1. Fostering Student Success: Leveraging Canvas Analytics for face-to-face, hybrid, and online courses
Welcome
February 16, 2018

2. Pat Fellows Instructional Designer & Technologist pfellows@uoregon
Pat Fellows Instructional Designer & Technologist Dave Furjanic Graduate Employee
Introductions

3. Introduce yourself...
Name, department, expectations

4. Learning Outcomes:
Understand the role of Learning Analytics in student success & retention
Learn how to access Canvas Analytics
Understand what the Data is saying
Learn how to use data to support students
Apply concepts to a Winter Term course

5. What are Learning Analytics?
Learning Analytics: the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.1
1. Ferguson, Rebecca (2012). Learning analytics: drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6) pp. 304–317.
International Journal of Technology Enhanced Learning

6. Types of Analytics Learning analytics – academia Predictive analytics
What aspects of the course did students master?
What topics are students struggling with that may require further discussion, attention or presentation?
Predictive analytics
How often do students view pages in a course?
How close to the due date do students submit their assignments?
Academic analytics
Action analytics
Predictive analytics:
How often do students view pages in a course?
How close to the due date do students submit their assignments?
Academic analytics:
What are the characteristics of at-risk students?
Does recruiting tactics match institutional aid?
Action analytics:
Which recruiting practices improves retention and completion rates?
What is the use of mobile devices on Campus and their demand on WiFi infrastructure?

7. What the Research is Saying
Data models may be able to predict student final grade as early as week 3 (of 10)
Increased time spent online does not accurately predict achievement
Discussion posts, messages sent, and assessments completed may be more accurate
Implication: quality over quantity?
Procrastination associated with lower achievement
This effect is stronger in e-learning than traditional courses
Implication: we should explore proactive strategies – for example, break tasks into chunks
How often a student looks at their grades may be the strongest predictor of achievement
Students who never access grades are more likely to fail

8. Canvas Learning Analytics
Course Analytics
Predict how students react to course activities
See which students are at-risk and need help
View how effective your teaching strategies are in allowing students to learn
See a quick view of what your students are achieving in your course
*Currently does not measure activity on mobile devices
Learner analytics
How well a particular student is doing in your course
AND what can we learn about the design of our course in Canvas. Keep this in mind for later

9. What to look at/for? Patterns Color Red No data points Whole class
From student to student
Color Red
Missing
Poor
No data points
Activity by date
Communication
At end of slide – let’s take a look at Canvas Course Analytics and data
Go to a Winter term course and click on the Course Analytics button on the right top of page

10. Canvas Course Analytics
Zoom, laser, pen
Use flowchart for navigation
Use word doc for definitions

11. Student Interactions Report: (aka: Teacher Activity Report)
People>Settings>SI Report on menu
Note, last interaction date, scores, and assignments
Flip order

12. Course Analytics Next: Student analytics
Go to Course Analytics and scroll down
Sortable
Numeric presentation

13. Student Analytics
Activity by Date includes – joining a web conference, posting a new comment in discussions or an announcement, submit a quiz or start a quiz, submit an assignment, create a wiki page.
Communication – All conversations, individual or group/class.
Submissions – green line, submitted early, yellow line, submitted late, red box, missing.

14. Student Access Report
Course Navigation Menu clicked – Course Home, Course Grades, Course Syllabus, Course Modules, Course People
Course participation – Course Assignments, Course Discussions, Course Quizzes, Course Conferences, Course Pages, Course Files

15. Page Views and ParticipationB
Difference between Page Views and Participation
A, B, C students – Patterns? C

16. Submissions A B C
A student, B student, C student – what do you see?

17. Grades A B
Same idea Patterns? C

18. Let’s try it! https://giphy.com/stickers/forever-young-7N9Y5qu2X0KXe
Think about showing what you find to the group. We can keep student identity
Go into your Winter course and identify, using the student and class information, student that might be at risk, and if you see anything that stands out with respect to specific content and course activities and design of the course.

19. Working with Students Conversations Announcements Discussions – Posts
Grades
Message students who…Assignment feedback
Written
Audio
Video
Attendance
Calendar
How to work with students at risk, or doing great work

20. Quiz Statistics Quiz Summary Question Breakdown
Export Student Analysis
Export Item analysis
Not a lot of time, but let’s talk briefly about quizzes, as there are statistics there.

21. True/False and Multiple Choice quiz questions include an item discrimination index, which attempts to look at a spread of scores and reflect differences in student achievement. This metric provides a measure of how well a single question can tell the difference (or discriminate) between students who do well on an exam and those who do not.
+.25 or higher is good

22. Course Statistics Statistics for course site Totals Assignments
Students – last Log-in time
File storage
FYI

23. Questions?

24. library.uoregon.edu/cmet
Thank you!
Educational Technology Support Center for Media & Educational Technologies (CMET)
19, Knight Library
library.uoregon.edu/cmet