Evaluation of a personalized digital library based on cognitive styles: Adaptivity vs. adaptability

Abstract

Personalization can be addressed by adaptability and adaptivity, which have different advantages and disadvantages. This study investigates how digital library users react to these two techniques. More specifically, we develop a personalized digital library to suit the needs of different cognitive styles based on the findings of our previous work (Frias-Martinez, et al., in press). The personalized digital library includes two versions: adaptive version and adaptable version. The results showed that users not only performed better in the adaptive version, but also they perceived more positively to the adaptive version. In addition, cognitive styles have great effects on users' responses to adaptability and adaptivity. These results provide guidance for designers to select suitable techniques to develop personalized digital libraries.

The impact of user- and system-initiated personalization on the user experience at large sports events

“…Martinez et al (2009) found that users performed better with, and reacted more positively to system-initiated personalization within digital libraries. In contrast, Park et al (2007) examined the effectiveness of user-initiated and system-initiated menus in desktop applications.…”

“…Martinez et al, 2009;Verpoorten et al, 2009;Sun and May, 2013) have shown that both user-generated and system-generated personalization have benefits within specific usage environments. 'Usergenerated' and 'system-generated' personalization are roughly equivalent to the terms 'adaptable' and 'adaptive used in the user modelling literature -i.e either allowing users themselves to adapt content and layout to their preferences, or having a system undertake this automatically (Treiblmaier et al, 2004).…”

A Survey of Recommender System Types and Its Classification

“…It was followed by a lot of works in the field of recommender systems which helped users to find products, services or content such as books, movies, music, television shows, electronic or digital products etc by applying various algorithms which reviews the different users and items to give proper suggestions [16] [17] [18]. The research works in the field of recommender systems will be organized in this paper based on its type.…”

Generic service integration in adaptive learning experiences using IMS learning design

“…The experience used GRAIL (Escobedo-del-Cid et al, 2007), the IMS LD engine integrated in the .LRN (http://www.dotlrn.org) Learning Management System, as supporting software. This engine includes a module implementing the exchange of information between the engine and generic external services as described in the GSI architecture (Frias-Martinez et al, 2009).…”

“…This material is called Adaptive Hypermedia (Brusilovsky, 2001). It is important to establish the difference between adaptable and adaptive content (Frias-Martinez, Chen, & Liu, 2009). Adaptable material is meant to enable users to adapt themselves the content layout and navigation support to their preferences.…”