Learning Analytics: Logic and Structure

1. What do you want to do/understand better/solve?

I most want to develop an automated solution for collecting and analyzing pertinent data from online continuing education courses and other blended learning resources. The outcome of the analysis should not only document what learning has occured, but also be adaptive and recommend further learning resources. The data should be easily understood by both learners and training coordinators.

2. Defining the context: what is it that you want to solve or do?

a. Who are the people that are involved?

The people involved will be myself as the primary developer. Additional advice will involve the participants in the #LAK13 MOOC.

b.What are social implications?

The social implication is Arkansas will gain a pilot learning analytics system that should be repeatable by other public and non-profit agencies. These pilot learning analytics systems will benefit the regional society by improving acquisition and implementation of economic development and small business knowledge

c. Cultural?



3. Brainstorm ideas/challenges around your problem/opportunity.

a. How could you solve it?

b. What are the most important variables?



4. Explore potential data sources.

a. Will you have problems accessing the data?

b. What is the shape of the data (reasonably clean? or a mess of log files that span different systems and will require time and effort to clean/integrate?)

c. Will the data be sufficient in scope to address the problem/opportunity that you are investigating?



5. Consider the aspects of the problem/opportunity that are beyond the scope of analytics.

How will your analytics model respond to these analytics blind spots?