Tag Archives: math


HEDLINE: Fantastec raises $800k Seed Round


Finnish educational games startup Fantastec raised a $800k Seed Round from Booster Investment and a group of angel investors reports Arctic Startup.

The funding will be used to grow the team, create multi-platform titles and to expand internationally.

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EdTech EuropePlanning to attend EdTech Europe 2014 on June 12th in London? Use the promo code EDUKWEST to get 20% off the ticket price!

EDUKWEST Sunday Review

Sunday Review for the Week of March 17th 2014

In this week’s Sunday Review we learn about the potential reasons why Coursera is allowed to give access to some of its courses to Iranian students, why VCs tend to get edtech wrong, who owns the rights to a MOOC when the instructor leaves the institution, why students sue Google, how semantic search will improve education, how researchers are chasing pageviews like bloggers and more.

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C12 Audio Podcast

C12 Interview: Ilan Samson of QAMA Calculator (Audio)

C12 Audio Podcast

C12 Interview: Ilan Samson of QAMA Calculator

  • recorded: July 27th 2012
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Enter QAMA, truly one of the coolest, most thoughtful, welcome bits of ed tech to hit math classrooms in a very long time. Created by Ilan Samson, a retired physicist and serial inventor, to address exactly the problems I described above, the QAMA calculator forces students to provide a reasonable estimate for their answer before it will output the exact answer.

C12 Interview Ilan Samson QAMA Calculator

C12 Interview: Ilan Samson of QAMA Calculator

Editor’s Note: The post originally appeared on ZDNet Education. Click here to read the entire post.

C12 Interview Ilan Samson QAMA Calculator

Calculators are designed to eliminate the need for repetitive, tedious arithmetic, leaving time to actually think about the math. When used correctly in the classroom, modern graphing calculators can do wonders for visualization, simulation, and encouraging that critical thought that we’re all after.

They were supposed to eliminate the tedium and simple mistakes that plague many calculations but instead have become the go-to device for any math problem. Worse, students frequently lack the mathematical savvy to know when the answer output by the calculator doesn’t make sense. Estimation, it would seem, is a lost art.

Enter QAMA, truly one of the coolest, most thoughtful, welcome bits of ed tech to hit math classrooms in a very long time. Created by Ilan Samson, a retired physicist and serial inventor, to address exactly the problems I described above, the QAMA calculator forces students to provide a reasonable estimate for their answer before it will output the exact answer.

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Ilan covered much more complex functionality later in our interview (I’m afraid that when you stick a couple of math geeks together, we can get a bit long-winded, so I didn’t include the entire interview here); however, the concept remains the same. Force students to demonstrate conceptual mastery and then give them the exact answer. The calculator is really quite amazing in its ability to determine appropriate degrees of allowable error and to prevent gaming of the system through any sort of trial and error. In fact, the logic built into the little machine would make one heck of a case study in a computer science class.

The calculator also allows for the estimating requirement to be turned off, but not with out a set of randomly flashing LEDs alerting instructors that students aren’t stepping through the full process in determining their answers. It isn’t often that a device will make me really say “Wow – this could be a game-changer.” The QAMA calculator, though, is precisely that. At around $20 a piece, these little devices are quite inexpensive and yet stand to change the way a couple generations of students have been using calculators. The ability to simply estimate is so critical in not just mathematics, but in all applications of math; the QAMA calculator is a no-brainer place to start in shifting the way our students learn math, logic, reasoning, and more.


On Mothers and Math: Behind the Buzz

As someone who has been relatively vocal about research rigor and how findings are interpreted (and sometimes misinterpreted) in the mainstream media, it was certainly interesting for me when a small study I did as a spin-off from my dissertation picked up a bit of buzz a few weeks back. To summarize, in an analysis of number-related language (e.g., “three cats,” “how many apples?”) in everyday speech, American mothers of toddlers (mean age 22 months) spoke two to three times more often about numbers and quantities when talking to boys compared to girls. After reading some of the questions and comments (some quite angry!) about the study, I thought it might be interesting to provide a bit of a behind-the-scenes look at how this paper came to be. I’ve addressed a few issues that directly deal with gender stereotyping – and why the study did not include fathers – in a previous Q&A with Mommyish.com, so I will try my best to not be repetitive.

I was originally studying differences between Mandarin Chinese and English speaking parents, how they talk to children about number before they enter formal schooling, and how this might contribute to the well-documented cross-national differences in math scores between Mandarin speaking countries (China, Singapore, Taiwan) and their English speaking counterparts (including the United States). I never failed to get at least one question about gender differences each time I presented the data. Since my research was actually about language and concept development, it took awhile after sorting the initial study out before I took the time to carefully look at what was happening between genders.

I needed to make sure that the age of the children and the amount of overall speech generally matched between boys and girls (i.e., I controlled for age and amount of speech) in order to compare between roughly equivalent groups of mother-son and mother-daughter pairs. The fact that only mothers were left after this matching process was purely circumstantial, not intentional. (However, at least one study has found that fathers show a greater bias toward boys than mothers when explaining science museum exhibits). My colleagues and I were both shocked and fascinated to find significant differences in number speech to boys and girls… but only in the American group. Over the next two years (that’s right, years), this paper was written and revised countless times. However, it was rejected no fewer than seven times from as many journals before finally being accepted and published in the Journal of Language and Social Psychology.

This is just one example of the stark difference in pace between academia and Silicon Valley. Between authors, reviewers, and editors, iterating on a manuscript can take months, if not years, for a variety of reasons. A lot of stress can result from a sometimes incredibly long peer review process. More than once have I wondered if a reviewer actually read my manuscript, and have become incredibly frustrated when reviews that don’t seem particularly negative result in a rejection for an unclear reason. Despite all of the challenges, I firmly believe in peer review as a tenet of the scientific process. I feel that it is important for articles that go down as scientific record to be reviewed by individuals with domain expertise. In addition, my co-authors and I knew that we had an important, compelling result, and knew that the only way that it would ever have any impact in the world (even just to us in our own careers!) would be to get it published in a peer-reviewed journal. And we finally succeeded… on the eighth try.

The amount of time it takes to design, run, analyze, implement, and then publish a research study is one of the reasons why there isn’t a lot of “hard evidence” about some of the current learning technologies Silicon Valley is buzzing about. Pilot results are one thing, but full randomized controlled trials are a whole different beast. Building a bridge between rigorous scientific research and development of technology is something that I feel is incredibly important, but has quite a ways to go. It is my hope that in this next phase of my career, I can make a contribution in this area, and perhaps even inspire more girls and women to pursue STEM!


Chang, A., Sandhofer, C.M., & Brown, C.S. (2011). Gender Biases in Early Number Exposure to Preschool-Aged Children. Journal of Language and Social Psychology, 30(4), 440-450.

Crowley, K., Callanan, M. A., Tenenbaum, H. R., & Allen, E. (2001). Parents explain more often to boys than girls during shared scientific thinking. Psychological Science, 12, 258-261.

Picture by kakisky