Engineering Insight: The Foundational Principles of Human-Textbook Interaction®

First of all, Human-Textbook Interaction (HTI) is not a real field, and “HTI” is not a recognized acronym. Secondly, the term is not protected as a registered trademark (though the font may be the property of the Microsoft Corporation…). Thirdly, even if it were and was, I wouldn’t enforce it, since this document is at least as much a desperate plea as it is intellectual property. Fourthly, the term, Human-Textbook Interaction, is a play on the (actual) field, “Human-Computer Interaction (HCI),” a sub-/interdisciplinary area of engineering psychology, computer science, and industrial design. As such, I selected “textbook” for its comparative resemblance to a computer program or website, where “Lecture,” “Instruction,” and so on felt a little clunky or vague. In general, though, any version of an educational item or instance can be substituted accordingly.

Up through about the 80s, computers were quite user-unfriendly: large, slow, clunky, and complicated, most could only be run by trained professionals. These machines appeared to be (and in a sense were) the playthings of electro-mechanical engineers, and generally required about that level of expertise to make work. As companies like IBM and Apple sought to make computing available to the masses, the field of HCI emerged. Its principal concern was making computers “User-Friendly” – transforming these gizmos into something that non-specialists could use. Implicit within that goal was the making of computers into something that non-specialists could imagine themselves using. Making it usable wasn’t sufficient if the consumers in the market were so intimidated by the machine they wouldn’t bother to try. (Ever gotten one those whiz-bang space-age espresso machines, the ones where the control panels looks like an airplane cockpit? Think that, but several orders of magnitude greater.) HCI is the field that allows us normal folk to approach these staggeringly complex machines with ease and fluidity, and it’s built on some foundational principles: point-and-click, green-means-go, edged-boxes are clickable, a spinning wheel means “I’m working on it – no need to click again,” and so on. Most of these features, in fact, are so obvious and ingrained we barely notice them. Which is exactly the point: well-designed computer interaction elements are natural, easy, obvious. It’s hard to overstate just how much this is not the default state of computers. It’s hard to overstate how much hard and counterintuitive thinking went into making this process so easy and natural.

As a former teach, self-educator, multiple-graduate-degree-holding adult learner, I have run the gamut of positions in the instructor-pupil continuum, and I think it’s high-time we took a leaf from the computer people and started to put more effort into making learning resources as natural and intuitive as computers. As suggested in the previous paragraph, this is both a cognitive and an affective project. Sometimes textbooks (lectures, videos, whatever) are downright bad: they provide unclear explanations, they have technical errors or reference outdated resources, or they make unwarranted assumptions about the learner. More frequently, their primary flaw is not that they are erroneous, it is that they are unapproachable.

I use the word torpor in the following way: “That feeling you get when just looking at a learning resource makes you feel so overwhelmed, so filled with dread at the boredom and frustration to come, so bamboozled by the volume of what you need to know—and don’t – to even begin that you just want to give up immediately and go to sleep.” Even when you know, somewhere in your mind, that the content is learnable, that you have peers that have pulled it off and aren’t as bright as you, that millions of people learn it every year, but you feel you just can’t do it – that feeling. Like with computers above, it is not sufficient that the content of our learning materials be functional. We also have to make them such that they communicate clearly the message: “You can do this. It’s not going to be that bad. We’ll take it a step-at-at-a-time, we’ll have breaks along the way, and I promise it will be at least a little bit fun! It’s not going to be easy, but you can imagine yourself pulling it off.”

I genuinely do not believe that STEM is all that conceptually hard, and I don’t believe that the reason people avoid it is because it is beyond their intellectual capacity or overly distant from their interests. I believe it’s an emotional thing. Think of Adderall abuse in colleges, for example. Adderall doesn’t make you any smarter – we know that, and we’ve proven it. Kids abuse Adderall because it makes learning complex material less boring, less intimidating, and less tedious. So what does it say about the we teach the wondrous worlds of biology and chemistry, the weird and staggering implications of physics and astronomy, or the beautiful and satisfying logic of math, or the unexplored frontiers of computing that students have to literally drug themselves to make it tolerable?

Well, pick up a textbook and you’ll see. First, you’ll see a small building of a book, a resource that very literally weighs you down. Leaf through it a bit and you’ll see dense walls of black-and-white text, crappy graphs and spaghetti-code mazes of flow-charts and diagrams, a taxonomy of Greek and Latin neologisms cataloguing minutiae you’ll never use after the midterm, and page-long equations with subscripts and powers and “nth”-this and “Sigma-that” and radicals-of-radicals, all conveniently annotated with endnote ”ii.iiii.iiiii” which (if you find it) offers its clarifying insights in the form of – as if in some carnival-house circular-logic hell—a reference to a different inscrutable paper published in the Journal of Things Three People On Earth Care About.

My assumption is that the rationale for this unhappy trend continuing is some combination of 1) inertia, 2) the Curse of Knowledge, 3) the egotism of the authors, eager to preen and prove just how profound they are, and 4) an assumption that the passion which drives a person to a lifetime of increasing depth of knowledge about x is shared by everyone who cares to learn about it at all. In HCI, the principal dispute is between the programmers (who see the value of every. single. line of code and every. single. feature of the program) and the UI/UX team who understand that normal folks happily forgo a certain level of customizability and functionality to attain an easier and more accessible interface. I suspect some similar motivations underlie the instructional resource industry, though without a robust human-interaction component, and likely without a comparable market incentive—after all, the textbooks are required.

Whatever it is, the end-product is the literary abomination straining the backs of every high-school and college student in the country. Whatever it is, the current ogre of a resource is at odds with everything we have learned in the progress of psychology, cognitive science, and behavioral economics. Inspired by gems like Nudge by Richard Thaler and Cass Sunstein, Predictably Irrational by Dan Ariely, Don’t Make Me Think by Steve Krug, Brain Rules by John Medina, Made to Stick by Chip and Dan Heath, and the inexhaustible geniuses behind 3Blue1Brown and Better Explained, I’d like to offer here some introductory principles of Human-Textbook Interaction as well as some resources that I’ve found to meet these. I have also created, here, a forum in which you, dear reader, can make reference to any resources you’ve discovered that are likewise consistent with these guidelines.

The Principles of Human-Textbook Interaction

1) Remember that if I don’t feel like learning it, I won’t.

2) Offer only as much detail as is relevant to your audience’s needs.

3) Better yet, let your audience choose the level of depth they prefer.

a. See, for example, NewsELA , where you can select a variety of reading difficulty levels for a given story. All students leave knowing the same story, but no one level is assumed to be suitable for all readers.

b. Consider, as another example, the abstracts in academic journal.

4) Never use a word or symbol that you’ve not seen in Good Housekeeping without a clear and adjacent explanation of what it means.

5) Use large font. Use double-spacing. Leave empty margins for annotations, definitions, and reader notes.

6) Pictures > Diagrams; Diagrams > Text; Textual Analogies > Textual Descriptions; Plain-Language Text > Technical Text; Annotated Technical Text > Unannotated Technical Text.

7) If it looks easy, manageable, and fun, I’ll probably do it. If it looks overwhelming, dull, and difficult, I’ll probably avoid it.

8) Don’t trust your own judgment about how it looks – ask a bright 9th-grader.

9) From Frank Lutz: “Never use a word that makes one reach for a dictionary – cause they probably won’t.”

10) Likewise, never ask me to make a large, discrete commitment of time – cause I probably won’t.

11) Break big concepts into small concepts; break small concepts into numbered lists or discrete, ordered statements.

12) Break big tasks into small tasks. Break small tasks into simple, clear steps.

13) Never use black-and-white visuals unless you’re writing a textbook on films made before 1970.

14) Any technical procedure, code, or illustration of process should appear side-by-side with a plain-language breakdown of what is going on.

a. See “Grokking Algorithms” and the Python code used in formatting.

15) Accept that most people aren’t as interested in this as much as you are.

16) From Steve Krug: “Eliminate half of the words – then eliminate half of those.”

17) Beware the Curse of Knowledge.

a. Don’t assume something is obvious to me because it’s obvious to you.

b. Make implicit steps explicit.

18) Remember that, for me, starting is the hardest part. Sell me on beginning, give me some chances to succeed, and proceed gradually, then I’ll build up the confidence to persist when the time comes.

19) Manage expectations: don’t sugarcoat the challenge, but don’t push me in the deep end and tell me to swim.

20) Assume I’m lazy and bored – cause I probably am.

21) Never, ever make me ask: “Where do I begin?”

22) Never, ever make me ask: “What do I do now?”

23) Never, ever make me ask: “Am I done?”

24) Anything that I will likely need to reference frequently should be printed on a separate page, along with all the other things I’ll likely need to reference.

25) Even really dumb mnemonics // are as memorable as the Pentatonix!

26) Layout instructions into single, actionable, discrete steps.

27) BUT: constrain my choices

a. Wherever possible, give me a step-by-step, a checklist, a template, an outline, a format guide, a deadline, a schedule, a daily task, a study guide, a diagram, a flowchart, a goal, a diagram, a…

28) If you don’t know –yourself—how to compose a human-friendly textbook, see some of the ones shared here. Use these as a template.

29) Exploit my cognitive tendencies – the marketing teams trying to get me to not study do!

a. See Nudge or Made to Stick or You Are Not So Smart for some ideas.

b. Assume I have the attention span of a teenager – cause – hey, is that a squirrel?!

c. Remember you’re competing with video games, friends, shopping, chores, romantic aspirations, <insert a million other things> that I could be doing instead of reading your book.

d. Think like a marketing strategist. Earn my time and attention.

30) A good analogy is as helpful to a learner as a Mr. Carson is to Lord Grantham.

a. See: intuition pumps, reference frames, and mental schemas.

b. Give an analogy first, then provide the qualifications that increase specificity.

31) Provide, whenever possible, immediate, customized feedback.

a. Think: Correct = A; if you got B, you probably did x; C, you probably did y.

b. Leave a “I really don’t know” option, then suggest further resources.

Don’t expect me to take care of myself! Build in the best learning practices of interleaving, spaced repetition, mnemonics and hooks, self-testing, and a study plan.