Since you learn best by doing, I would suggest a few basic techniques that will allow you to learn these materials and retain the knowledge over the long-term. The important thing is not to overload yourself with too much disparate information at one time, and to also make sure you are doing enough to solidify each important piece of knowledge before you move on to something else. Look at this as a long-term goal --- aim to gradually build knowledge gradually and in a "deep" manner, where you solidify new knowledge as you go.
Start with what you know, and let yourself wander outward: I would counsel against attempting to learn a large number of meta topics at once. The difficulty with doing this is that those topics might not have obvious connections for you, and that will make knowledge retention difficult. Instead, it is often useful to start with a topic that is of immediate interest to you, which gives rise to broad meta-questions to which you do not already know the answer. It is commonly the case that aspects of your discipline border on to other disciplines, including broader issues of philosophy of science, and so there are often a lot of obvious questions at the border of your own knowledge. By answering these, and connecting it to your existing knowledge and work, you can move outward and solidify your knowledge at each step. Pick a topic on the border of your existing knowledge, and focus on that, but allow yourself to wander into its connections with other topics as you get to the margins.
Since you have not mentioned your area of speciality (or even the broad field you are in) it is not possible for me to give examples that are applicable to you. So in substitution of that, I will give you an example of my own previous learning. I am a statistician, and when I was learning probability and statistics in detail as a grad-student, I learned a lot about the mathematics of "random variables", which are a certain kind of mathematical object. There are some natural philosophical questions arising from this. Is there actually such a thing as randomness in nature? If not, does that invalidate the foundations of probability theory? If not, why not --- i.e., why would it make sense to have mathematical "random variables" if there is no randomness. If there is no randomness in nature, then what is "probability"? Those inquiries led me to the literature on philosophy and probability (plus determinism, indeterminism, compatibalism, etc.), which led me to other broader methodological issues in epistemology, and to learning the approaches of a number of broad schools of thought. One question naturally led to another, until eventually I had a good meta-knowledge that I could connect all the way back to practical issues in my subject matter.
Learn the history by learning about individuals, and remember interesting titbits about them: Just as it is useful to learn broad subject areas by starting with individual questions and working outward, when learning the history of your science, it is similarly useful to start with one person who developed something you find particularly interesting, and then gradually expand outward to learn about more and more people and groups. Also, avoid just learning about the contribution of each person to your field --- try to augment this by learning some interesting things about each individual that will help you remember them.
For example, I have learned a lot about the statistical contributions of Ronald Fisher, but I also try to remember him better by familiarising myself with his contributions in genetics and eugenics. No matter how much I might forget about Fisher, it is very easy to remember that he formulated the "sexy son hypothesis" in genetics. That is not something that is super important to understanding his contribution to statistics, but it is an interesting thing about Fisher that makes it easy to remember him. Similarly, I remember William Gosset by the fact that he worked at a Guinness brewery for almost all of his career. When I teach introductory statistics to students, I often mention this little titbit, and whenever I have occasion to drink a Guinness, I will usually bore my drinking partner half to death by bringing up Gosset's work on the Student-T distribution.
Write about the things you learn, even if it is not an academic paper: In some instances, there may be opportunities for you to incorporate what you learn into your publishable scholarly papers. Unfortunately, the large amount of effort involved in scholarly research means that this is not usually a feasible method of broad learning on a wide range of topics. For that reason, it is worth establishing some other avenue for you to write about what you have learned and present it to others. This could be writing articles or posts on a website or blog, answering questions on one of the StackExchange websites, giving presentations to colleagues, or incorporating what you learn into your lecture materials and teaching it to students.
Some researchers keep expository notes on things they are learning, and personally, I find that the easiest and most effective was to do this is to start writing up "partial papers" in the form of a scholarly paper whenever you get any new idea while learning a new subject. These can be expository papers that might or might not become substantial enough to warrant an academic publication, but in the meantime, they function as useful expository notes collecting and organising your thoughts on a topic you have studied. I have written hundreds of these partial papers, and most will probably never get turned into full published papers, but they are there on my hard-drive to allow me to look at my own exposition of an idea or area of analysis that was interesting to me. By framing the exposition as something that might one-day be an academic paper, I also put it in an organised manner, and save myself some work if I want to develop it for publication later.
Incorporate what you learn into your teaching: When you have learned a new thing that sheds light on your subject, try incorporating this into your lecture notes and adding it to your lessons to your students. Teaching is often a very effective method of learning, and it can be useful to solidify your knowledge.