Why do learning professionals in L and D – managers, project managers, interactive designers, learning experience designers and so on, ignore research? It doesn’t matter if you are implementing opportunities for learning such as nudges, social opportunities, workflow learning, performance support or designing pieces of content or full courses, you will be faced with deciding on whether one learning strategy, tactic or approach is better than another. This can’t be just about taking a horse to water – you must also make sure it drinks. Imagine a health system where all we do is design hospitals and opportunities for people to do healthy things or get advice on how to cure themselves, by people who do not know what the clinical research shows. 

Whatever the learning experience, you need to know about learning.

Lawyers know the law, engineers know physics but learning professionals often know little about learning theory. The consequences of this are, I think, severe. We’re sometimes seen as faddish, adopting tactics that are neither researched nor anything more than a la mode. It leads to products that do not deliver learning or learning opportunities – social systems that lie fallow and unused, polished looking rich media that actually hinders rather than helps one learn. It makes the process of learning longer, more expensive and less efficacious. Worse still, much delivery may actually hinder, rather than help learning, resulting in wasted effort or cognitive overload. It also makes us look unprofessional, not taken seriously by senior management (and learners).

We have seen the effect of flat-earth theory such a learning styles and whole word teaching of literacy, and the devastating effect it can have, wasting time in corporate learning and producing kids with poor reading skills. In online learning the rush to produce media rich learning experiences often actually harms the learning process by producing non-effortful viewing, click-through online learning and cognitive overload. Leader boards are launched but have to be abandoned. The refusal to accept evidence that most learning needs deliberate practice, whether through desirable difficulty, retrieval or spaced practice, is still a giant vacuum in the learning game.

So there are several reasons why research can usefully inform our professional lives.

One of things research can achieve, is to implore us to discard theories and practices, which are shown to be wrong-headed, like VAK learning styles or whole word teaching. These were both very popular theories, still held by large percentages of learning professionals. Yet research has shown them, not only to be suspect as theories, but also as having no efficacy. There’s a long list of current practice, such as Myers-Briggs, NLP, emotional intelligence, Gardener’s multiple intelligences, Maslow’s hierarchy of needs, Dales cone for learning and so on, that research has debunked. Yet these practices carry on long after the debunking – like those cartoon figures who run off cliffs and are seen still hanging there, looking down…

Whether its general hypotheses like Does this massive spending on diversity training actually work? Or, at the next level Does this nudge learning delivery strategy based on the idea of hyperbolic discounting actually work better than single point delivery?  Research can help. There’s specific learning strategies by learners Does this retrieval or spaced or desirable difficulty practice increase retention? Even at the very specific level of cognitive science, lots of small hypotheses can be tested – like interleaving. In online learning What is the optimum number of options in a multiple choice question? Is media rich mind rich? As some of this research is truly counterintuitive, it also prevents us from being flat-earthers, or believing something, like the sun goes round the earth, just because it feels right. 

As technology increasingly helps deliver solutions, it is useful to design technology on the basis if researched findings. If, for example, an AI adaptive system was to be designed on the basis of Learning Styles, as opposed to the diagnosis of identified cognitive errors, that would be a mistake. Indeed technology, especially smart technology, often embodies pedagogic approaches, baking in theory, so that the practice can be enabled. I have built technology that is based wholly on several principles from cognitive science. I have also seen much technology that does not conform to good evidence based theory.

Learning is something we all do. We’ve all gone through years of school and so it is something on which we all have opinions. This means that discussions with stakeholders and budget holders can be difficult. There is often an over-emphasis on how things ‘look’ and much superficial discussion about graphics, with little discussion about the actual desired outcome – the acquisition of knowledge and skills and eventual performance. Research gives you the ability to navigate through these questions from stakeholders on the basis of avoiding anecdote, relying on objective research.

Research has shown that learners are strangely delusional about optimal learning strategies and what they think they have learnt. This really does matter, as what they want is not always what they actually need. Analogously, you as teacher or learning designer, are like a doctor advising a patient, who is unlikely to know exactly what they have to do to solve their problem. An evidence-based approach moves us beyond the simplicities of learning styles and too much focus on making things ‘look’ or ‘feel’ good. Explaining to a learner that this approach will get them to their goal quicker, pass that exam and perform better can benefit from making the research explicit to the learner.

6. Research helps you select tools
One of the biggest problems in the delivery of online learning, is the way the tools shape what the learner sees, experiences and does. Far too many of these tools focus on look and feel, at the expense of cognitive effort, so we get lots of beautiful sliding effects and lots of bits ion media. It is, in effect, souped-up Powerpoint. Even worse are the childish games templates that produce mazes and other nonsense that is a million miles away from proper gaming. We have a chance to escape this with smarter software and tools that allow the learner to do what they need to do to learn – open input, write, do things. This requires Natural Language Processing and lots of other new tech.

In navigating organisational politics, structures and budgeting, also making your internal service appeal to senior management, research can be used to validate your proposals and approaches. HR and L and D have long complained about not being taken seriously enough by the business. Finance has the advantage of a body of established practice, massively influenced by technology and data. This is becoming true of marketing, production, even management, where data on the efficacy of different channels is now the norm. So it should be with learning. Alignment and impact matter. Personalised ‘experiences’ really do matter in the midst of complex learning.

Conclusion
If all of the above don’t convince you, then I’d appeal to the simple idea of doing the right thing. It’s not that all research is definitive, as science is always on the move, open to future falsification. But, as with research in medicine, physics in material science and engineering, chemistry in organic and inorganic production, maths in AI, we work with the best that is available. WE are duty bound to do our best on the best available evidence or we are not really a professional ‘profession’.