To Blend or Not to Blend?: Perceptual Speed, Visual Memory and Aggregated Search

While aggregated search interfaces that present vertical results to searchers are fairly common in today's search environments, little is known about how searchers' cognitive abilities impact how they use and evaluate these interfaces. This study evaluates the relationship between two cognitive abilities ? perceptual speed and visual memory ? and searchers' behaviors and interface preferences when using two aggregated search interfaces: one that blends vertical results into the search results (blended) and one that does not (non-blended). Cognitive tests were administered to sixteen participants who subsequently performed four search tasks using the two interfaces. Participants' search interactions were logged and after searching, they rated the usability, engagement and effectiveness of each interface, as well as made comparative evaluations. Results showed that participants with low perceptual speed spent significantly more time completing tasks when using the blended interface, while those with high perceptual speed spent roughly equivalent amounts of time completing tasks with the two interfaces. Those with low perceptual speed also rated both interfaces as significantly less usable along many measures, and were less satisfied with their searches. There were also main effects for interface: participants rated the non-blended interface significantly more usable than the blended interface.

[1]  H. Harman,et al.  Kit of factor-referenced cognitive tests , 1976 .

[2]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[3]  Bryce Allen,et al.  Perceptual speed, learning and information retrieval performance , 1994, SIGIR '94.

[4]  Jaime Arguello,et al.  Task complexity, vertical display and user interaction in aggregated search , 2012, SIGIR '12.

[5]  Mounia Lalmas,et al.  A Task-Based Evaluation of an Aggregated Search Interface , 2009, SPIRE.

[6]  Maarten de Rijke,et al.  Aggregated search interface preferences in multi-session search tasks , 2013, SIGIR.

[7]  Jacek Gwizdka,et al.  Individual differences and task-based user interface evaluation: a case study of pending tasks in email , 2004, Interact. Comput..

[8]  Yiqun Liu,et al.  Influence of Vertical Result in Web Search Examination , 2015, SIGIR.

[9]  Elaine Toms,et al.  The development and evaluation of a survey to measure user engagement , 2010, J. Assoc. Inf. Sci. Technol..

[10]  Jaime Arguello,et al.  Development and Evaluation of Search Tasks for IIR Experiments using a Cognitive Complexity Framework , 2015, ICTIR.

[11]  Mark Sanderson,et al.  The effect of user characteristics on search effectiveness in information retrieval , 2011, Inf. Process. Manag..

[12]  Jaime Arguello,et al.  The effect of cognitive abilities on information search for tasks of varying levels of complexity , 2014, IIiX.

[13]  Michael C. Pyryt Human cognitive abilities: A survey of factor analytic studies , 1998 .