Name
Abstract | ||
|---|---|---|
For textbooks on technical topics, the typical amount of text used is more than what many college students will read. Some teachers observe, and students report, that students commonly skim such text. As such, a writing style that aggressively minimizes text while still teaching the core technical topic may improve student learning; if text is short enough, students may then read and study the text more carefully. The objective of this study was to compare the effect of text quantity on amount learned. We created and compared content styles using a lesson that taught Google search techniques. The two main content styles were normal text and minimal text. The normal text style included 6-12 sentences followed by 1-3 examples. The minimal text style included 1-2 sentences followed by 1-3 examples. We conducted a randomized control study with 168 participants enrolled in a college-level Introduction to Computing course for non-computing majors. Each participant was randomly assigned one lesson style. We provided a prelesson and post-lesson quiz, each with ten questions. Additionally, the participants completed background and follow-up surveys. The study was part of a course homework assignment, so self-selection bias was limited. The course is primarily taken by non-majors and covers the basics of Word, Excel, and HTML. An improvement score is a participant's post-lesson minus pre-lesson quiz scores. The average improvement score for minimal text was 2.4 (6.5 - 4.1), which is higher (p-value < 0.01) than the average improvement score for normal text of 1.1 (5.1 4.0). Thus, teaching the same topic using less text led to more learning. The conclusion is not that materials should be watered down, but rather that great attention should be paid to using minimal text while teaching the same core topics. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/FIE.2015.7344322 | FIE |
Keywords | Field | DocType |
digital learning,digital education,digital content,lesson assessment,text length,minimal text,college education,college textbooks,STEM | Digital learning,Digital education,Computer science,Usability,Writing style,Knowledge management,Atmospheric measurements,Mathematics education,Pedagogy,Digital content,Student learning | Conference |
ISSN | Citations | PageRank |
0190-5848 | 3 | 0.82 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alex Edgcomb | 1 | 37 | 6.13 |
| Frank Vahid | 2 | 2688 | 218.00 |
| Roman Lysecky | 3 | 605 | 60.43 |