Alright. Given that you’re interested in psychology, feel free to check these resources out: https://dnav.international/video-audio-resources/ https://dnav.international/wp-content/uploads/DNA-V-workbook-april-15-2020.pdf
These are introductions to Acceptance and Commitment Therapy.
You can also check out the Healthy Minds Program https://hminnovations.org/meditation-app
You mention not having money for therapy. There is evidence suggesting that therapy like Acceptance and Commitment Therapy is effective even if learned through books. What is important is to learn the mental processes that matter.
Here is an approach to therapy that you could try: https://youtu.be/o79_gmO5ppg
Sorry if my questions sound harsh. I genuinely want to know if this could help. How do you feel about reading books? Have you done it before? Do you have a place and time to read without distractions? Would reading from a device be feasible for you?
Professionals have large networks of neurons. They are sturdy and efficient from repeated use. Memory palaces help to start the construction of these large networks of neurons. Afterwards, as another commenter noted, the knowledge is deeply processed. Mnemonics are replaced by networks of meaning. It is no longer “This algorithm rhymes with tomato”, but “This algorithm is faster if the data is stored in faster hardware, but our equipment is old so we better use this other algorithm for now”.
Broadly, the progression of learning is: superficial learning, deep learning, and transfer. Check out Visible Learning: The Sequel by John Hattie for more on this.
Edit: To directly answer your question, experts have so many sturdy neural hooks on which to hang new knowledge that mnemonics become less and less necessary. Mnemonics may be particularly helpful when first learning something challenging, but are less necessary as people learn.
You could also check out a paradox called the expert paradox. We used to think memory is boxes that get filled. This idea was directly challenged by Craik and Lockhart’s Levels of Processing. Levels of processing supports the idea that “the more you know, the faster you learn”. Note that this is domain-specific. In other words, an expert in dog training won’t learn quantum mechanics faster than anyone else.
I’d say feeling admiration for others. People who are kind, patient, insightful, and critical thinkers. People who look at how political goods (including wealth) are distributed and can think critically about it. Nutomic and Dessalines for sure.
On mobile atm but there’s the Princeton books on Computer Science
I see your concern for truth in any scenario, and I agree validity should be a constant consideration! However, bias and astroturfing are different. Bias is the lens that we use to look at reality. Astroturfing is forcing lenses onto many others without them knowing. It is a deliberate campaign.
I like the novelty/predictability ratio idea. There is also the idea of “create expectations and satisfy them”, which leads to a sense of stability. Our cultures and genres create expectations. Rhymes tied to a certain metric can become part of these expectations. Of course, you can also create expectations and frustrate them, which leads to a sense of instability. Searching for “fakeout rhyme” videos makes this evident. Pat Pattison, an expert in songwriting, could be a good source on this ☺️
There’s also some thinkers who say that thinking only ever happens through language, so talking could be more of a mapping of “thinking words” onto “communication words”.
Yes! Rhetoric, the study of the available means of persuasion! Lots of professions still do that today: speech writers, advertisement creators, academic rhetoricians, some linguists, some anthropologists or sociologists, some historians…
It depends on the author! Authors create symbolic universes and they get to choose the rules of those universes. You can read Robert McKee’s work for more on this.
I appreciate your passion for scientific literacy - it’s crucial for combating misinformation. However, I’d like to share some perspectives that might broaden our understanding of scientific knowledge and how it develops.
First, it’s worth noting that the distinction between “theory” and “hypothesis” isn’t as clear-cut as we might think. In “The Scientific Attitude,” Stephen McIntyre argues that what truly defines science isn’t a rigid set of rules, but rather an ethos of critical inquiry and evidence-based reasoning. This ties into the “demarcation problem” in philosophy of science - the challenge of clearly defining what is and isn’t science. Despite this ongoing debate, science continues to be a powerful tool for understanding our world.
Your stance seems to align with positivism, which views scientific knowledge as objective and verifiable. However, other epistemological approaches exist. Joseph A. Maxwell’s work on critical realism offers a nuanced view that acknowledges both the existence of an objective reality and the role of human interpretation in understanding it.
Maxwell defines validity in research not just as statistical significance, but as the absence of plausible alternative explanations. This approach encourages us to constantly question and refine our understanding, rather than treating any explanation as final.
Gerard Delanty’s “Philosophies of Social Science” provides a historical perspective on how our conception of science has evolved. Modern views often see science as a reflexive process, acknowledging the role of the researcher and societal context in shaping scientific knowledge.
Larry McEnery’s work further emphasizes this point, describing how knowledge emerges from ongoing conversations within communities of researchers. What we consider “knowledge” at any given time is the result of these dynamic processes, not a static, unchanging truth.
Understanding these perspectives doesn’t diminish the power or importance of science. Instead, it can make us more aware of the complexities involved in scientific inquiry and more resistant to overly simplistic arguments from science deniers.
By embracing some psychological flexibility around terms like “theory” and “hypothesis,” we’re not opening the door to pseudoscience. Rather, we’re acknowledging the nuanced nature of scientific knowledge and the ongoing process of inquiry that characterizes good science.
What do you think about these ideas? I’d be interested to hear your perspective and continue this conversation.
Thanks for the response. I guess I do see much of human behavior through a contextual behaviorist lens. Sorry if it seems excessive. I am not Hayes or Hoffman. It is just frustrating to see blanket explanations for human behavior, instead of understanding specific processes. I guess I really want to avoid the fundamental attribution error and reductionism, something contextual behaviorism deliberately aims to avoid.
While I recognize Emotion Focused Therapy is helpful to understand and, if possible, change social behavior (which is why I mentioned it previously), I maybe should have brought up Emption Construction Theory or even Sapolsky’s multi-lens framework, considering different timescales of explanation. Would you have suggested something different? When does contextual behaviorism fail?
Thanks for helping me potentially falling into reductionism. I wouldn’t want to fall in that trap.
Anytime we talk about human behavior, it is a good idea to learn and use the lens of behavioral contextualism. If and only if the contextual behaviorist analysis concludes that human connections is the issue, Sue Johnson’s texts will be great to understand your coworker. Otherwise, the contextual behavioral analysis will let you know what’s going on.
Edit: Removed excess text
I don’t get it. Can you give context?
Ultimately, yeah. The article points out that the way they want to do it is with unique designs, carbon neutrality, and transparency in the production chain.
I agree that we shouldn’t jump immediately to AI-enhancing it all. However, this survey is riddled with problems, from selection bias to external validity. Heck, even internal validity is a problem here! How does the survey account for social desirability bias, sunk cost fallacy, and anchoring bias? I’m so sorry if this sounds brutal or unfair, but I just hope to see less validity threats. I think I’d be less frustrated if the title could be something like “TechPowerUp survey shows 84% of 22,000 respondents don’t want AI-enhanced hardware”.
I MISSED THE EQUIVALENT OF PLACE IN LEMMY? Does anyone have context?
Agile is indeed more of a mindset than a rigid system. In my recent experience helping a tabletop game team, we applied Agile principles to great effect. Rather than trying to perfect every aspect of the game at once, we focused on rapidly iterating the core mechanics based on player feedback. This allowed us to validate the fundamental concept quickly before investing time in peripheral elements like the looks of the game.
This approach embodies the Agile value of ‘working product over comprehensive documentation’ - or in our case, ‘playable game over polished components’. By prioritizing what matters most to players right now, we’re able to learn and adapt much more efficiently.
Agile thinking helps us stay flexible and responsive, whether we’re developing software or board games. It’s about delivering value incrementally and being ready to pivot based on real-world feedback.
Sorry if you know this game, but I’ve met plenty of people who haven’t and I’ve never seen it mentioned online until I searched for it today: Contact!