Learning Analytics
Webtexts prompt students to respond to content at least once for every five minutes they spend inside our learning environment, which provides the highest resolution of learning analytics currently available anywhere. Starting with our rigorous essential learning outcomes, we author auto-graded questions for every assignment, enabling the creation of a map of exactly what each of your students, and your class as a whole, are learning.
What you can know:
About your class
- Are students doing the homework?
- How many students completed last night’s homework? (without grading)
- Which students most need a reminder that this is assigned?
- Which students are most likely cheating or not taking the assignments seriously?
- Which students are scoring well, but struggling to do so?
About a student
- How much of the coursework has this student completed?
- How long has this student spent clicking, typing, and scrolling in this webtext?
- What are this student’s study patterns?
- What kinds of questions is this student missing?
About this webtext
- Which assignments or questions are students skipping?
- Which questions are students missing?
- How long does it take most students to complete this assignment, chapter, or course?
What we measure:
- Every time a student signs in
- Every time a student views a page
- How long they spend clicking, typing, and scrolling in each assignment
- How many questions they attempt
- How many auto-graded questions they answer correctly
- How many times they reset and submit answers
What we can know:
- Which assignments are most often used
- Which questions seem to confuse students
- Which concepts are proving difficult for many students to master
The ability of a publisher to know how effectively their content works is nothing short of revolutionary. For the first time in the history of publishing resources for learning, the publisher, instructional designers, and authors can know where the content is succeeding wildly, and where it needs to be strengthened. By reviewing the (anonymous) results of tens of thousands of students interacting, we can, for the first time ever, know what works and what doesn’t. We release a new edition of each webtext twice a year. And we have the data to prove that each edition is, in fact, stronger than the one before.



