Catching up with the Internet Era: Online data collection for researchers

In the world we humans spend a great deal of time connected to the internet, this is especially true for younger people – who are growing up surrounded by this technology. You can see this huge change over time in graph from Our World in Data below!

Alex post pic1
Source: http://data.worldbank.org/

Increasingly, researchers and companies are leveraging this remote access to behaviour to answer questions about how humans behave. Companies have been collecting ‘user data’ for years from online platforms, and using this inferred information about people to improve user experience, and in some cases sell more products to the correct people. The amount of data we are able to collect on behaviour is expanding exponentially, and at the same time so is the quality and modality of this data – as people connect different devices (like activity monitors, clocks, fridges). Wearable sensors are becoming particularly more frequent – often this data is stored using internet-based services.

 

Infographic: The Predicted Wearables Boom Is All About The Wrist | Statista
Taken from Statista

Psychology and cognitive science is starting to catch up on this trend, as it offers the ability to carry out controlled experiments on a much larger scale. This offers the opportunity to characterise subtle differences, that would be lost in the noise of small samples tested in a lab environment.

However, for many the task of running an online experiment is daunting; there are so many choices, and dealing with building, hosting and data processing can be tricky!

Web Browsers

A good starting point, and often the most straightforward, is building experiments to work in a web browser. The primary advantage of this is that you can run experiments on the vast majority of computers, and even mobile devices, with no installation overhead. There are some limitations though:

Compatibility:

Internet Explorer - sigh

With multiple different web browsers, operating systems, and devices, the possible combinations number in the 1000s. This can lead to unexpected bugs and errors in your experiment. A workaround is to restrict access to a few devices (see below for tips on how to do this in JavaScript) – but this is traded off with how many participants you would like to access.

Accuracy:

Web browsers were not designed to run reaction time experiments in, or present stimulus with millisecond precision. Despite this, some research has shown equivalent precision for Reaction Time, and Stimulus Presentation.

If you are very concerned still, you may utilise WebGL, a web graphics engine, which allows you to gain analogous presentation times to native programs, and even use a computer’s graphics card. Although this will be limited by the operating system and hardware of the user!

There are a number of tools that can help you with browser experiments. From fee-paying services like Gorilla, which deals with task building, hosting and data management for you, to fully open source projects like jsPsych, and PsychoPy’s PsychoJS – which deal with building experiments and data, but not hosting (although there are plans to develop a hosting and data storage solution). All of these offer a graphical user-interface, which allows experiments to be built without any prior knowledge of programming!

Unity

unity

One intermediate tool – which we are currently using – is cross platform development environment called Unity. Whilst originally intended for creating video-games, Unity can be repurposed for creating experimental apps. The large advantage is an easy capability to build to a vast variety of operating systems and platforms with minimal effort: a Unity project can be built for a web browser, iOS app, Android app, Windows, OSX, Linux…. and so on. You can also gain access to sensor information on devices (hear rate monitors, step counting, microphone, camera), to start to access the richness of information contained in these devices.

The utility of this tool for experimental research is huge, and apparently appears to be under-utilised – it has an easy to learn interface, and requires minimal programming knowledge.

Conclusion

Whilst this post is largely non-instructional, hopefully it has shed some light on the potential tools you can use to start running research online (without employing an expensive web or app developer), or hopefully just piqued your interest a tiny bit.

If you would like to dive in to the murky (but exciting) world of web development, you can also check out a few tips for improving the quality of your online data here.

 

 

This exciting post was written by Alexander Irvine, one of the newest members of our lab. Alex previously worked on developing web-based study at Oxford before joining the lab and is experienced in an array of programming languages and tools. Check out his personal website if you want to read more in-depth about online data collection.

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