I’ve been thinking about building more tools for myself. Some of the ideas I’ve been playing around with are around simplifying activity tracking further, possibly getting it to the point where it suggests things for me to do when my brain is fuzzy.

My current tracking system has two tiers. For my most-common activities, I use a custom menu that I can open from my phone’s home screen. I created the menu using Tasker. It’s easy to configure menu items to update my Quantified Awesome activity records as well as run other logic on my phone. For example:

• “Eat dinner” creates an activity record for “Dinner”, then starts MyFitnessPal so that I can log the meal
• “Walk home” creates an activity record for “Walk – Other”, then starts step-by-step navigation of the walk back to my house
• “Sleep” creates an activity record, then launches Sleep as Android
• “Ni No Kuni” creates an activity record, prompts me for what I want to do after an hour of playing, opens a page with tips for the game, and then reminds me of my plans after that hour passes

One advantage of using something on my phone is that I don’t have to wait for the initial web page from Quantified Awesome to load. My keyboard occasionally takes a while to come up, too, so the menu-based interface gets around that as well. Also, as I get the hang of using Tasker, I can set up more intelligent processes. The menu has a link to open the web version, so if I want to track something less frequent, I can always use the web interface.

In the web interface, I usually type a substring to identify the category I want to track. For example, “kitch” results in an activity record for “Clean the kitchen”. I use this interface if I need to backdate entries (ex: -5m), too.

In addition to the two interfaces above, I’ve been thinking about taking advantage of the predictability of my schedule.

Research into adaptive menus turns up quite a few design ideas and considerations. Since I’m building this for myself, I can get around many of the challenges of adaptive interfaces, such as privacy and predictability. I’m curious about the following options:

• Text-based input with minimal cues, as part of a more powerful command line
• Context-sensitive menu with a handful of items (3-4, with a link to more): I can probably suggest candidate activities based on the past two activity records. That might mean a little bit of latency as I check, though. It also means that the menu will keep shifting, so I’ll need to read it and find the item I want to click on.
  • For everyday use?
  • For really fuzzy moments?
• Static menu of frequent items, but adaptive highlighting (ex: green or bold, or fading out other things slightly)
  • Abrupt onset, others fading in over 500ms
  • Colour?
  • Weight?
• Split menu: frequent items on top, everything else below
  • Static
  • Adaptive
• Hierarchy of menus: speedy, but lots of tapping
• Cut off menu: show only the activities that come after the one I’ve just tracked

Hmm… It might be interesting to play around with different menu options. It would be good to experiment with NFC as well, especially early in the morning. =)

Related:

• “Dynamic versus static menus: an exploratory comparison (Mitchell, Schneiderman 1989): people preferred static menus
• “Comparing static, adaptable, and adaptive menus” (Findlater, 2001): people liked split adaptable menus
• “Exploring the design space for adaptive graphical user interfaces (Gajos, Czerwinski, Tan, Weld, 2006): spatial stability – copy instead of move, adapt slowly
• “Ephemeral adaptation: the use of gradual onset to improve menu selection performance” (Findlater, Moffatt, McGrenere, Dawson, 2009): abrupt onset + fading in other items
• “Predictive menu selection on a mobile phone” (Bridle and McCreath, 2005): Mobile considerations

Blogging should expand your brain. It’s a great tool for learning things, so why limit yourself to what you think you’re an expert on? I want to write about things I don’t know. Then I can help other people get started, and other  people can help me learn. (Hence the preponderence of “Thinking about…” and “Learning…” posts on my blog versus “How to…” posts.)

Research lets you jumpstart your learning by building on other people’s experiences. Fortunately, you have access to more information than you could ever read, thanks to the wonders of the Internet.

I’ve been re-learning how to research and how to synthesize that information for blog posts. It’s much more useful when you’re no longer trying to pad a school report with three to five reliable sources. Did you come across an interesting post on a blog? A great message on a forum? Go ahead and link to them, no PhDs required.

1. Make an outline of the questions you want to answer or ideas you want to explore.

You’ll be reading a lot. It helps to have a framework that shows you what you’ve covered and what you need to look for next. Here are some outlining tips from Journalistics. Here’s an example: my outline for blogging skills.

2. Search for “good enough” resources.

Don’t worry about finding the absolute best resource. Look for good-enough resources, and prioritize as you find more. Don’t link just for the sake of linking. Every link should add more insights or details.

I usually go through the first five to ten pages of Google search results. If people quote an even better source, I follow that link. Sometimes I’ll try different search queries based on the titles of blog posts I like.

You can quickly get a sense of whether a blog post is better than other things you’ve read. Does it give specific, punchy, perhaps unexpected advice illustrated with personal experiences, or is it your run-of-the-mill link-building blahblahblah? Speed-reading can pay off a lot here.

Want to go into greater depth? Look for relevant books and read them, summarizing the key points for your readers. Google Book Search is great for searching inside books, and Amazon’s recommendations are handy too. I sometimes check out seven or more books on a single topic, read them all over a week, and pick out key points for a blog post. This is an excellent way to add value, because most people won’t have the time to read the same books.

You can also check out other channels: podcasts, Twitter conversations, online Q&A sites, magazines, research papers… Go beyond blog posts when looking for resources, and you’ll find plenty of relevant material.

Good news – you can’t lose. If you find excellent resources right away, then you don’t have to write a big blog post. Just learn from those resources, and maybe write a post with your question and links to the best resources you found. If you spend an hour searching and you can’t find anything you really like, that’s fine too. Chances are that other people are frustrated by it too. Take that as a cue to write the blog post you wish you’d read.

3. Add key points and links to your outline.

By adding to your outline along the way, you’ll see how ideas are related to each other and where the gaps are. If you’re copying an exact quote, add quotation marks so that you don’t accidentally plagiarize it when rereading your notes. Better yet, paraphrase it right away. To make citations easier, add attributions or links. That way, you don’t have to chase down references.

Here are Cal Newport’s tips on how to use an outline to write papers quickly: outline the topic, find solid sources, capture quotes, and then turn that outline into your paper. Works for blog posts too.

4. Reorganize your outline and notes.

Take another look at your outline and reorganize it until the flow makes sense. The order in which you find resources is rarely the order in which you want to share them. For example, you may want to categorize the tips you’ve picked up, combine similar items, and arrange them in a logical order. You can also compare different viewpoints and line up the arguments for each alternative, then conclude with recommendations. With a little paraphrasing, you might be able to fit the tips into a creative mnemonic. Play around with the structure before you start writing your post.

5. Add value through summaries, insights, and personal experiences.

While searching for resources, you might have noticed an intimidatingly large number of results. For example, searching for how to do research for your blog gets more than a billion search results. Why add one more?

You’ve probably also noticed that many results are missing something. Maybe you didn’t find a single post that answers the exact question you wanted to explore (or if it did, the answer was buried in an intimidatingly long post). Maybe most of the search results are fluffy self-promotional pieces. Maybe they’re badly formatted and hard to read.

There’s room for you to add something of value, even if it’s just a good summary. Other people could spend a few hours reading all those search results and books, and trying to map out the insights from various resources… but if you’ve already done the work, why not save them some time and share what you’ve learned so far?

Add your own tips. While researching, you’ll probably think of a few points that you can’t find in the pages that you’ve seen so far. Write them down. Maybe other people didn’t write about those tips because they’re more experienced than you and they took that for granted, but other beginners will find those tips useful. Maybe other people didn’t write about those tips because you’re more experienced than they are (or at least you’ve made different mistakes). Add your thoughts.

Tell personal stories. Instead of just sharing advice, share your experiences in applying that advice. What worked well for you? What could have gone better? This is a great way to learn more, too – you’re not just passing on advice, you’re trying things out and adding your own perspective. A.J. Jacobs and Gretchen Rubin do this really well in their books on life experiments, and are definitely worth reading.

I hope these five steps will help you learn new things while writing blog posts. You don’t have to limit yourself to what you know. You can use your blog to help you learn. Good luck and have fun!

How do you research ideas for your blog posts?

Image credits: Stack of books by discpicture (via Shutterstock) 

Author’s note: I feel like this post should have more links in it, given the subject. I’m not particularly impressed with most of the posts I came across in my research, though (see the last point in step 2). Do you have any favourite resources along these lines?

I love research-backed books that help us understand why we do what we do. Paula Szuchman and Jenny Anderson’s Spousonomics: Using Economics to Master Love, Marriage, and Dirty Dishes was no exception. The book takes a look at common marital conflicts and situations, showing the underlying economic principles that influence our actions. For example:

• Division of labour: Splitting chores equally may not result in the most efficient or the happiest of marriages. Specialize, remembering that payoffs can change over time.
• Loss aversion: People hate to lose, which can result in really drawn-out fights. The advice to “never go to bed angry” can backfire. It’s okay to have time-outs.
• Supply and demand: If you want something to happen more often, don’t make it costly or risky.
• Moral hazard: It’s easy to take good things for granted. It’s also easy to end up trying to avoid any sort of conflict. The sweet spot is in the middle, where you’re not taking your relationship for granted, but you’re not paranoid about your spouse quitting.
• Incentives: Think about the incentives you use and if they’re really effective. Trust can be much more useful than nagging.
• Trade-offs: Think at the margin: consider the costs and benefits of small changes. Ignore sunk costs when making decisions. Get over the “it’s not fair” fixation.
• Asymmetric information: Communicate clearly. Don’t play games by hiding or withholding information. Figure out the essentials of what you need to share so that you don’t overload your spouse.
• Intertemporal choice: It’s easy to make good decisions for the future, but hard to stick with those decisions in the present. Use commitment devices to help you stick with your resolutions or good ideas.
• Bubbles: Non-bubbly married life is normal, so don’t stress out if you’re no longer infatuated. Beware of being unduly influenced by groups – just because everyone else seems to be doing something doesn’t mean it’s right for you, too. Don’t get overconfident.
• Game theory: Don’t let the urge to retaliate or overcompensate lead to you to wildly polarized positions. Work together to get optimal results, not just individually-optimal results, and use commitment devices to help you stick with it.

The book goes into far more depth, and is an excellent read. It’s illustrated with case studies (problem couples who usually end up patching things up) and lots of research.

Here are some thoughts I particularly like:

If there are areas you care about but you feel helpless in, put in the time and effort to develop the comparative advantage in at least one of them. The authors tell the story of one economist who put the time into at least learning how to bathe an infant so that his wife wouldn’t end up with all the child-rearing tasks – and so that he wouldn’t get tempted to take advantage of that kind of a division.

Looking for things to read? In terms of marriage research, I’d recommend “Spousonomics” and Susan Page’s “The 8 Essential Traits of Couples who Thrive”. What do you like?

My research supervisor is chairing the ACM Hypertext conference that will be held in Toronto from June 13 to 16, 2010. The conference focuses on linking and interconnectivity, and will have sessions on Web 2.0, social computing, and the semantic web. Tracks:

• Social computing
• Adaptive hypermedia and applications
• Hypertext in education and communications

The deadline for paper submissions is February 14.

ACM Hypertext2010

Both our internal Social Networks Analysis community and Colleen Haikes (IBM External Relations) tipped me off to some absolutely fascinating research on the quantitative correlation between social networks and performance based on an analysis of IBM consultants. You can read the research summary and view the presentation, or read the research paper for all the details. Highlights and what I think about them:

• Structurally diverse networks with abundance of structural holes are associated with higher performance. Having diverse friends helps. The presentation gives more detail – it’s not about having a diverse personal network, but it’s about connecting to people who also have diverse networks. I suspect this is related to having connectors in your network.

Betweenness is negatively correlated. Being a bridge between a lot of people is not helpful. The presentation clarified this by saying that the optimal team composition is not a team of connected superstars, but complementary team members with a few well-connected information keepers.

Strong ties are positively correlated with performance for pre-sales teams, but negatively correlated with performance for consultants. Pre-sales teams need to build relationships, while consultants often need to solve a wide variety of challenges.

Look! Actual dollar values and significant differences! Wow. =)

Here’s another piece of research the totally awesome IBM researchers put together:

A separate IBM study, presented at the CHI conference in Boston this week, sheds light on why it’s easier said than done to add new, potentially valuable contacts to one’s social network in the workplace.  The study looked at several types of automated “friend-recommender” engines on social networking sites.  The recommender engines used algorithms that identified potential contacts based on common friends, common interests, and common hyperlinks listed on someone’s profile.

Although most people using social media for the workplace claimed to be open to finding previously unknown friends, they were most comfortable with the recommender engines that suggested  “friends’ friends” — generally, people whom they already knew of.  The friend-recommenders with the lowest acceptance rates were those that merely look at whether people have similar interests — although they were the most effective at identifying completely new, potentially valuable contacts.  Friend-recommenders that took the greatest factors into account were deemed the most useful.  (IBM’s Facebook-style social networking site, Beehive, uses this type of friend-recommender engine.)

Personally, I don’t use friend recommenders to connect to completely new people, but they’re great for reminding me about people I already know.

Check out the research – it’s good stuff. =)

(cross-posted from our external team blog, The Orange Chair)