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Browsing All Posts published on »January, 2013«

Review of “Computational Investing, Part I” taught by Tucker Balch (Spring 2013)

January 28, 2013 by Tucker Balch

This is a summary of survey responses from 1,257 of the 25,589 students who enrolled in this course in Spring 2013. This review may of interest to students considering to take the third offering of this course starting at coursera on August 16, 2013. Advertisements

MOOC Student Demographics (Spring 2013)

January 27, 2013 by Tucker Balch

I report on survey responses from 1,207 of the 25,589 students who enrolled in a Massive Online Open Class (MOOC) titled “Computational Investing, Part I” via coursera.org in Spring 2013. The responses represent 56% of the students who completed the course and 2.5% of those who initially enrolled but did not complete it.

$10mm Trading Competition

January 17, 2013 by Tucker Balch

Here’s an interesting new approach to trading talent discovery: Offer investment capital to top portfolio managers.

Teaching a MOOC: Lessons Learned & Best Balch Practices

January 12, 2013 by Tucker Balch

I just completed teaching a MOOC on Computational Investing via coursera.org. I did some things right and a lot of things wrong. Here are my lessons learned from the first round. I’m very excited now about the second go at this, and the ability to make the course even better. Some of these items are […]

MOOC Monetization Begins: Student Identity Verification

January 12, 2013 by Tucker Balch

First step in providing value for course completion: Ensure that the student is who he says he is.

Students Are Customers

January 8, 2013 by Tucker Balch

Viewing students as customers makes sense for universities that compete for their tuition.

Are MOOC Startups Evil?

January 6, 2013 by Tucker Balch

Some folks attribute less than altruistic motives to startup companies providing Massive Online Open Courses (MOOCs). There is nothing bad in help, no doubts, like consulting and advising efficient tools (check this post), but sometimes it’s just too good to be true.