Piranhas are competing with sharks – that is the reality of today’s digital era. New problems and interwoven opportunities may constantly emerge, but what worked a year ago might not work this time. So, finding ways to recognize and overcome the common pitfalls associated with growing a business is the only way to keep going forward. Yet, the current need-based training and development largely miss to deliver transferable skills and provide learning as a solution for companies increasingly reliant on distributed teams.
The future of work will see the need for institutionalized micro-learning that will help people perform in their professional tasks through just-in-time and defined need-based learning. This brings about the concept of the intelligent workplace – one that inspires problem-solving, critical thinking, and intuition – even amid uncertainties and dynamic developments. And the learning journey toward that goal should be in an individual’s own time, in smaller bytes, and easily translated to action.
How can enterprises move to an institutionalized microlearning approach toward workplace education and learning?
How We Nurture Culture of Self-Learning
Many companies out there still spend so much time dealing with the “alligators” that are snapping at their back and missing to look “beyond the weeds”. This results in disproportionate spending on training that fails to deliver the desired outcome.
Instead of grand solutions, micro-learning simply calls for a human teacher that is available at workplaces to help guide problem resolution that is personalized and time-efficient. This helps the learner access the right information and knowhow in familiar situations and from someone they can relate to.
This doesn’t mean that workplaces need a network of external experts; rather, they should promote activity, interest, and situation-based mentoring, where learners connect with subject matter experts (SMEs) on the call basis. The people who have experience working with similar tasks are more likely to teach authentically and accurately, considering the specific organizational circumstances.
Learning through deeply embedded current work context brings the right insights on activity and shared work scenarios, while boosting motivation to learn actively and quickly. The retention is also higher when an SME guides the learner, just like it goes in the famous proverb: “Give a man a fish and you feed him for a day; teach a man to fish, and you feed him for a lifetime.”
However, the challenge here lies in creating incentives for both: the one who learns and the other who shares the knowledge. Learning and teaching are always bi-directional, be it formal or informal. It’s a symbolic process that creates greater value through collaboration, sharing, and reverse learning. Therefore, it should be promoted as such and driven to its full potential with the help of technology that matches learning pairs at the right time, allowing learners to leverage the partnership anywhere within the enterprise.
Creating a Skill Bank
To advance micro-learning, workplaces could leverage automated mentoring platforms, creating a skill bank that is affordable, affable, and agnostic to any type of industry. Such pure-play software should operate a single, detailed profile for each user with professional stats, work portfolio, and activity history. The database could then list different scenarios and partnerships with individuals that would take upon roles as mentees or mentors, depending on the specific situations.
Enterprises would need a pool of mentor volunteers who believe in sharing knowledge and reverse learning. Anyone looking to learn a particular skill or trying to get support in problem resolution would then be assigned to the optimal match. Once both accepted, the learning pair would set into motion with self-directed goals and a self-paced learning cohort. And with each stage having defined touchpoints, there would be a constant feedback loop.
Within such a mentoring software, contributors could add some of the past problems that they worked on or create an inventory of running task lists of short-term problems that they would be working on. This can encompass any situation, from presenting in another language or preparing a speech for a conference to making a sales call or designing a new software framework for a given problem.
The contributors could also add granularity of details or specifics around the items in their task lists, and qualify any open questions that they still do not know the answer to. This could be a person doing a roadshow in Europe, specifically looking to better manage the logistics, get any advice on software tools to use, or tips for tailoring a speech that will best engage the audience.
A Distributed Network of Mentors and Learning Partners
To take it a step further, the mentoring platforms could leverage machine learning (ML) to recognize different user groups and identify whether they work in the same umbrella – the same organization, department, or broader collaboration network. Based on this, it could find the best candidate to teach on a specific subject or match ideal learning partners for an upcoming task.
Such recommendations would then be displayed on the users’ screen. After all, no other learning method can yield a long-lasting solution other than when the learner takes ownership of the process, and the learning agenda becomes clearly hooked to a specific and immediate need to execute a task. The motivation to learn out of anxiety to perform and succeed is a primary need and thus attended with priority.
Typically, users who volunteer to act as teachers or mentors receive their own periodic assessments on advanced job skills. The system then informally records the results of high-achievers, helping to qualify skills that a user may have developed or shown activity towards, into more depth and greater detail. Over time, this ensures better matching and allows the user to consolidate their knowledge – something that can be further leveraged for their professional growth even outside the organization.
In personal development, the inclination and commitment of the learner always improve when the learning is relevant and practical. In addition, peer learning within an enterprise guarantees a vast range of topics, organizational validation, and a personalized time and intensity of the learning. But ultimately, discussing and solving actual challenges to personal and professional growth can trigger invaluable self-learning practices – one of the keys to nurturing human talent.
Source : https://www.hr.com/en/magazines/all_articles/microlearning-design-for-an-intelligent-workplace_kemvu64j.html