exercises), some feedback may be enlightening and disruptive (such as the realization that a certain training delivery format is consistently delivering mediocre outcomes in terms of performance). It is important for us to recognize that the learner experience (LX) takes precedence over prior notions of effective learning design.

As an anonymized example, a hypothetical “XYZ” bank held an automated training in professional ethics, assuming this was a routine procedure that could be tackled at the participants’ own pace. Unfortunately, several learner-participants from the same cohort found the automated video lectures and subsequent exercises to be confusing. To them, some of the situations and outcomes even “felt unrealistic”.

In this context, as an L&D practitioner who receives such feedback, would you persist with automated training for this subject domain? Or might it be more appropriate to include guided human supervision from an internal SME? We have to keep in mind that ethical missteps in a workplace context may not just impede performance but may result in catastrophic circumstances for an institution.

Iterative improvement based on learner feedback is the key to improving learning pathway(s) in modern workplace learning. Learning blends have to be analyzed, and continuously refined to ensure the recipes stay relevant and deliver performance results for the years to come.

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