There are many common misunderstandings about learning. For instance, Practice does make perfect (except in  'education and professions like computer science, military-aircraft piloting, and sales').

Teaching goes hand in hand with encouragement and social skill. One kind of effective complement [literature summary] is the indirect process compliments [twitter] which is all about cheering someone on for trying to do the right thing. Secondly emotion control aids academic achievement (B) [peer reviewed]. Yet emotion control is more closely associated with interpersonal competence. As the saying goes: those who can't control their own emotions try to control others. Thirdly, and anecdotally mathematical anxiety [text] manifests in counterproductive social environments: boring classrooms with rote learning, high stake test oriented parenting and unsupportive peer groups.

What else can we learn from research on how to learn most effectively? Spaced repetition and practice testing are the most effective learning techniques. When I scoured the internet and my social network for other techniques I discovered other tactics used by competitive memory athletes. I found that Mnemonics/memorisation [Wikipedia] tactics such as the aforementioned spaced repetition [freeware] came up as well as the picture walk (more or less a variant on the method of loci, which is described in the mnemonics hyperlink and used in childhood education), chunking, or building spatial, personal, surprising, sexual or humorous mental association's may be useful in gaming the rote side of formal education.

Memorisation is one portion of learning. Other important principles are: overlearn, learn by teaching, practice tests, using analogies, concept map, do worked examples, role play to learn, and learn by observation. It is also helpful to learn how to ask questions that can be answered with evidence, with heuristics like the PICOT research question [text] [tutorial]).

There are general principles of learning [twitter] (alt: Wikipedia) and it is a step by step process (see: the 9 learning events [Wikipedia]). The process is just as systematic for the learning disabled (see the DEFENDS learning strategy for learning disabled students [meta-analysis])

There are defined routes to mastery and there are no magical shortcuts. In fact, slow motion practice is the closest thing to a magic bullet in learning sports.The evidence reveals speed reading trades off accuracy, comprehension, and understanding. Don't mistake me here, there are time saving tools like fermi calculations to improve your ability to guestimate,  and work Breakdown Structures in project management. There is even a ‘Tim Ferris’ approach to learning called “accelerated learning/reverse engineering a skill from the end outcome”, which helped him learn a language enough to get interviewed in it, within 4 days.

What are the highest impact learning strategies? Thankfully, the highest impact influences on learning achievements are well understood. High expectations for one’s grades [text] [meta-analysis] is the greatest determinant of student achievement.

The environment matters to: Sleep after learning to retain information, learned in the morning [peer reviewed] and use dynamic learning environments [one experiment] [YouTube].

Every now and then you’ll hear of a new strategy or technique. They can be reviwed via sources like the Education Elf. However, other techniques are introduced on social media. For instance, there’s a video I recently came across about The Feynman Technique [opinion] [YouTube] on YouTube. When encountering these don’t throw out your model of learning. Typically, one can explain these techniques in terms of the foundational principles already fleshed out. Or, like a portion of unsettled science, they are soon rebuked. For instance: Despite criticism from both students, that one documentary on the Finnish education system, and academia, homework may be more beneficial than needless, but in select circumstances. Note this phenomenon is not unique to education research. Half a dozen years on, 20% of cardiology recommendations are downgrades or reversed, with those based on single trials, observational data or opinions about 10% percentage points more like to falter, than those based on multiple trials. However, the nature of evidence-based learning is that if and when the evidence does change, we ought to change our perspective along with it.