These are a sampling of some of the considerations, perspectives, issues, and opportunities for integrating digital approaches to learning. The list of topics here is not exhaustive. Each of the areas can be amplified into longer, more formal workshops. -ray
Learner-Centered as a Primary Contextual Value
A key value in successful online and blended programs is learner-centered, that is, moving the focus from the teaching to the learning. It is not as easy as it might seem, but it pays huge benefits in learning outcomes and student satisfaction.
Thinking about the Future of Work to Make Better Decisions about Learning Today
Some Good Practices in a Learner-Centered Course
7 Things You Should Know about Universal Design
Digital Learning is Guided by Instructional Designers
Committed to Accessibility and Universal Design
New Continuum of Learning Approaches
Visualization of the continuum - pedagogy->andragogy->heutagogy
Primers on three "gogies"
Community of Inquiry Model
Community of Inquiry - social constructivist model of online learning
Community of Inquiry Framework - first ten years
Online Student Engagement: Tools and Strategies / Time and Balance
Identifying and Assessing Learning Outcomes
If we are going to get all of this done, doesn't it take a lot more time?
How does one balance all of these tasks?
Increasingly we are writing our syllabi with learning outcomes; mapping those to program outcomes. Here are are some tips from Rochester Institute of Technology outcomes implementation in online courses:
This is a great step-by-step example of how one can implement outcomes in an online class - and assess those outcomes, tracking in a simple excel sheet (Canvas is likely to have more sophisticated tools, but this explains the nuts and bolts):
Research shows that injecting "difficulties" early in the semester may result in better learning outcomes:
The power of data is now leveraged by higher education
At the class level, the program level, the campus level
Class Level Analytics
Dashboards - faculty and student
Monitoring student progress, Purdue Course Signals gives
students access to live class data in the aggregate
Program Level Analytics
A couple of quick examples:
- "heat map" - which courses are working; which are not
- most importantly, how do students do in gateway courses (courses required to advance to higher levels)
- where are the hang-ups (D,F,Withdraw)?
- where are the successes?
select department from global listings of all courses and prefixes
Program "heat map" - green is lower "dew (D, F, Withdraw) rates - to red (highest rates of unsuccessful completion of the class)
Select a course and look at the "dew" rates by semester:
PAR Project Codebook including Student Success Matrix Variables
Critically important in building data analytics is the creation of a well defined codebook of variables that are to be collected. It is from this collection that reliable data is collected and reports, predictions and prescriptions can be made.
University Level Analytics
A couple of quick examples:
- If a student at UIS enrolls for more than 2 online summer classes, the likelihood that student will complete in fewer than four years is doubled
- If an on-campus student takes one online class, on average, that student takes 2 more credit hours (in two out of three cases, the online class seems to be added to the normal course load)
- Poison pair classes - multiple instances of poison pair classes have been identified. Poison pair classes are ones that if they are taken the same semester results in lower grades on average and higher dropouts.
- In depth data on gateway classes
Some Current Trends that May Shape the Future
Augmented Reality - Virtual Reality
AR in higher ed
VR in higher ed
Holoportation by Microsoft
Leap Motion - available now - 3D interactive on laptop/desktop
Artificial Intelligence in Education