About Learning Analytics

 

What is learning analytics?

The Society for Learning Analytics Research defines learning analytics as “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.”

What is the purpose of learning analytics?

The purpose of applying learning analytics is to enhance or improve student success. Learning analytics provides important information to faculty on a range of factors related to student performance and success involving Canvas, Kaltura, LinkedIn Learning, and other learning technologies and systems. 

This information supports the critical work of faculty in areas including student engagement, academic performance, and learning outcomes, among others. 

Beyond teaching and learning, this information can also support the assessment and accreditation efforts of academic units.

Testimonial

“The Student Zero Activity Report flags students who have not logged into Canvas at all or have not done so for a long time. This tool provides us with valuable information and allows us to identify those students who may be at academic or engagement risk. We can then reach out to those students and take appropriate measures.”

Michelle Crilly
Director, Center for Student Success
School of Business

How does learning analytics improve student learning?

The use of learning analytics can  

  • increase student retention 

  • inform stakeholders’ judgments  

  • offer more personalized learning

  • detect students’ at-risk and undesirable behaviors 

  • support course design and development  

  • provide timely feedback and intervention  

  • increase students’ engagement 

  • improve learning outcomes  

  • assist in understanding students’ progress and performance 

To share your specific learning analytics needs with the IT Learning Technology Team, please complete our Learning Analytics Survey. We estimate completing the survey will take no more than 10 minutes.

 

To learn more about Learning Analytics, please check out the video tutorials below:

Course-Based Tool

Accessed via Canvas

Appropriate for

Video Tutorial

New Analytics

Track student data using an interactive chart or table.

For more information about New Analytics, click here.

  • Instructors
  • TAs

Click here

Student Context Cards

Click a student’s name anywhere in Canvas to view a summary of the student’s progress in the course.

  • Instructors
  • TAs

Click here

Individual Student Access Report

View a summary of student participation in a course.

  • Instructors
  • TAs

Click here

Quiz Statistics

View statistics such as quiz average score, high score, low score, standard deviation, and average time of quiz completion.

  • Instructors
  • TAs

Click here

 

Reports Delivered via Email

Appropriate for

Video Tutorial

Course Storage Report

View storage space used by each course in a selected term

To request this report for your school, department, or program, click here.

  • Program Directors
  • Department Heads
  • Student Success Coordinators
  • Advisors

Click here

Students with No Submissions Report

View all students enrolled in a course who have not submitted an assignment in Canvas

To request this report for your school, department, or program, click here.

  • Program Directors
  • Department Heads
  • Student Success Coordinators
  • Advisors

Click here

Enrollment Report

View users' enrollment status (teacher, student, TA) in a given course

To request this report for your school, department, or program, click here.

  • Program Directors
  • Department Heads
  • Student Success Coordinators
  • Advisors
COMING SOON

Student Zero Activity Report

View students who have not visited a course in Canvas since enrollment

To request this report for your school, department, or program, click here.

  • Program Directors
  • Department Heads
  • Student Success Coordinators
  • Advisors

Click here

Student Access Report

View all the activity from students enrolled in a given course or all courses in a given term

To request this report, click here.

  • Instructors

COMING SOON

Unpublished Courses Report

View the courses for a given term that are not published

To request this report for your school, department, or program, click here.

  • Program Directors
  • Department Heads
  • Student Success Coordinators
  • Advisors

Click here

Questions or issues? Contact the Office of Learning Technology using the Service Desk.

References

Alhadad, S., Arnold, K., Baron, J., & Whitmer J. (2015). The Predictive Learning Analytics Revolution: Leveraging Learning Data for Student Success. EDUCAUSE Center for Analysis and Research (ECAR), Retrieved from https://library.educause.edu/-/media/files/library/2015/10/ewg1510-pdf.pdf

Becker, B. (2013). Learning analytics: insights into the natural learning behavior of our students. Behavioral & Social Sciences Librarian, 32 (1), 63-67

Daniel, B. (2015). Big Data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(1), 904-920.

Daniel, B. K. (Ed.). (2016) Big data and learning analytics in higher education: Current theory and practice. Springer.

Dziuban, C., Moskal, P., Cavanaugh, T., & Watts, A. (2012). Analytics that inform the university: Using data you already have. Journal of Asynchronous Learning Networks, 16(3), 21-38.

Lawson, C., Beer, C., Rossi, D., Moore, T., & Fleming, J. (2016). Identification of ‘at risk” students using learning analytics: the ethical dilemmas of intervention strategies in a higher education institution. Educational Technology Research and Development, 64(5), 957-968.

Myint, S., Khine (2018). Learning Analytics for Student Success: Future of Education in Digital Era

Picciano, A. G. (2012). The evolution of big data and learning analytics in American higher education. Journal of Asynchronous Learning Networks, 16(3), 9-20.

Toetenel, L., & Rienties, B. (2016). Analyzing 157 learning designing using learning analytics approaches as a means to evaluate the impact of pedagogical decision making. British Journal of Educational Technology, 74(5), 981-992.

Verbert, K., Manouselis, N., Drachsler, H., & Duval, E. (2012). Dataset-driven research to support learning and knowledge analytics. Educational Technology & Society, 15(3), 133-148.

Details

Article ID: 83111
Created
Mon 7/15/19 4:50 PM
Modified
Wed 2/19/20 11:59 AM