Digital data collection

Authors: Sara Price, Mona Sakr, Carey Jewitt and Berit Hendriksen  

The expanding range of online tools for collection and analysis of social media (e.g. for crawling and scraping social media content) are primarily focused on collecting text-based data and are limited in terms of accessing multimodal data.

MODE is exploring how these different data collection techniques can contribute to researching embodied learning in digital environments, together with investigating the value of digitally generated data and digital apps as data collection tools. For example, the use of a Geographical Position System (GPS) tracker app (on an iPad) was used to provide a cumulative trace of the routes taken by students during the exploration of WWII history and ‘condensed time’ to produce a spatial narrative of their trail. Digital apps have also been useful in generating digital data, for example, in the WWII study students used Evernote to create geo-tagged photographs, record audio narratives, and write captions to produce multimodal ‘notes’ that constituted a narrative linked to time and space. These were used to support student reflection, provide supplementary data to support the analysis of video data, as well as to enrich data sets for analysis.

Dynamic and static screen capture software is proving to be a useful tool for MODE. A study of infant interaction with finger painting Apps on the iPad has used dynamic screen capture (e.g. Quicktime screen record facility, Camtasia) to capture infants’ painting process in real-time alongside video recording of their interaction. Other projects on social media have used screen capture tools (e.g. Zotero, Little snapper) to collect whole websites as PDFs or images that can then be analysed in an offline setting. These can be combined with Computer Assisted Qualitative Data Analysis (CAQDAS) packages (e.g. Nvivo) and web browser extensions (e.g. Ncapture,  or TubeCatcher) to collect webpages, online PDFs and social media content. It can, for example, collect any twitter-profile page, tweets by a particular user, and tweets that include a particular word, phrase or hashtag, that can then be imported and analyzed using the Nvivo 10 package. Another key resource MODE uses to support the analysis of websites and blogs is ‘The Wayback Machine’, an archive of websites, containing snapshots of sites linked to dates, which makes it possible to search and analyze the changes made to sites over time. The British Library provides a similar service for with their UK Webarchive.


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