Learning seen from the writer's side: how to organise the text, what to draw, how to pair an article with video, and how to lay the two out. Each post reviews the evidence and its limits, with this site's course guides as the case.
Three practices have meta-analytic support: give readers a fully worked example, ask them to explain for themselves, and state a common misconception before refuting it. Questions before reading mainly help the content they ask about, and most experiments used math and science materials, short texts, and college students.
Adding a graphic raises reading comprehension by about 0.39 standard deviations on average. Placing each diagram next to the text that explains it, and having readers do something with a diagram rather than just look at it, each have research behind them and cost less than drawing one more diagram, though no experiment compares them directly with adding a diagram; only one experiment isolated prediction, and it found no detectable difference. Use a state table for step-by-step execution, a numbered list for a single-path flow, and a table for comparisons. On a phone, a mermaid diagram with more than 3 nodes side by side in one rank shrinks until the text is unreadable.
In a quasi-experiment in one intro course, sections whose worked examples labeled what each step was for did better on quizzes right after learning, with no significant difference on later exams. Live coding, and Parsons problems in place of writing code, showed no measured difference in learning. Public GitHub notebooks rerun in their saved order finished without error about a quarter of the time; no study has measured how code that does not run affects what readers learn.
Jargon makes general readers rate a text as harder to read, and definitions that appear only on mouseover did not bring that rating back up. In studies of foreign-language reading tested right after reading, readers with glosses learned about 45% of the unknown words, versus about 27% without. Papers with more equations get cited less, and people have computed this correlation for both biology and physics, but the two sides never agreed on whether it holds up, and no study has measured whether readers understand less.
Put a video at the top if it covers the whole article, at the start of a section if it covers only that section; videos at the bottom often get skipped. Readers mostly rewatch specific segments, so every section should link to its timestamp and the intro should state the video's length. Prequestions and writing your own explanation after each segment have experimental support, but those experiments all used short material, a little over 20 minutes at most.
Research interfaces share one move: keep the video and the matching text visible together, either beside the text or right at the passage being read. In the 16-person Papeos study, the condition with clips attached to passages had the lowest mean mental demand (the omnibus test across three conditions was significant). No experiment has compared layouts for a long written guide paired with a lecture recording, and no research I found says what to do on phones.
No study compares the same content as an interactive article and as a static one. When interaction was added to the same chart, none of the variants in one set of experiments beat the static version. What helped was readers doing something with the figure, and the gap disappeared once the comparison group also did something. Readers use the component that responds at a touch and sits in the middle of the narrative; about half of desktop readers never opened content placed behind a click. One long-time maker of interactive tutorials says each takes one to five months, including the time to learn the algorithm.
College-classroom meta-analyses find about half a standard deviation, but they compare whole-course teaching formats, the active sections usually include group discussion and instructor responses, and most controls were not done or not reported. In online courseware, "students who do more practice score higher on quizzes" recurs across a dozen-plus courses, but all of it is observational. None of the studies read here compared one person reading an article with and without practice.
Asked content gains the most, according to research on classroom quizzes and prequestions (I found no synthesis of inserted questions themselves with a legally available full text), and feedback works better the more information it carries, though that evidence comes from classrooms, computer-based materials, and short laboratory texts. Readability formulas explain only a quarter to a third of teachers' difficulty judgments, and 30 Bloom verb lists disagree on where the same verb belongs.
Large-sample records of "did anyone answer when the question appeared" come only from MOOCs: for a question shown in the player when the video reaches its position, about 74% of people who started that video answered; for pop-up review questions, about 70% of multiple-choice and about 40% of type-a-number questions were attempted. Under random assignment, about half as many people did a task that required typing as did one that only required ticking a box. None of the studies I read measured readers of public articles, and this site has no data either.
In classroom studies, having students solve problems before instruction raises conceptual knowledge and transfer by about a third of a standard deviation on average, but every one of those studies had a teacher in the room; versions with group work had larger effects, except in interventions lasting only a few hours. A set of experiments that had roughly ten-year-olds solve first found the opposite. Unassisted discovery loses to explicit instruction, and discovery with scaffolding or feedback does better; no difference was detected between fading and not fading scaffolds. No study has tested one person reading an article and doing a project alone.
People who know more beforehand still know more afterward (correlation .53), but the average correlation with how much they learn this time is close to zero, and individual studies range from strongly negative to strongly positive. High-assistance materials help learners with low prior knowledge (d = 0.51) and hurt those with high prior knowledge (d = −0.43); high and low are relative splits within each study. Stating prerequisites at the top is industry practice; whether readers can use it to decide if a post is for them has not been tested.
In one refutation-text meta-analysis, effects showed no measured difference whether or not studies first screened out readers who already answered correctly. A misinformation review lists 11 studies of the familiarity backfire effect; 3 reported that repeating a myth made people believe it more, all three on vaccines and all with single-item measures. No study has directly tested what happens when the reader never heard the misconception before. What you can act on now: keep the false claim and the correct claim together, give the correct claim with a reason, and do not let the false claim stand alone as a heading.
Telling readers what something is good for makes them rate the material as more useful, but across seven experiments no difference was detected in immediate test scores; in classroom studies where students wrote about usefulness themselves, results flipped across students and courses. Interesting details unrelated to the main point lowered immediate test scores on average, by an uncertain amount; only one pair of experiments detected no harm when learning was voluntary.
With no intervention, readers' ability to tell which text they understood and which they did not averages a correlation of only 0.18, which the authors convert to about 55% accuracy. Writing a summary or keywords after reading everything, or answering practice questions before judging, makes judgments somewhat more accurate; just reading ready-made questions and answers showed no detectable benefit. Most of the evidence comes from college students reading expository texts in the lab.
Spreading practice across days shows an effect of about d = 0.54 in a meta-analysis of real classroom studies, which its authors consider smaller than a meta-analysis that mixed in lab studies. Spacing embedded in mathematics courses (which also involves interleaving) is g = 0.24, and when eight university STEM courses used the same procedure, the gain averaged only 1.5 percentage points, with no detectable difference. Rereading a week later showed no detectable advantage a week after that, and none of the studies in that classroom meta-analysis let learners decide for themselves whether to come back and review.
The most complete attempt, Quantum Country, embedded 112 questions in an essay that takes about four hours to read and then emailed readers to schedule reviews. Its authors rate the evidence that readers would remember much less without review as only emerging, and say there is no evidence it generalizes to other domains. When a MOOC pushed review questions to learners, about 80% of those assigned never touched them, and grades showed no detectable difference; the example that worked was a classroom experiment where review was scheduled into class time.
In a randomized experiment in one AI course, an order built from rated transition difficulty beat a historical order by about 5 percentage points. Among 8 studies that sequenced interdependent content with algorithms, none significantly beat a fixed human-designed order. Practicing four problem types mixed across eight worksheets gave 61% versus 38% on a test about a month after review, a combined effect of interleaving and spacing. Spiral curricula have almost no efficacy research. MOOC learners who earned certificates still skipped 22% of the content on average.
In HarvardX and MITx courses, about half of registrants on average never entered the course; among those who did enter, only 3.13% passed in 2017–18. A prompt to write a study plan raised completion from 13.8% to 17.7% in three courses, but at 247 courses no difference in completion was detected. These are all MOOC numbers; this site has no data on reader behavior.