A resource for safe and effective troubleshooting from the leaders in simulation training.
Welcome back, Troubleshooters! From all of us at Simutech, we hope you’re all well and weathering this coronavirus storm safely.
If you’re a regular reader here, you’ll know that the goal of this blog is to help manufacturers stay on top of trends that will affect them, usually with a training and education focus, so they can reduce the downtime that’s such a drag on profitability, and stay ahead of the competition. We’ve recently been doing a series of posts on adaptive learning, and right now we’re concentrating on the future of learning, because it applies directly to employee training, an area where manufacturers can potentially make big gains.
The Future of Learning is the Future of Training
Training obviously has a lot of benefits. Properly trained staff have fewer accidents, which results in fewer OSHA penalties and lawsuits. They stay with the company longer because training makes them more valuable, enables them to take on more responsibility, increases their self-worth and their sense that the company values them, and is a goal along their desired career path. Training can have very tangible financial advantages for an organization; for example, well trained maintenance staff are worth their weight in gold—they can diagnose and repair electrical faults in production line equipment quickly and efficiently, and that’s huge for manufacturers whose downtime costs them in the thousands of dollars per minute.
While the benefits of training are clear, the cost has always been the obstacle. That’s why new technologies and approaches that are lowering the cost of training are very good news for manufacturers. If you have the vision, you can see how in the not-so-distant future you will be able leverage these advances to train more employees faster, to the same quality standards, and for less money.
One way to prepare for this is to understand how technology is making mass education possible. Last week we talked about the future of education being transformed by adaptive learning (AL) powered by artificial intelligence (AI). Today we’re looking at the ways that AI is improving, so that it is able to provide an ever more personalized learning experience along with the efficiencies of scale.
AL of the Future: Profiles and Learning Styles
Most of us are familiar with the notion of learning styles, that is, that some people are visual learners and others are aural, verbal, or active, etc. Some like written materials. There’s no shortage of research that confirms there are distinctly different learning styles. There is also a lot of research that confirms that matching (or mismatching) teaching and learning styles can have a significant effect on learning outcomes (e.g., Ford and Chen 2001, Gilakjani 2012).
In a fascinating study out of Pakistan, students from a number of universities studying in four different subject areas—physics, math, botany, and chemistry—were evaluated to determine their individual learning style on four dimensions of learning: sensing/intuition; active/reflective; visual/verbal; and sequential/global. Their instructors’ teaching styles were also evaluated on the same dimensions.
The researchers found that overall, more students were mismatched with their instructors than were ideally matched. This is because more students prefer visual, sensing and active learning styles, while more teachers teach with a passive lecture style. More importantly, the researchers found that students with matched learning styles significantly outperformed those who were mismatched (mean scores of matched students were 76% while mismatched were 70%). The study also concluded that while visual learning is most dominant, active, global, sequential, reflective, concrete and verbal learning styles all account for an equal proportion of students.
What all of this shows is that learning characteristics are different for each person and that people respond better to different kinds of learning resources. In addition, not only learning styles, but learners’ goals, abilities, and background knowledge also differ. Obviously, to optimize the AI-based learning of the future, course designers need to take students’ individual profiles into account. And that brings us to…
Profiling (But in a Good Way)
Just like the way your streaming video service creates a profile for you, so it can serve up better viewing suggestions for you, the AL- and AI-based learning systems of the future will create a profiles of users in order to adapt content and content delivery to them.
And they won’t even know it’s happening! Learning programs will collect data in real time based on students’ answers and behaviors, using what they call “stealth assessment” (happening beneath the radar). They will “get to know” each learner and personalize a program of content delivery specific to them.
In the future, this is likely to happen at a higher level than e-learning programs. A platform-wide AI network will collect data from a much wider set of activities and even from separate e-learning systems, shared to create a deeply individual profile, and giving the AI a much richer data source from which to infer more subtle learning influencers, such as psychological or emotional state.
Also part of the profile is learners’ ability to adapt to computer-based learning, which may depend on things like age or cultural background. Lee (2001) identified four types of learner adaptation: model learners, disenchanted, maladaptors, and fanatics, all of which have differing levels of ability and satisfaction that affects their learning. Increasingly sophisticated AI will have to take these abilities into consideration as well.
A Golden Opportunity for Continuous Improvement
The key takeaway here for manufacturers is that there are many opportunities for continuous improvement in the area of training, and that computer-based software, including simulation software, that integrates adaptive learning and AI will continue to improve the learning experience as well as student performance. And that’s an efficiency no manufacturer can afford to overlook.
Well, that’s it for today, Troubleshooters! Tune in again next week as we continue exploring AL, AI, and the latest trend that’s certain to have a role in the future of learning—gamification.
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