This is a positive psychology course based on work by Seligman et al.
Results: Repeated measures analyses showed that the PPEs led to lasting increases in happiness, as did the positive placebo. The PPEs did not exceed the control condition in producing changes in depression over time.
Conclusions: Brief, positive psychology interventions may boost happiness through a common factor involving the activation of positive, self-relevant information rather than through other specific mechanisms. Finally, the effects of PPEs on depression may be more modest than previously assumed.
Expectancy control (early memories): “[...]Every night over the next week, set aside about 10 minutes before bed [...] to log on to this website to write about an early memory.”
Positive placebo (positive early memories, in addition to rationale above): “[...]
Every night over the next week, set aside about 10 minutes before bed [...] to log on to this website to write about an early positive memory.”
Three good things (Seligman et al., 2005): “[...] log on to the website daily for seven days to list three things that went well on that day and why they happened.”
Using signature strengths in a new way (Seligman et al., 2005): “This exercise consists of two parts. You will take a questionnaire that gives you feedback about your strengths. This will take about 45 minutes. The next day you will be asked to use these strengths in new ways every day for one week [...]”
So regardless of whether the specific exercises are uniquely useful, it seems like it's valuable to make yourself focus on the positive stuff.
Now, why did I say "mostly" and "almost"?
1. The best technical courses are on Udacity. You may disagree but I think enough people would agree that it ought to be somewhere on the list.
2. Learning to learn is popular but its kind of vacuous. (You may disagree, and this time I may be in a tiny minority who hold this view). So I think the sentiment reader might need tweaking.
Still, all in all, a great resource. I am bookmarking it and am glad you did this.
Udacity is the 3rd most recommended course provider after Coursera and edX. Those courses will make it into v2.
It seems to me that the comments on the learning to learn course generally read like positive recommendations, so I think HN disagrees with you there . But I do want to experiment with different sentiment analyzers.
1. The pomodoro technique really is useful if you're a hopeless procrastinator like me. It's saved my butt numerous times.
2. The explanation of the value of alternating between focused intense thinking and diffused thinking also helped clarify why unfocused thinking is genuinely productive (of course, as long as it's mixed with focused thinking). I've used this to work around mental blocks when I got too stuck in the focused mode.
You can read a blog post about building bicycle wheels in five minutes and get most everything you'd gain from going to a weeklong course, but the difference is all in how you'd engage with it. A longer discussion, open area for questions, and building familiarity with the material drive the skill home whereas that 5 minute blog post might as well disappear into the depths of memory the second you navigate elsewhere.
I took the course and while I agree that I wanted more depth, it certainly wasn't "vacuous" given the context. And it should be noted, the materials of the course follow some of the concepts taught within - they're doing their best to make sure you learn their basic concepts of how to learn.
Learning How To Learn is an entry level way to get from practically nothing (everyone who can comprehend the course has some fundamental basics; e.g. spaced repetition we learn at elementary school in The Netherlands) to a more productive learning environment. It does that by teaching you techniques via theory, practice, and ultimately a quiz about the material. After you completed the course, you will understand the techniques, have familiarized yourself with each of these, and you can likely apply them. It is also likely you found a preferred technique (or found a confirmation that your previous preference is the best one for you). If you already know these techniques (such as spaced repetition, focused & diffused mode, pomodoro technique) then the course has little value. You could still help people on the forums (explaining something has great value for yourself as well), or learn a thing or two from the forums or Friday mailing. If people don't know how to learn then all the other courses on Coursera and other MOOCs are useless. The popularity of the course and the positive reviews underline its usefulness.
You can find naysayers for every course. For example, I'm a naysayer of the Cryptography I course in a way. I recommend it (as far as I finished it; the first 2 chapters I did) because for me it gave me gigantic headaches and migraine. It isn't for me, I'm just not intelligent enough for it combined with the headaches and migraine it didn't work out and I had to call it. YMMV.
You've completely missed the point and even failed to assume that the OP was well-meaning.
The whole point of making it clear that the content of an online course can easily be learned by reading a blog post on the subject is to warn potential users that they risk wasting their precious time watching hours of videos consisting mostly of useless filler when spending 5 minutes reading a blog post would get you the same results.
Frankly, this is a major and all too frequent problem witg MOOCs. Sadly, some courses are obvious exercises on how to stretch close to no content into hours of video.
Personally I would hate to waste hours of my personal time unnecessarily, thus I appreciate these warnings.
> Personally I would hate to waste hours of my personal time unnecessarily, thus I appreciate these warnings.
These warnings can be made with about any online content. It boils down to "I found it a waste of time"; data suggests the course was NOT a waste of time however. I appreciate such data over anecdotal evidence.
The point is that the assertion was made regarding this specific course but not any other. You're the one trying to put up a strawman by forcing the assertion to cover other courses, when nothing of the sort has been made.
>Additionally, it is not possible to get on the same level via a 5 minute blog post compared to completing the course. Such counts for most if not all courses.
I'm not familiar with the course, but I'm very familiar with other MOOCs from edx, coursera, and udemy. Based on my personal experience I can say that some courses, particularly technical courses, are indeed packed with useless filler content, and the same learning experience can be had by reading a small blog post covering the subject.
This assertion is not uncommon, and unfortunately is a recurring problem with MOOCs.
The problem is that it doesn't bring anything new to them, but they forget that other people don't have the same knowledge as they do. This is called the course of knowledge, where you forget what it was like before you knew something.
What I can say about "Learning how to learn" specifically is that it covers how to encode information for better retention, what strategies to use to increase long-term recall (there are 3 and they're unintuitive), how to use chunking, how to build habits.
Sure, you could cover these topics in 5 minutes, but you wouldn't do them justice. Especially for someone who's encountering them for the first time.
Is that universally agreed on? The Udacity courses I had looked at (full stack development, AI for self driving cars) were good and insightful, but somewhat half-baked, and not as good as edX or Coursera.
 Earlier comment where I asked a basic question that went beyond the understanding of the literal face of the course. https://news.ycombinator.com/item?id=18596450#18601298
I would be interested (if you have the energy) to see which Coursera and Edx courses you preferred to the Udacity courses you liked.
https://www.coursera.org/specializations/robotics (also available at edx as https://www.edx.org/micromasters/pennx-robotics)
And I would rank them in the order of edx, coursera, and udacity last.
It's not totally fair because the best comparison for udacity should be their self driving car nanodegree but it doesn't let you audit for free and I don't care for certificates. From the few udacity courses I did do, I felt their videos are too short and triggers my ADHD to go do something else after watching each minute or two long video. Edx/coursera felt a lot more like university lectures and felt more rigorous in comparison.
Self-driving car engineer nanodegree
(not the one with "intro" in its name)
Robotics software engineer nanodegree
Flying car and autonomous flight engineer nanodegree
Just as a sample, this is one of many projects I completed as part of the self-driving car engineer nanodegree. My code controls a car driving on a highway with other cars.
What You'll Learn:
Understand essential algorithmic techniques and apply them to solve algorithmic problems
Implement programs that work in less than one second even on massive datasets
Test and debug your code even without knowing the input on which it fails
Formulate real life computational problems as rigorous algorithmic problems
Prove correctness of an algorithm and analyze its running time
Algorithmic Design and Techniques
Learn how to design algorithms, solve computational problems and implement solutions efficiently.
Data Structures Fundamentals
Learn about data structures that are used in computational thinking – both basic and advanced.
Learn how to use algorithms to explore graphs, compute shortest distance, min spanning tree, and connected components.
Learn about NP-complete problems, known as hard problems that can’t be solved efficiently, and practice solving them using algorithmic techniques.
String Processing and Pattern Matching Algorithms
Learn about pattern matching and string processing algorithms and how they apply to interesting applications.
Dynamic Programming: Applications In Machine Learning and Genomics
Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.
Graph Algorithms in Genome Sequencing
Learn how graphs are used to assemble millions of pieces of DNA into a contiguous genome and use these genomes to construct a Tree of Life.
Algorithms and Data Structures Capstone
Synthesize your knowledge of algorithms and biology to build your own software for solving a biological challenge.
Learning how to learn is a vital part of this list because online courses are notorious for having people burn out and lose interest so it's especially important that these people can stick with a course using actual techniques.
I think it’s mostly a matter of engagement and commitment (no real penalty to dropping a MOOC and it didn’t cost much, if anything) and not that burnout is any worse. IOW, the rate of loss of interest might be no higher, but the initial level of interest might be lower, putting you closer to the threshold of dropping out.
Full time university is also the last time I had no other life obligations...
I think many online learning places are making a large mistake by not letting people sample the first 3 or 4 lessons.
I too have signed up for and left a rather large number of MOOC style courses simple because signing up for the course is often the only way for me to see if I enjoy the course material, the teacher, and the teaching style—all three of which vary wildly course by course on every site.
It seems to me they would be getting much more accurate numbers on completion if they didn’t hide the courses behind so much mystery. It would also have the benefit that we wouldn’t feel like we’ve “dropped” so many courses.
And also like you, I didn’t drop many courses at uni, but there was also more information available about the exact course material and there was much more consistency of teaching style. Also many were required for a degree and getting the degree was my primary purpose at the time, MOOCs however are more of a free time fun time thing for me so I’m much more picky.
However, my experience was that this class didn't effectively develop that skill or the habit for me.
I agree. I thought that it would teach me something revolutionary but it didn't. Granted, some of the things they teach are useful.
I think the course is just a victim of some people hyping it up too much.
Check out HN.Academy and let me know what you think. It's the result of mining the HN archives for references to online courses and then ranking them and displaying all references in one place.
Ranking currently takes into account HN stories (points) and comments (sentiment, karma, estimated points).
I had started with a much broader set of course providers, but Coursera ended up swamping the rankings of pretty much all the other providers. edX is also in the rankings with a few courses. I plan to add more providers but as of now none of them will impact the top rankings.
If you were looking to start a new learning endeavor in the new year... here ya go.
even without that, this is an awesome list. thanks.
Awesome page, though!
Some might be beyond high school level, like fundamental theorems of arithmetic (unique prime factorization) and algebra (polynomial factors/zeros). There's also non-integer exponents, defining reals etc.
All this stuff is used in High School but must be taken on faith. Good for believers, bad for skeptics.
Or is this just Mathematics 101? [my engineering maths didn't cover it]
Mathematics: Its Content, Methods and Meaning
by A.D. Aleksandrov,
, M.A. Lavrent'ev
may cover this in book form. (FWIW I have not read this, but intend to at some point)
That said, for a rigorous proof-based approach to high school math, you may enjoy "Basic Mathematics" by Lang: https://www.amazon.com/Basic-Mathematics-Serge-Lang/dp/03879...
> Calculus: Single Variable Part 1 - Functions
Coursera · University of Pennsylvania https://www.coursera.org/learn/single-variable-calculus
Perhaps we need a separate index that's just YT (and Vimeo?)?
A previous related work of mine is TechYaks , which ranks software tech talks using (among other signals) HN recommends.
I have another one in the pipe...
Edit: Nice work! Next steps would be to sort and collate similar topics.
Eg, the Johns Hopkins University "Data Science" course isn't worth doing (unless maybe it has been updated?), and note that most of the comments are pre-2017.
It's an R course, but it teaches pre-Tidyverse R.
Also it's not a great course in that the assignments aren't synced to the lectures - you need to know lots of stuff which haven't been touched on to complete the assignments at each stage. (Source: I did it in 2014 or 15)
It'd be neat if there was a search feature that let us search by subject or keyword or any other course metadata.
This means Blockchain and crypto are there and I doubt that's the most valuable thing you can learn this year.
* Compilers: https://lagunita.stanford.edu/courses/Engineering/Compilers/...
* Automata Theory: https://lagunita.stanford.edu/courses/course-v1:ComputerScie...
It's incredible how these free courses are rolling out.