The EdTech Revolution for Researchers

04/24/2013 03:38 pm ET | Updated Jun 24, 2013
  • Corinne Bendersky Associate Professor of Management and Organizations, UCLA Anderson School of Management

Modern universities are complex organisms that house everything from economic development offices to TV stations to hospitals. But at their core, universities are still centered on teaching and research.

These roles are important -- maybe more vital than ever before. This might seem dramatic, but I don't think it's a stretch to suggest that the future of our enlightened society rests largely on how well we educate rising generations and the progress we make through academic research. Today's students are tomorrow's leaders, and today's research leads to tomorrow's business patents, medical breakthroughs and revelations about human behavior.

There has been a lot of focus recently on how technology is affecting teaching and learning, but the same thing is happening with research. Increasingly, my colleagues and I are abandoning antiquated methods of tabulating data on paper and moving to technology platforms instead. The technology revolution for research faculty is stretching budgets, improving accuracy and accelerating the rate of research by stripping away many cumbersome logistics.

The digitization of academic research has followed a pattern similar to consumer electronics, beginning with large, clunky devices and database machines filling entire rooms and evolving to Web-based software. The first breakthrough came when the first desktop scientific calculator was released by Hewlett-Packard in 1968 and subsequently popularized by Texas Instruments as a handheld device in the 1970s. Also in the late 1960s -- the heyday for mainframe computing -- a software program called SPSS emerged that allowed corporations and academic researchers to do complex data analysis.

All of these tools are helpful for crunching data once you have it, but it has taken a while to close the loop on digitizing the research process. In the last decade, new technology has improved the way we actually collect information, as well. In my field of study (organizational behavior), our research focuses on people. We survey them, observe them and put them through controlled experiments to gauge perceptions, attitudes, behaviors and other insights about what "makes us tick" and how we work together.

In human insight research like mine, Web-based tools have removed many of the logistical barriers of broader sampling, reduced the potential for human error and made the experience more enjoyable for respondents, all of which lead to better data. My colleagues and I have used tools like SurveyMonkey and Zoomerang, which are pretty well known these days, and more sophisticated platforms like Qualtrics, to gather information. The data we collect with these software platforms can be easily exported to database management programs like Excel, SPSS or STATA for analysis.

I recently completed a study that illustrates how technology has changed the way we do academic research. I have long been interested in the difference between perception and reality in the workplace, and how those perceptions change over time to reflect the actual value individuals bring to the organization. This kind of research requires doing surveys and controlled experiments, which involve staging various scenarios where the conditions change for each individual.

In the past, both of these methods would have consumed copious amounts of time and money, which are precious resources in the publish-or-perish world of academic research, especially given dwindling budgets. To survey members of an organization, for example, I would have to print hundreds of copies of a physical form -- each of which might be several pages long -- and provide self-addressed and stamped envelopes for each potential respondent to ensure confidentiality. Then, I would have to ask the organization to dedicate people to distributing and collecting the survey and the employees to spend time completing the survey during a narrow window in their work day.

The experimental portion would require me to print different versions of the materials and fret about whether research assistants keeping everything straight for accuracy and data integrity. In both cases, once collected, the data would have to be manually entered to computer programs in order to analyze, which introduces even more opportunities for human error.

By adding technology to the process, research faculty are bypassing these logistics and focusing their efforts on research design and analysis. For my study, I used a single technology platform -- the aforementioned Qualtrics -- to conduct both survey and experimental data collection. Rather than distributing hard surveys to an organization at great expense, I was able to extend the geographic reach of the survey and use a splashy Web interface to make the poll more appealing to increase response rates, expand the time period so people could complete the survey at their convenience and minimize human error in the data management process.

On the experimental side, I used a simulated instant messenger platform that created the impression that the subject was interacting with a real person who was in a different location. This level of sophistication increases the accuracy of the experiment and is increasingly the kind of thing that faculty don't need to have custom built by software programmers.

In this new age of technology-enabled research, academics are doing better work more efficiently and institutions are saving money. Just as advances in technology are changing how we deliver education, this same evolution is accelerating the rate and accuracy of scholarly discovery. And that's important for all of us.

Dr. Corinne Bendersky is an associate professor of management and organizations at UCLA's Anderson School of Management in Los Angeles.