Mixed methods data collection using simulated Google results: reflections on the methods of a point-of-selection behaviour study

Autor: Britanny Brannon, Erin M. Hood, Tara Tobin Cataldo, Randy Graff, Kailey Langer, Christopher Cyr, Summer Howland, Amy G. Buhler, Samuel R. Putnam, Joyce Kasman Valenza, Ixchel M. Faniel, Lynn Silipigni Connaway, Rachael Elrod
Rok vydání: 2020
Předmět:
Zdroj: Information Research: an international electronic journal. 25
ISSN: 1368-1613
Popis: Introduction. A multi-institutional, grant-funded project employed mixed methods to study 175 fourth-grade through graduate school students’ point-of-selection behaviour. The method features the use of simulated search engine results pages to facilitate data collection. Method. Student participants used simulated Google results pages to select resources for a hypothetical school project. Quantitative data on participants’ selection behaviour and qualitative data from their think-aloud protocols were collected. A questionnaire and interviews were used to collect data on participants’ backgrounds and online research experiences. Analysis. This paper reflects on the data collection methods and highlights opportunities for data analysis. The ability to analyse data both qualitatively and quantitatively increases the rigor and depth of findings. Results. The simulation created a realistic yet controlled environment that ensures the comparability of data within and across a wide range of educational stages. Combining data on participants’ behaviour, thoughts and characteristics provides a more complete picture of factors influencing online resource selection. Conclusions. Using simulated results pages in combination with multiple data collection methods enables analyses that create deeper knowledge of participants' information behaviour. Such a complicated research design requires extensive time, expertise and coordination to execute.
Databáze: OpenAIRE