Title: CS 525 Special Topics: Online Learning Infrastructure

Location: Goddard Hall  012

Course Catalog Description: This course acquaints participants with the fundamental concepts and state-of-the-art computer science research in online instructional systems. Advanced interactive instructional systems serve as tutors, as learning companions or both. This course introduces their design, the technology that powers them, the learning theories that motivate them and results from experimental evaluations. We will cover both the learning theory, and how to design and build systems consist with existing theories. The course consists of weekly presentations on current advanced literature, discussions and a term project. 
Prerequisite: Proficiency in a high level programming language

Time:  The registrar thinks the class is Tue and Thursday 4:5:20 but I am changing it to be 
Tuesday 4:30-5:50
Thursday will still start at 4-5:20  

Reinforcement learning applied to learning what works in online ed.
    -See this paper 
Creating Educational Interventions:  
    -Google Doc AdOns  (see one Neil did with his student last year)
    -Google Apps for Business
    -Using ASSISTments API to make a innovative product
Automating the analysis of experiments: Optimal Experimental Design

See the following link for assignment information

Test on readings = 20% (must pass this test to pass the class)
Discussion of Reading and your effort you show in answering the quizzes in assistments before class =20% 
Project = 60%

Cheating Policy
You can talk about programming assignments together, but not share code.  This should be crystal clear.  If in doubt, ask me.

Your final grade will reflect your own work and achievements during the course. Any type of cheating will be penalized with an F grade for the course and will be reported to the WPI Judicial Board in accordance with the Academic Honesty Policy.

-Make a cool product
-Get a peer reviewed publication out the door.
-affect detection

Important Dates
Two venues approaching for potential publications... (we will add to this list)
Learning at Scale (L@S)
    Paper Deadline = October 18th

Learning Analytics and Knowledge Conference (LAK)
    Paper Deadline = October 31st

Hangout Link

This page is here at http://tiny.cc/fallcs525 or