Is there any difference? At core, my new book is about learning science. And, as I’ve lamented before, the lack of understanding of cognitive science is a barrier to better L&D. However, it takes a certain mindset to put this into practice in practical ways.
Should you overall be optimistic or cynical? Applying cognitive science (see what I did there?), I would err on the side of optimism. Research suggests a positive attitude is overall better. Thus, I guess I’m arguing for the former ;). The alternative, a cynic still looking for good, is less optimal.
However, optimism tempered with a healthy skepticism! There are those who’d take advantage of naivete, as has reliably been exposed. A vigilant evaluation of what’s presented is healthy for dialog and moving the industry forward!
You need to be prepared for the variety of ways people can mislead you (and even themselves). Without a decent understanding of scientific validity, you might be swayed by statistical sleight-of-hand. Worst case, you listen to those who carry the standard of rigor in evaluation. I don’t necessarily mean the scientists, because they don’t always present it in comprehensible ways (writing in their native academese). Instead, there are those who serve as translators of research to practice.
People like Will Thalheimer, Patti Shank, Julie Dirksen, Guy Wallace, Mirjam Neelen, and more (including yours truly), have boiled down learning science into practical approaches. Whether it’s overviews, processes, or even acronyms, their guidance is soundly based. We may not always agree, but you’re far better off betting on them than on those with a vested interest.
On your own, of course, you should be conducting several validity checks. Who’s telling you, and what’s in it for them? Is their message supported by external validation? Are there alternate views? Does it pass the ‘sniff’ test (that is, does it make a plausible causal story)? Of course, “if it sounds too good to be true, it probably is”.
In addition to empirical grounds, one should also evaluate the theoretical basis. Did the work emerge from empirical data, or was it made from someone’s musings, and untested? Is there a reason to accept the underlying frameworks?
Overall, I suggest that practitioners in learning first need to be grounded in understanding how we learn. Then, I reckon we need to be rigorous in evaluating new approaches. There will be wheat amongst the chaff, but the relative ratios are the issue. Make sure you’re finding nuggets, not tailings (I like my metaphors mixed).