Software assitance for teaching statistics

Further progress in propagating expertise without tying up existing expertise (i.e. increasing the supply while decreasing the demand): 

Report: Robots stack up to human professors in teaching Intro Stats | Inside Higher Ed

Without diminishing learning outcomes, automated teaching software can reduce the amount of time professors spend with students and could substantially reduce the cost of instruction, according to new research.
In experiments at six public universities, students assigned randomly to statistics courses that relied heavily on “machine-guided learning” software -- with reduced face time with instructors -- did just as well, in less time, as their counterparts in traditional, instructor-centric versions of the courses. This largely held true regardless of the race, gender, age, enrollment status and family background of the students.
The study comes at a time when “smart” teaching software is being increasingly included in conversations about redrawing the economics of higher education. Recent investments by high-profile universities in “massively open online courses,” or MOOCs, has elevated the notion that technology has reached a tipping point: with the right design, an online education platform, under the direction of a single professor, might be capable of delivering meaningful education to hundreds of thousands of students at once.
The new research from the nonprofit organization Ithaka was seeking to prove the viability of a less expansive application of “machine-guided learning” than the new MOOCs are attempting -- though one that nevertheless could have real implications for the costs of higher education.
The study, called “Interactive Learning Online at Public Universities,” involved students taking introductory statistics courses at six (unnamed) public universities. A total of 605 students were randomly assigned to take the course in a “hybrid” format: they met in person with their instructors for one hour a week; otherwise, they worked through lessons and exercises using an artificially intelligent learning platform developed by learning scientists at Carnegie Mellon University’s Open Learning Initiative.
Researchers compared these students against their peers in the traditional-format courses, for which students met with a live instructor for three hours per week, using several measuring sticks: whether they passed the course, their performance on a standardized test (the Comprehensive Assessment of Statistics), and the final exam for the course, which was the same for both sections of the course at each of the universities.

 via Monkey Cage