Berlin Show & Tell #3

On March 26th, the Berlin QS group had its third Show & Tell at Betahaus, with over 60 attendees and four presenters.

First up was Louis Crowe, a medical researcher who discussed new applications for neuromuscular electrical stimulation (NMES). You may be familiar with this from the overhyped “ab belts” from late-night infomercials. As Louis described, the technology also has many therapeutic uses, and it can be more effective as exercise when used at higher voltages — something he’s explored through self-experimentation and tracking, and showed us with a startling live demonstration during his talk.

Cassie Zhen, a graphic designer and fitness trainer, presented on a one-month self-experiment in which she materially improved her cardiovascular fitness — as measured by resting heart rate and VO2 max — through a  rigorously tracked diet and exercise program. Her presentation is available here.

Marc Lallemand, an engineer working at a startup, showed us what he learned from several months of tracking his work hours, alcohol and caffeine consumption, emotional state and various other aspects of his life.

Finally, Florian Schumacher, my co-organizer, presented his results from comparing six different pedometers. Tracking his everyday activity with a Basis Band, Bodymedia Link, Fitbit One, Fuelband, Jawbone Up and LUMOback, he analyzed the difference between the step count these devices had measured and found a total variation of 26.8%. He emphasized the motivational effect pedometers have on his activity level, and pointed out that the devices which build a close feedback loop by making the information easily accessible and understandable are the ones that maximize this benefit.

Florian recently started to work part of his time at a standing desk and began to measure and improve his posture with the LUMOback sensor measured above. By comparing the LUMOback score over several days, he showed how sitting long hours in a conference chair lead to a lot of slouching, while working at the standing desk made it easy for him to keep a healthy posture most of his day.

Finally, Florian presented his results from tracking his time by project, using the OfficeTime app. He found it helpful in both setting better priorities and increasing his focus and concentration.

Why Isn’t Spaced Repetition Software More Popular? (Part 2)

This is adapted from a presentation I gave at the Berlin Quantified Self Meetup in November 2012. There are two parts:

  1. What is spaced repetition software?
  2. Why don’t more people use it, and what can we do about that?

Part 2: Why Isn’t Spaced Rep Software More Popular?

In my previous post, I introduced the field of spaced repetition software; in this one, I’ll discuss why it hasn’t spread further and some new apps that might change that, including one that I’m working on myself.

First of all, I’m not the only person asking this question. Here’s a quote from Gary Wolf, co-founder of the Quantified Self movement, who wrote a great article on Piotr Wozniak and Supermemo:

Why isn’t this amazing technique more common? I explained some of the obvious reasons in my story. Still, I expected that, having launched the idea into an environment well suited to nourish it (many Wired readers are passionate learners, and many of them have software, design, and business skills), I would soon see some new implementations. And I was not disappointed. There are half a dozen versions of Supermemo in common use today. But they are used by very few people. Clearly, the problem remains unsolved.

And the Supermemo wiki has a long list of ideas, some more constructive than others. But they’re clearly aware of the problem.

I have some first-hand experience with this: when I was using Anki and Mnemosyne to study German, I recommended them to many of my classmates, and a few of them got as far as installing the software and loading up my German/English deck (which I would email them) but none of them really stuck with it. And these were smart, relatively computer-savvy people, often with better overall study habits than me, but this kind of software just didn’t quite “click” for them.

Why not? Here are some of those “obvious reasons”…

  • It’s difficult / mentally taxing. No use beating around the bush. These apps do require a certain type of concentration that’s a little uncomfortable at first. But once you get over that small initial hurdle… well, it’s still not Angry Birds exactly, but I find it a lot less difficult (and more satisfying) than other study methods.
  • None of the engagement methods of other educational software, like levels and achievements, social features, or “gamification.” I’m a skeptic on just how engaging (as opposed to distracting) some of these other features are, but there’s no question that some of them help, especially early on.
  • Not enough feedback, or not the right kind. This is a critical one. Notice that the graph I showed you — progress over time — does not come standard in Mnemosyne. I had to record that data every day in Excel and make it myself. You can get “snapshot” charts in the app, but not time-oriented ones, which are a better motivator.
  • Algorithm is too “strict.” If you stop using these apps for a few days, you’ll pile up lots of “overdue” cards. In theory you can ignore them and just take it slow, but there’s still that counter in the corner of the screen reminding you that you’re “behind.” In my mind, a good study app should not try too hard to dictate the pattern of usage, but rather adapt to make the most of whatever time the user puts in.
    There’s also the “one piece of info per card” rule, which I’ll come back to. And because of the moving average nature of the algorithm, it can be hard to convince the software that you really know a card, and you’ll often keep seeing it after you’ve rated it very highly. Finally, when I said earlier that you can define the ratings for yourself, I think some purists would object to that too.

Here are two other reasons that I haven’t seen elsewhere, although to me they’re equally obvious:

  • Still mostly client-side apps, not cloud-based
    • syncing among different devices is annoying
    • risk of data loss
    • compatibility and version issues
  • Still based on user-generated content
    • entering your own cards is time consuming, especially on a phone or tablet
    • downloading other users’ decks isn’t always much better
    • formatted text and other rich content are difficult

The risk of data loss is very real. It’s easy to say “well, you should be backing up everything anyway,” but the reality is that most of us don’t, and it’s hard enough to get users to adopt this one new habit without making them change others.

And the focus on user-generated content is a real problem as well. Most people are just never going to enter their own cards in large numbers. Downloading other users’ decks introduces the risk of typos and grammar mistakes (a huge problem if you’re learning a new language, less so if you’re studying something else) and, more importantly, their content is unlikely to be an exact match for what you want to learn, and it may not be comprehensive or well-formatted. I’ve found that downloading other users’ decks is a good way to try out the software, or try out a new subject, but when I know what I want to learn (say, B1 German vocabulary), I spend as much time editing someone else’s deck as I would in creating my own. And it’s very time-consuming to go beyond a small amount of unformatted text (or maybe a single image) on each side of a card.

Enough complaining — what can we do about it?

Well, here are some encouraging steps forward:

  • Mobile, tablet and web extensions for Mnemosyne and Anki
  • Fully “cloud-based” implementations (Kleio)
  • Shared editing “wiki” models for user-generated content (Memrise)
  • Moving towards professionally-created content (Skritter, Chinese3D)

The mobile and web tools around Mnemosyne and (particularly) Anki are getting better all the time. There are also some people building fully cloud-based implementations, and I recommend Kleio if you want to try one. Memrise uses some other mnemonic methods in addition to a form of spaced repetition, but in any case they’re the first app I’m aware of that lets users edit the same shared decks, so their corrections and tweaks are cumulative. This also allows a lot of “meta” content, with more than one piece of information per card. I think these things have a lot to do with the fact that they’ve achieved a relatively large user base in a short period of time, and (arguably) wider name recognition than the other apps I’ve been talking about.

The alternative to the “wiki” approach, of course, is professional content, and I know of at least two apps that do that for Asian languages: Skritter and Chinese3D. In this case, fixed professional content allows much more intricate graphical interfaces and user interaction, including drawing the actual characters on the screen in Skritter. If you’re studying Chinese or Japanese, I recommend checking these out.

And finally, I’ve developed my own prototype for European languages, with each pair of languages built from the ground up by professional translators and tagged according to real-world metrics (like the A1-C2 European language standards, or particular official exams). I’ve also simplified the algorithm and rating scale, added lots of extra content and formatting to each card, and made various other attempts to address the issues above.

The first “deck” is German for English speakers, which is now up to several thousand cards. We’ve got the web app up and running, and we’re starting on native mobile apps now.

colibri_1

colibri_2

I won’t go into more detail about my project here, but if you’re learning German and want to be a beta tester, send me an email at plewis@gmail.com and I’ll get you set up.

In any case, if you’re new to the subject of spaced repetition, I hope I’ve gotten you interested enough to try at least one of the tools I’ve mentioned. If you’re a user or creator of a tool that I haven’t mentioned, I’d love to hear about it and would be happy to append it to this post. And if you have other questions or just want to discuss (or disagree with) anything I’ve written here, just drop me a line.

Participants Sought for Study on Quantified Self Movement

This is a guest post by Marcia Nißen, who’s examining the Quantified Self movement as part of her Bachelor’s thesis.

Why do you measure yourselves? How much time do you invest in self measuring? What do you track and how do you track it? I haven’t been able to get my mind off these questions since getting involved with the Quantified Self movement. In my Bachelor’s thesis, I look into individual motivations and motives for self measurement and now need your help. If you measure or record anything in your life, I would appreciate it if you would take part in my survey.

Filling out the questionnaire should take 15 to 20 minutes. Your responses will remain anonymous and will of course not be given to third parties. I will be glad to provide the Quantified Self community with all results and findings from this data when I finish my  thesis. You can find the survey here: www.ksos.kit.edu/qs

Marcia Nißen studies industrial engineering at the Karlsruher Institut für Technologie (KIT) and is currently writing her Bachelor’s thesis on the topic “Self-Tracking Activities and Motivations”. Since September 2012 she has been blogging at vermessen-leben.de about the progress of her undergraduate work and phenomena she encounters on the topic of Quantified Self.

[Thanks to Edward Tanguay for the English translation of this post]

Welcome to the Quantified Self Berlin Group

This is a brief introduction for members of the new English-language Quantified Self group in Berlin. Of course, we hope to meet many of you in person at our first meetup on Thursday Nov. 22nd.

First, if you’re new to the overall Quantified Self movement, head over to their main website at quantifiedself.com and start with the About section or the Three Prime Questions.

Second: other than this site, the main way to keep up with our Berlin-area events is via our Meetup group or by following us on Twitter @QS_Berlin.

Bear with us while we sort out the exact structure of this site going forward, but at a minimum you’ll soon be able to follow the English- and German-language posts separately, and we’ll try to translate the most important posts so they’re available in both languages.

We’ll be posting more info here before and after this week’s meeting, and we’ll be covering a lot more at that meeting about how to sign up for future presentations and demos and how the group will operate. In the meantime, feel free to contact me (at plewis@gmail.com) or the other organizers with any questions about the new group.