We all know that people learn in different ways, but how often do we apply different approaches to teaching to ensure the best understanding, absorption and impact of the given lesson? Many of us have seen this first hand with the variances in the success of home-schooling during the COVID pandemic!
Coaching and mentoring, working with the individual, enables the mentee to grow and develop at their own pace, but larger-scale training often misses the mark. I heard an anecdote recently of an enterprise business delivering wide-scale training to its staff on 3 new tech platforms. The training agenda and pace was designed around a technical audience and failed to connect well with the non-technical trainees who just fell further behind in both understanding and adoption of the platforms. This generates unease in the trainees and can also cause dissatisfaction and a sense of failure which will have a detrimental impact on the workforce when the platform use becomes part of their BAU.
When training for non-technical users is labelled with a “data theme” additional limiting beliefs come into play. Many people assume “data = doing maths” and research has found at 20% of adults experience maths anxiety (The Maths Anxiety Trust 2018). Training on data subjects needs to be sensitive to this to overcome limiting fears and enable the trainee to learn in a positive way.
Some steps we have found are beneficial when supporting businesses who are on their journey to operate and grow with a data mindset, whether that is training on a new data platform or on new methodologies and approaches for using data in the business.
1. Understand the current level of knowledge.
Sounds like common sense, but many trainers assume a degree of data literacy and understanding in their attendees so throw in acronyms and more complex concepts. This can overwhelm and alienate the trainees, instead of building on the current understanding or knowledge gaps to have the required absorption of new information. Understanding your trainees’ knowledge base in the subject matter context gives you the opportunity to be relevant and therefore impactful in the training process.
2. Identify the learning style of your trainee and tailor your training accordingly.
The VARK model of learning styles identified 4 different types of learning that are relevant across all subject matter teachings.
The 4 different learning styles are:
Visual learners respond well to information presented in charts and diagrams, looking at the overall picture not drip-fed bits of knowledge
Read/write learners have a strong preference for the written word. They will most likely make copious amounts of notes to help their knowledge processing and recall of the content.
Kinesthetic (tactile) learners are hands-on. They are most successful when taking a physically active role in the learning process - traditional classroom learning does not have a strong impact on this group of learners.
Auditory learners are most successful when they hear information and discuss what has been learnt rather than writing it down.
Knowing an individual's learning style enables you to tailor your dissemination of information in the most impactful way.
The majority of data and tech platform training is hands-on (appealing to the kinesthetic learner especially), but for individuals who learn best in other ways, this can be a challenge. And I am not saying they won’t learn the platform, but it may just take longer and there may be more hurdles to successful understanding and adoption. Other teaching styles may need to be offered or incorporated to ensure the information is understood and absorbed such as through offering a mix of practical and written exercises, supporting with audio content not just presentation slides etc.
3. Disclose the why.
Anchoring the training into the real work environment is key. Why are the trainees being asked to learn a new platform or a new way of thinking? How does it fit into the bigger business environment and support the business mission? Articulating the “why” is often overlooked but is so important in increasing the trainees’ adoption of the new platform or methodologies.
4. Follow up on training.
It is easy to join a training session and then head back to the “day to day” and not put what has been taught into practice. It is also unlikely that from a single training session, a new skill or new way of working will be wholly adopted, so follow-ups with the trainees are key to identify what areas need further support or to reinforce the positive change from the training subject to drive adoption.
This is really important with data concepts when training non-technical or less data-literate individuals. Seeing how the concepts are successfully applied (or not) highlights focus areas for additional training and further enhancements.
When we work with businesses to support their evolution into leading and operating with a data mindset, we incorporate these principles into our training program designs delivering impact and positive change to ways of working. Get in touch if we can support your business on its journey to be data-driven.
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