March 09, 2020: FLOE infrastructure Continuation
Present: Cindy, Justin, Jutta, Michelle, Ned, Philip, Ted,
Agenda
Jutta continues the talk she didn’t finish in the last meeting
Discussion of a draft diagram of the high level implementation structure
Notes:
Requirement challenges:
Learners can control 3 parts to influence the matching:
Learning goals
Configure the preprocessor generated summary of learning needs/preferences
Feedback on matching results
Are these enough for the matching engine to be non-black box?
Large data sets to train algorithms
What other exploration tools can learners use to discover their learning needs?
Where to search OER material? Wild web?
Technical Challenges:
Preprocessor algorithm
Matching algorithm
How to identify each learner across all exploration tools and platforms
3 main direction of WeCount:
Address data gaps through co-design, challenge workshops that data related problems are not addressed
Identify accessibility issues of existing data science tools. Address these through co-design.
Explore the possibilities of moving against the bias, especially deep learning / big data based systems.
Floe infrastructure is the Floe match within WeCount
Issues with the diagram:
Instead of letting learners config a set of preferences, machine learning should be applied to understand how learners learn better
Instead of watching learners to discover their preferences, learners should be given a tool to track and record their preferences
The actual understanding of how learners learn better, such as kids learning math thru dinosaurs
Next meeting: Tomorrow 1-2PM