I’m attending the IFWE 2016 conference in San Antonio, TX and live blogging sessions. One more session till lunch! Be sure to follow the #ifwe2016 hashtag on Twitter if you want to learn about what else is going on here!

Presented by: Mindy Menn (Texas Woman’s University)

Description: What do novices need to know about learning analytics? How can learning analytics be leveraged to improve online programs and students’ experiences in online programs? Find out during this session addressing the basics of learning analytics.

Learning Analytics Introductions

Interesting bits from the introductions. Someone wants to understand better the difference between learning analytics and analytics. One institution is starting a learning analytics committee. One instructional design specialist does analytics as well as instructional design. Someone from Penn State is working on a custom dashboard of learning analytics. Another person is looking at how to give faculty learning analytic data to empower them.

Mindy had a really cool colored folding paper strategy. 5 sheets of colored paper, spread them apart and then fold so you have 9-10 layered and colorful places to write. This page has an example – scroll down.

Learning Analytics Definition and Limitations

• It’s measurement, collection, analysis, report of data
• It’s about the LEARNERS
• We want the learners to benefit
• “spot hidden trends and predict outcomes”
• “organize, store and mine data to improve teaching and learning for all students” – it’s not just the at-risk students – it’s for everyone – including the bored students
• It is a research domain and a field
• It overlaps with other fields – computer science, machine learning, statistics (lots of different regressions to predict relationships), big data, etc.
• It cannot make taking action easier
• It won’t be a magic solution
• It can never perfectly predict anything – remember your stats class!

Learning Analytics Questions

Some examples of things that we can look at with learning analytics…

• What registrar/institutional data provides insights to students’ progress?
• How does student’s video watching correlate with their course success?
• How does the time submitted compare with course performance?
• How does success in a specific course correlate with degree success?
• What are online learning behaviors and what do they tell us? When do they login? When do they logout? What do students click on?
• Who talks to who and how many responses in discussion forums?
• What signals do we have in courses where we might need to update something in the course? or to send students to a service to assist them with their study skills…

People who are interested in it….

• Learners – they are concerned about how we analyze their data, but also the data can be used to help give advice to them or to help them improve their practice
• Instructors
• Administrators – academic analytics are a little different – learning analytics is purely on the learner; academic is more about the whole university
• Researchers

Resources

• Society of Learning Analytics and Research (SoLAR)
  • International Conference on Learning Analytics and Knowledge – they have recorded presentations too
  • The Journal of Learning Analytics
• Educause Library – items tagged learning analytics
• US Dept of Education: Learning Analytics Issue Brief
• Charles Stuart University Privacy and Ethics Code of Practice in Learning Analytics
• Student Learning and Analytics at Michigan (SLAM)

What Next?

It’s important to know what your question is – which depends on your role… the stats people who can help you are going to want to know your question. So you need a narrow question. Not just to track and know everything!

Takeaways

I guess I really am doing learning analytics with my recent publications:

• Lim, J.. (2016). The relationship between successful completion and sequential movement in self-paced distance courses. International Review of Research in Open and Distributed Learning, 17(1). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/2167
• Lim, J. M. (2016). Predicting successful completion using student delay indicators in undergraduate self-paced online courses. Distance Education, 37(3), 317-332. doi:10.1080/01587919.2016.1233050

This is a huge area of interest to me. What data do we have? How can we collect it? How can we track it over time? How can we use it to monitor and improve the success of our online courses and programs? And how do we do it well and ethically?