How Instructional Design Solves Common Learning Challenges Created By Tech
How has the proliferation of communication technology impacted learning? The facts demonstrate that the incumbent workforce learns new information very differently than their predecessors. Organizational leadership, Learning and Development professionals, and individuals cannot expect that today’s learners will interact with and assimilate new information via droning lectures and exhaustive PowerPoint presentations, even when those are presented via Zoom or other video conferencing methods.
The Paradigm Shift
While these tools still have some basic use, learners overwhelmingly no longer look to single-source outlets of knowledge. Instead, your employees are used to accessing an entire network of resources. They may go looking through:
- YouTube videos
- Online articles and blogs
- Social Media
- Online file sharing tools
In short, learners are used to engaging with the world around them very differently. The change amounts to a seismic paradigm shift in the way people are processing day-to-day information, and a corresponding shift in the way we learn.
For example, mobile technology and use of search engines has reduced the need for rote memorization. Instead, people expect resources to supplement gaps in knowledge. Additionally, communication among experts used to take weeks, but now only takes minutes. Where visual aids and media used to be difficult to produce, anyone with a mobile device can create and access audio-visual resources anytime, anywhere.
The result is that modern technology has made education more accessible, but also changed the learner and resulted in a shift that requires new instructional design methods. Formal training and learning will be less effective than performance support on-demand.
Instructional Design And Technology
The time has come to take advantage of our learners’ implicit ability to learn in a technology-centric world. This has many implications for the move of the workplace to the digital environment. Instructional design best practices are needed to successfully make the transition and should be adopted to engage with employees and build virtual teams.
If we consider the fact that modern technology has infused today’s learners with innate information-processing skills that were previously unheard of, we can shift our educational focus to the distribution of knowledge instead of on the knowledge itself. Our interconnected professional networks and ability to analyze data have created vast oceans of information that are at our disposal – we’re not going to run out of information any time soon. Such large repositories of knowledge create three distinct challenges when faced with disseminating knowledge:
What knowledge or information does your workforce need in order to support organizational priorities? What about individual priorities?
What is the most effective way to engage with a remote workforce, and distribute information in a way that supports purpose and the mission of the team?
How can we make sure our workforce has learned what we want them to learn?
We can address all three challenges with instructional design and technology.
Instructional Design Methods To Engage Learners In The Age Of Remote Work
When it comes to prioritization, we can look to data gathering and analytics with a strategic plan in place to make use of the data to enhance the learning experience. Data mining through the lens of needs analysis is the best way to use data, assessments, and other resources to inform decisions regarding training solutions.
Approaching this process with a specific goal in mind helps focus attention on data that relates to the employee performance gaps or organizational challenges. For example, if you’re looking at cutting down employee turnover, data relating to the amount of onboarding training employees receive would offer good insights about what direction your training should take. Once a training program is in place, don’t overlook the data gathered by your users. Seat time analytics, progression statistics, and rates of participation are all valuable tools in measuring the success of a training initiative.
Once you have a goal in mind and data metrics gathered, you can focus your attention on distribution. The methodology behind your chosen distribution efforts is more important than the knowledge you are trying to distribute. Establishing a secure efficient pipeline of research-based instructional design methods is the only way to get your expertise into the hands of your workforce.
Each distribution method has its own nuances, pros, and cons, but fully exploring the approaches and finding what will work best with your content and audience is well worth the investment in exploration of instructional design best practices, time, cost, and effort. For example, one distribution method that is increasing in popularity is the practice of continuous learning instead of single training sessions. The practice is especially useful in onboarding training, as most employees don’t reach their full productivity potential in the first year of work. Continuous learning allows learners to learn new concepts at a manageable pace.
Additionally, ongoing training offers ample opportunities for learners to discuss problems or learning obstacles with their supervisors without appearing overly needy or giving the impression that they can’t solve problems on their own.
The Importance Of Analytics
This interval-style approach to training can become even more effective when combined with performance support measures for learners to access along the way. Modern technology has given us a profound ability to quickly create searchable databases of information that can be beneficial to new hires who require support while they immerse themselves in their new role. While timely and engaging training opportunities coupled with an on-the-job resource library are ideal for new employees, this technique works just as well for current employees who need to learn a new soft skill or reference a procedure that is not commonly used.
We can apply this knowledge, based on instructional design methods, in the following ways. As data analytics become easier to obtain and more robust, we can use that technology in our training programs to generate valuable information about our users in order to gauge the effectiveness of a given course. Data like completion rates, exit surveys, rates of participation, and competency scores can be easily collected with modern training programs.
Once this data is gathered and sorted, it can be compared to rates of success in related areas or toward meeting certain goals. For example, if users were offered an optional, web-based training to develop certain soft skills to help them improve the effectiveness of their sales pitch, the number of employees that take the training offers just one data point. The employees who excel at the coursework can offer another data point, and the employees who contribute any information to their exit survey provide yet one more. This data can be compiled, analyzed, and cross-referenced to see if the employees who took the training became more effective salespeople.
Choosing The Right Approach
With the amount of technology available and on its way, choosing the technological framework for your learning solution can be a daunting task. It’s easy to associate relevance and effectiveness with the amount of buzz a certain technology is getting, but all tech is not created equal. Once you’ve done the work of isolating your company’s needs and mapping out a plan to achieve those needs, the next step is choosing a technology that will do the best job. Those that are most likely to get your learners on the right track will be unique to your organization, but certain best practices will still apply.
Download the eBook The Future of Work: The Role of Instructional Design In Converting VILT To eLearning In 2021 to discover the challenges of learning in a virtual environment and how to overcome them cost effectively with instructional design best practices.