I have a special affinity for quantitative research. Specifically: I LOVE online survey work! It’s a very efficient method to gather lots of data at scale that is almost automatically formatted for easy analysis and visualization.
Even though I have past experience with designing, collecting and analyzing survey data around current events, politics and marketing, my academically-focused work this year really sharpened my survey skills. I used Qualtrics almost exclusively as the online platform for creating and administering surveys, and I recruited larger samples than I ever have before using Amazon Mechanical Turk (MTurk), Qualtrics‘ own panel aggregation and a study pool run by Carnegie Mellon University’s Center for Behavioral and Decision Research (CBDR). My collaborators and I also recruited participants through US-based Survey Monkey; Prolific Academic, a UK-based company that also recruits US-based workers; and QQ and SoJump survey platforms based in China.
The increased stakes and many unknowns I encountered as my research evolved led me to reach out on social media, at workshops and in my own labs for help and for new ideas. I also reached out to MTurk workers for advice on fine-tuning my surveys, and I signed up myself as an MTurk worker to see how it looks from the other side. Below, I share some of what I learned during this year’s academic work that may also benefit your own survey research.
Continue reading Tips from my online survey research in 2018
Recently, when working with undergraduates to design a new experiment, they told me that they preferred to recruit participants under 40 in order to control for age effects in attitudes toward using technology.
Actually, that’s not quite what they said. “Older people are slower to change to new technologies,” is the quote I remember.
I acknowledged that I had seen “age effects” in my recent research — which I had just asked them to read through, though that summary didn’t include in which direction the age effects were seen. For the pilot study, I conceded that it might be wise to narrow the sampling to an age range that is more easily recruited around a college campus.
But privately, I started wondering – Do I believe, as they apparently do, that older people are usually slower to “get” technology? After all, **I** am older than 40. I could argue that, given my life circumstances as an adult returning student, I am learning new technologies at a **faster** pace than those younger than me simply because I am playing catch-up. But, in my more honest moments, I know I am more set in my ways than when I was 20 or 25. … Except, I might only be set in ways that I’ve learned the hard way from bad experiences, including from technologies that promise more than they deliver, while I stay open to new possibilities. … Except, I’ve known plenty of tech curmudgeons older than me, so I very well might be the exception. Except, …
Continue reading Age effects: Correlation, causation, and socialization
People often ask me why I decided to study human-computer interaction after a long career in journalism and media. For me, it’s primarily because of the chance to be on the frontlines of tech innovation and explore the different ways that computing in its current forms — social, ubiquitous and immersive — are impacting media, the law and our society.
Continue reading Samsung Gear VR + Edge S7 could popularize virtual reality